Long-term photovoltaic system degradation can be predicted through a simple, low-cost solution. The approach requires the configuration specification for a photovoltaic system, as well as measured photovoltaic production data and solar irradiance, such as measured by a reliable third party source using satellite imagery. Note the configuration specification can be derived. This information is used to simulate photovoltaic power production by the photovoltaic system, which is then evaluated against the measured photovoltaic production data. The simulated production is adjusted to infer degradation that can be projected over time to forecast long-term photovoltaic system degradation.
A system and method for personal energy-related changes payback evaluation with the aid of a digital computer are provided. An overall thermal performance of a building is estimated. One or more proposed replacements for existing equipment associated with an individual associated with the building is received. An annual electric consumption associated with the existing equipment is determined. The consumption associated the existing equipment is converted into a time series that includes a plurality of values that are each associated with a time interval. Renewable energy production data associated with the building is obtained. The time series is combined with the photovoltaic production data to obtain time series net consumption data. A cost associated with the time series net consumption data is determined. A payback associated with replacing the existing equipment is estimated using the cost.
G06Q 10/0631 - Resource planning, allocation, distributing or scheduling for enterprises or organisations
G01K 3/08 - Thermometers giving results other than momentary value of temperature giving differences of valuesThermometers giving results other than momentary value of temperature giving differentiated values
G01K 13/00 - Thermometers specially adapted for specific purposes
G01K 17/20 - Measuring quantity of heat conveyed by flowing media, e.g. in heating systems based upon measurement of temperature difference across a radiating surface, combined with ascertainment of the heat-transmission coefficient
G01R 21/02 - Arrangements for measuring electric power or power factor by thermal methods
Improved energy conservation, including realization of a ZNET (Zero Net Energy including Transportation) paradigm, can be encouraged by providing energy consumers with a holistic view of their overall energy consumption. Current energy consumption in terms of space heating, water heating, other electricity, and personal transportation can be modeled by normalizing the respective energy consumption into the same units of energy. Options for reducing energy that can include traditional energy efficiencies, such as cutting down on and avoiding wasteful energy use and switching to energy efficient fixtures, and improving the thermal efficiency and performance of a building, can be modeled. Additional options can also include non-traditional energy efficiencies, such as replacing a gasoline-powered vehicle with an electric vehicle, fuel switching from a water heater fueled by natural gas to a heat pump water heater, and fuel switching from space heating fueled by natural gas to a heat pump space heater.
A Thermal Performance Forecast approach is described that can be used to forecast heating and cooling fuel consumption based on changes to user preferences and building-specific parameters that include indoor temperature, building insulation, HVAC system efficiency, and internal gains. A simplified version of the Thermal Performance Forecast approach, called the Approximated Thermal Performance Forecast, provides a single equation that accepts two fundamental input parameters and four ratios that express the relationship between the existing and post-change variables for the building properties to estimate future fuel consumption. The Approximated Thermal Performance Forecast approach marginally sacrifices accuracy for a simplified forecast. In addition, the thermal conductivity, effective window area, and thermal mass of a building can be determined using different combinations of utility consumption, outdoor temperature data, indoor temperature data, internal heating gains data, and HVAC system efficiency as inputs.
G05B 13/02 - Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric
5.
SYSTEM AND METHOD FOR BUILDING WATER-HEATING-BASED GROSS ENERGY LOAD MODIFICATION MODELING WITH THE AID OF A DIGITAL COMPUTER
Gross energy load can be determined by combining periodic net load statistics, such as provided by a power utility or energy agency, with on-site power generation, such as photovoltaic power generation, as produced over the same time period. The gross energy load provides an indication upon which other types of energy investment choices can be evaluated. These choices can include traditional energy efficiencies, such as implementing electrical efficiency measures, which includes cutting down on and avoiding wasteful energy use and switching to energy efficient fixtures, and improving the thermal efficiency and performance of a building. The choices can also include non-traditional energy efficiencies, such as replacing a gasoline-powered vehicle with an electric vehicle, fuel switching from a water heater fueled by natural gas to a heat pump water heater, and fuel switching from space heating fueled by natural gas to a heat pump space heater.
A photovoltaic system's configuration specification can be inferred by an evaluative process that searches through a space of candidate values for the variables in the specification. Each variable is selected in a specific ordering that narrows the field of candidate values. A constant horizon is assumed to account for diffuse irradiance insensitive to specific obstruction locations relative to the photovoltaic system's geographic location. Initial values for the azimuth angle, constant horizon obstruction elevation angle, and tilt angle are determined, followed by final values for these variables. The effects of direct obstructions that block direct irradiance in the areas where the actual horizon and the range of sun path values overlap relative to the geographic location are evaluated to find the exact obstruction elevation angle over a range of azimuth bins or directions. The photovoltaic temperature response coefficient and the inverter rating or power curve of the photovoltaic system are determined.
H02S 50/00 - Monitoring or testing of PV systems, e.g. load balancing or fault identification
G06F 30/13 - Architectural design, e.g. computer-aided architectural design [CAAD] related to design of buildings, bridges, landscapes, production plants or roads
7.
SYSTEM AND METHOD FOR ESTIMATING SASONAL NET CARBON EMISSIONS SAVINGS WITH THE AID OF A DIGITAL COMPUTER
A system and method for estimating seasonal net carbon emissions savings with the aid of a digital computer is provided. Efficiencies of electricity generation as supplied to a building and of the building's cooling and heating systems are obtained. Carbon emissions of electricity and natural gas consumption are obtained. A cooling season duration and a heating season duration that together include seasonal changes affecting the building are defined. A net carbon emissions savings afforded by an electric energy efficiency associated with the building is evaluated as a function of a reduction in electricity consumption afforded by the electric energy efficiency times the electricity consumption carbon emissions plus an inverse of the cooling system efficiency based on the cooling season duration less the natural gas consumption carbon emissions over the heating system efficiency based on the heating season duration, wherein the electric energy efficiency is implemented based on the evaluation.
G06F 30/13 - Architectural design, e.g. computer-aided architectural design [CAAD] related to design of buildings, bridges, landscapes, production plants or roads
G06F 119/08 - Thermal analysis or thermal optimisation
G06Q 10/04 - Forecasting or optimisation specially adapted for administrative or management purposes, e.g. linear programming or "cutting stock problem"
SYSTEM AND METHOD FOR REDUCING PEAK ENERGY CONSUMPTION LOAD OF A RENEWABLE-RESOURCE-POWER-PRODUCTION- SYSTEM-CONNECTED BUILDING WITH THE AID OF A DIGITAL COMPUTER
HVAC load can be shifted to change indoor temperature. A time series change in HVAC load data is used as input modified scenario values that represent an HVAC load shape. The HVAC load shape is selected to meet desired energy savings goals, such as reducing or flattening peak energy consumption load to reduce peak energy consumption load. Time series change in indoor temperature data can be calculated using only inputs of time series change in the time series HVAC load data combined with thermal mass, thermal conductivity, and HVAC efficiency. The approach is applicable for both winter and summer and can be applied when the building has an on-site renewable power system.
F24F 11/30 - Control or safety arrangements for purposes related to the operation of the system, e.g. for safety or monitoring
F24F 11/46 - Improving electric energy efficiency or saving
F24F 11/62 - Control or safety arrangements characterised by the type of control or by internal processing, e.g. using fuzzy logic, adaptive control or estimation of values
A graphical workflow definition and management tool enables administrators and other authorized users to implement a workflow process that can be used to evaluate project submissions or other applications that require step-by-step process completion. The steps required to navigate through the workflow are first defined. Inputs, outputs, and actions, including conditional criteria, can be specified for the steps. The flow of control between the individual steps in the workflow is mapped out; changes to the status of a project submission can cause a submission to migrate to a succeeding step in the workflow. A “sandbox” testing environment allows changes to any aspect of the workflow to be safely evaluated without affecting live data. Conflicts between production and test workflows are identified and intelligently resolved.
Improved energy conservation, including realization of a ZNET (Zero Net Energy including Transportation) paradigm, can be encouraged by providing energy consumers with a holistic view of their overall energy consumption. Current energy consumption in terms of space heating, water heating, other electricity, and personal transportation can be modeled by normalizing the respective energy consumption into the same units of energy. Options for reducing energy that can include traditional energy efficiencies, such as cutting down on and avoiding wasteful energy use and switching to energy efficient fixtures, and improving the thermal efficiency and performance of a building, can be modeled. Additional options can also include non-traditional energy efficiencies, such as replacing a gasoline-powered vehicle with an electric vehicle, fuel switching from a water heater fueled by natural gas to a heat pump water heater, and fuel switching from space heating fueled by natural gas to a heat pump space heater.
The accuracy of photovoltaic simulation modeling is predicated upon the selection of a type of solar resource data appropriate to the form of simulation desired. Photovoltaic power simulation requires irradiance data. Photovoltaic energy simulation requires normalized irradiation data. Normalized irradiation is not always available, such as in photovoltaic plant installations where only point measurements of irradiance are sporadically collected or even entirely absent. Normalized irradiation can be estimated through several methodologies, including assuming that normalized irradiation simply equals irradiance, directly estimating normalized irradiation, applying linear interpolation to irradiance, applying linear interpolation to clearness index values, and empirically deriving irradiance weights. The normalized irradiation can then be used to forecast photovoltaic fleet energy production.
G01W 1/02 - Instruments for indicating weather conditions by measuring two or more variables, e.g. humidity, pressure, temperature, cloud cover or wind speed
G06Q 10/04 - Forecasting or optimisation specially adapted for administrative or management purposes, e.g. linear programming or "cutting stock problem"
G06F 17/11 - Complex mathematical operations for solving equations
H02S 50/00 - Monitoring or testing of PV systems, e.g. load balancing or fault identification
A system and method for personal energy-related changes payback evaluation with the aid of a digital computer are provided. An overall thermal performance of a building is estimated. One or more proposed replacements for existing equipment associated with an individual associated with the building is received. An annual electric consumption associated with the existing equipment is determined. The consumption associated the existing equipment is converted into a time series that includes a plurality of values that are each associated with a time interval. Renewable energy production data associated with the building is obtained. The time series is combined with the photovoltaic production data to obtain time series net consumption data. A cost associated with the time series net consumption data is determined. A payback associated with replacing the existing equipment is estimated using the cost.
G06Q 10/0631 - Resource planning, allocation, distributing or scheduling for enterprises or organisations
G01K 3/08 - Thermometers giving results other than momentary value of temperature giving differences of valuesThermometers giving results other than momentary value of temperature giving differentiated values
G01K 17/20 - Measuring quantity of heat conveyed by flowing media, e.g. in heating systems based upon measurement of temperature difference across a radiating surface, combined with ascertainment of the heat-transmission coefficient
G01R 21/02 - Arrangements for measuring electric power or power factor by thermal methods
A system and method for balance-point-thermal-conductivity-based building analysis with the aid of a digital computer are provided. A total thermal conductivity of a building is obtained. A balance point thermal conductivity of the building is identified. The balance point thermal conductivity is divided by an area of the building to obtain the balance point thermal conductivity per unit of the area. A further balance point thermal conductivity per the unit of a further area of at least one further building and a further total thermal conductivity of the at least one further building is obtained. The balance point thermal conductivity per unit of the area of the building is compared to the further balance point thermal conductivity per the unit of the further area of the at least one further building and the total thermal conductivity is compared to the further total conductivity of the at least one building.
G06F 30/20 - Design optimisation, verification or simulation
F24F 11/64 - Electronic processing using pre-stored data
G05B 15/02 - Systems controlled by a computer electric
F24F 11/62 - Control or safety arrangements characterised by the type of control or by internal processing, e.g. using fuzzy logic, adaptive control or estimation of values
Gross energy load can be determined by combining periodic net load statistics, such as provided by a power utility or energy agency, with on-site power generation, such as photovoltaic power generation, as produced over the same time period. The gross energy load provides an indication upon which other types of energy investment choices can be evaluated. These choices can include traditional energy efficiencies, such as implementing electrical efficiency measures, which includes cutting down on and avoiding wasteful energy use and switching to energy efficient fixtures, and improving the thermal efficiency and performance of a building. The choices can also include non-traditional energy efficiencies, such as replacing a gasoline-powered vehicle with an electric vehicle, fuel switching from a water heater fueled by natural gas to a heat pump water heater, and fuel switching from space heating fueled by natural gas to a heat pump space heater.
A graphical workflow definition and management tool enables administrators and other authorized users to implement a workflow process that can be used to evaluate project submissions or other applications that require step-by-step process completion. The steps required to navigate through the workflow are first defined. Inputs, outputs, and actions, including conditional criteria, can be specified for the steps. The flow of control between the individual steps in the workflow is mapped out; changes to the status of a project submission can cause a submission to migrate to a succeeding step in the workflow. A “sandbox” testing environment allows changes to any aspect of the workflow to be safely evaluated without affecting live data. Conflicts between production and test workflows are identified and intelligently resolved.
A Thermal Performance Forecast approach is described that can be used to forecast heating and cooling fuel consumption based on changes to user preferences and building-specific parameters that include indoor temperature, building insulation, HVAC system efficiency, and internal gains. A simplified version of the Thermal Performance Forecast approach, called the Approximated Thermal Performance Forecast, provides a single equation that accepts two fundamental input parameters and four ratios that express the relationship between the existing and post-change variables for the building properties to estimate future fuel consumption. The Approximated Thermal Performance Forecast approach marginally sacrifices accuracy for a simplified forecast. In addition, the thermal conductivity, effective window area, and thermal mass of a building can be determined using different combinations of utility consumption, outdoor temperature data, indoor temperature data, internal heating gains data, and HVAC system efficiency as inputs.
F24F 11/30 - Control or safety arrangements for purposes related to the operation of the system, e.g. for safety or monitoring
G05B 13/02 - Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric
F24F 110/00 - Control inputs relating to air properties
F24F 130/00 - Control inputs relating to environmental factors not covered by group
The overall thermal performance of a building UATotal can be empirically estimated through a short-duration controlled test. Preferably, the controlled test is performed at night during the winter. A heating source is turned off after the indoor temperature has stabilized. After an extended period, such as 12 hours, the heating source is briefly turned back on, such as for an hour, then turned off. The indoor temperature is allowed to stabilize. The energy consumed within the building during the test period is assumed to equal internal heat gains. Overall thermal performance is estimated by balancing the heat gained with the heat lost during the test period.
G06Q 10/0631 - Resource planning, allocation, distributing or scheduling for enterprises or organisations
G01K 3/08 - Thermometers giving results other than momentary value of temperature giving differences of valuesThermometers giving results other than momentary value of temperature giving differentiated values
G01R 21/02 - Arrangements for measuring electric power or power factor by thermal methods
G01K 17/20 - Measuring quantity of heat conveyed by flowing media, e.g. in heating systems based upon measurement of temperature difference across a radiating surface, combined with ascertainment of the heat-transmission coefficient
Long-term photovoltaic system degradation can be predicted through a simple, low-cost solution. The approach requires the configuration specification for a photovoltaic system, as well as measured photovoltaic production data and solar irradiance, such as measured by a reliable third party source using satellite imagery. Note the configuration specification can be derived. This information is used to simulate photovoltaic power production by the photovoltaic system, which is then evaluated against the measured photovoltaic production data. The simulated production is adjusted to infer degradation that can be projected over time to forecast long-term photovoltaic system degradation.
A system and method for seasonal energy consumption determination using verified energy loads with the aid of a digital computer are provided. A digital computer is operated, including: obtaining energy loads for a building measured over a seasonal time period; obtaining outdoor temperatures for the building as measured over the seasonal time period; verifying stability of the energy loads, including: evaluating the energy loads over time; and identifying at least one of one or more discontinuities and one or more irregularities in the energy loads based on the evaluation. Operating the computer further includes: determining a baseload energy consumption using at least some of those of the energy loads; calculating seasonal fuel consumption rates and balance point temperatures; and disaggregating seasonal fuel consumption based on the baseload energy consumption, seasonal fuel consumption rates, balance point temperatures, and at least some of the outdoor temperatures into component loads of consumption.
G06Q 10/04 - Forecasting or optimisation specially adapted for administrative or management purposes, e.g. linear programming or "cutting stock problem"
G06Q 10/02 - Reservations, e.g. for tickets, services or events
A system and method for determining a balance point of a building that has undergone or is about to undergo modifications (such as shell improvements) are provided. A balance point of the building before the modifications can be determined using empirical data. Total thermal conductivity of the building before and after the modifications is determined and compared. Indoor temperature of the building is obtained. The balance point temperature after the modifications can be determined using a result of the comparison, the temperature inside the building, and the pre-modification balance point temperature. Knowing post-modification balance point temperature allows power grid operators to take into account fuel consumption by that building when planning for power production and distribution. Knowing the post-improvement balance point temperature also provides owners of the building information on which they can base the decision whether to implement the improvements.
Improved energy conservation, including realization of a ZNET (Zero Net Energy including Transportation) paradigm, can be encouraged by providing energy consumers with a holistic view of their overall energy consumption. Current energy consumption in terms of space heating, water heating, other electricity, and personal transportation can be modeled by normalizing the respective energy consumption into the same units of energy. Options for reducing energy that can include traditional energy efficiencies, such as cutting down on and avoiding wasteful energy use and switching to energy efficient fixtures, and improving the thermal efficiency and performance of a building, can be modeled. Additional options can also include non-traditional energy efficiencies, such as replacing a gasoline-powered vehicle with an electric vehicle, fuel switching from a water heater fueled by natural gas to a heat pump water heater, and fuel switching from space heating fueled by natural gas to a heat pump space heater.
A system and method for building energy-related changes evaluation with the aid of a digital computer are provided. Obtained is a total amount of fuel purchased for a building over a set period from which an existing amount of the fuel consumed for space heating is derived. Characteristics including thermal performance and furnace and delivery efficiencies of the building for both existing and proposed equipment are obtained, including remotely controlling a heating source inside the building. The thermal performance and furnace and delivery efficiencies characteristics of the existing and proposed equipment are expressed as interrelated ratios. An amount of fuel to be consumed for space heating is evaluated as a function of the existing amount of the fuel consumed for space heating and the ratios of the existing and proposed equipment.
G06Q 10/0631 - Resource planning, allocation, distributing or scheduling for enterprises or organisations
G01K 3/08 - Thermometers giving results other than momentary value of temperature giving differences of valuesThermometers giving results other than momentary value of temperature giving differentiated values
G01R 21/02 - Arrangements for measuring electric power or power factor by thermal methods
G01K 17/20 - Measuring quantity of heat conveyed by flowing media, e.g. in heating systems based upon measurement of temperature difference across a radiating surface, combined with ascertainment of the heat-transmission coefficient
G01K 13/00 - Thermometers specially adapted for specific purposes
23.
System and method for building heating and gross energy load modification modeling with the aid of a digital computer
Gross energy load can be determined by combining periodic net load statistics, such as provided by a power utility or energy agency, with on-site power generation, such as photovoltaic power generation, as produced over the same time period. The gross energy load provides an indication upon which other types of energy investment choices can be evaluated. These choices can include traditional energy efficiencies, such as implementing electrical efficiency measures, which includes cutting down on and avoiding wasteful energy use and switching to energy efficient fixtures, and improving the thermal efficiency and performance of a building. The choices can also include non-traditional energy efficiencies, such as replacing a gasoline-powered vehicle with an electric vehicle, fuel switching from a water heater fueled by natural gas to a heat pump water heater, and fuel switching from space heating fueled by natural gas to a heat pump space heater.
A system and method for determining a balance point of a building that has undergone or is about to undergo modifications (such as shell improvements) are provided. A balance point of the building before the modifications can be determined using empirical data. Total thermal conductivity of the building before and after the modifications is determined and compared. Indoor temperature of the building is obtained. The balance point temperature after the modifications can be determined using a result of the comparison, the temperature inside the building, and the pre-modification balance point temperature. Knowing post-modification balance point temperature allows power grid operators to take into account fuel consumption by that building when planning for power production and distribution. Knowing the post-improvement balance point temperature also provides owners of the building information on which they can base the decision whether to implement the improvements.
A photovoltaic system's configuration specification can be inferred by an evaluative process that searches through a space of candidate values for the variables in the specification. Each variable is selected in a specific ordering that narrows the field of candidate values. A constant horizon is assumed to account for diffuse irradiance insensitive to specific obstruction locations relative to the photovoltaic system's geographic location. Initial values for the azimuth angle, constant horizon obstruction elevation angle, and tilt angle are determined, followed by final values for these variables. The effects of direct obstructions that block direct irradiance in the areas where the actual horizon and the range of sun path values overlap relative to the geographic location are evaluated to find the exact obstruction elevation angle over a range of azimuth bins or directions. The photovoltaic temperature response coefficient and the inverter rating or power curve of the photovoltaic system are determined.
H02S 50/00 - Monitoring or testing of PV systems, e.g. load balancing or fault identification
G06F 30/13 - Architectural design, e.g. computer-aided architectural design [CAAD] related to design of buildings, bridges, landscapes, production plants or roads
26.
System and method for renewable power system interconnection workflow processing with the aid of a digital computer
A graphical workflow definition and management tool enables administrators and other authorized users to implement a workflow process that can be used to evaluate project submissions or other applications that require step-by-step process completion. The steps required to navigate through the workflow are first defined. Inputs, outputs, and actions, including conditional criteria, can be specified for the steps. The flow of control between the individual steps in the workflow is mapped out; changes to the status of a project submission can cause a submission to migrate to a succeeding step in the workflow. A “sandbox” testing environment allows changes to any aspect of the workflow to be safely evaluated without affecting live data. Conflicts between production and test workflows are identified and intelligently resolved.
Long-term photovoltaic system degradation can be predicted through a simple, low-cost solution. The approach requires the configuration specification for a photovoltaic system, as well as measured photovoltaic production data and solar irradiance, such as measured by a reliable third party source using satellite imagery. Note the configuration specification can be derived. This information is used to simulate photovoltaic power production by the photovoltaic system, which is then evaluated against the measured photovoltaic production data. The simulated production is adjusted to infer degradation that can be projected over time to forecast long-term photovoltaic system degradation.
A Thermal Performance Forecast approach is described that can be used to forecast heating and cooling fuel consumption based on changes to user preferences and building-specific parameters that include indoor temperature, building insulation, HVAC system efficiency, and internal gains. A simplified version of the Thermal Performance Forecast approach, called the Approximated Thermal Performance Forecast, provides a single equation that accepts two fundamental input parameters and four ratios that express the relationship between the existing and post-change variables for the building properties to estimate future fuel consumption. The Approximated Thermal Performance Forecast approach marginally sacrifices accuracy for a simplified forecast. In addition, the thermal conductivity, effective window area, and thermal mass of a building can be determined using different combinations of utility consumption, outdoor temperature data, indoor temperature data, internal heating gains data, and HVAC system efficiency as inputs.
F24F 11/30 - Control or safety arrangements for purposes related to the operation of the system, e.g. for safety or monitoring
G05B 13/02 - Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric
HVAC load can be shifted to change indoor temperature. A time series change in HVAC load data is used as input modified scenario values that represent an HVAC load shape. The HVAC load shape is selected to meet desired energy savings goals, such as reducing or flattening peak energy consumption load to reduce demand charges, moving HVAC consumption to take advantage of lower utility rates, or moving HVAC consumption to match PV production. Time series change in indoor temperature data can be calculated using only inputs of time series change in the time series HVAC load data combined with thermal mass, thermal conductivity, and HVAC efficiency. The approach is applicable for both winter and summer and can be applied when the building has an on-site renewable power system.
F24F 11/62 - Control or safety arrangements characterised by the type of control or by internal processing, e.g. using fuzzy logic, adaptive control or estimation of values
F24F 11/46 - Improving electric energy efficiency or saving
The accuracy of photovoltaic simulation modeling is predicated upon the selection of a type of solar resource data appropriate to the form of simulation desired. Photovoltaic power simulation requires irradiance data. Photovoltaic energy simulation requires normalized irradiation data. Normalized irradiation is not always available, such as in photovoltaic plant installations where only point measurements of irradiance are sporadically collected or even entirely absent. Normalized irradiation can be estimated through several methodologies, including assuming that normalized irradiation simply equals irradiance, directly estimating normalized irradiation, applying linear interpolation to irradiance, applying linear interpolation to clearness index values, and empirically deriving irradiance weights. The normalized irradiation can then be used to forecast photovoltaic fleet energy production.
G01W 1/02 - Instruments for indicating weather conditions by measuring two or more variables, e.g. humidity, pressure, temperature, cloud cover or wind speed
G06Q 10/04 - Forecasting or optimisation specially adapted for administrative or management purposes, e.g. linear programming or "cutting stock problem"
G06F 17/11 - Complex mathematical operations for solving equations
H02S 50/00 - Monitoring or testing of PV systems, e.g. load balancing or fault identification
A system and method to evaluate building cooling fuel consumption with the aid of a digital computer is described. The evaluation can be used for quantifying personalized electric and fuel bill savings. Such savings may be associated with investment decisions relating to building envelope improvements; HVAC equipment improvements; delivery system efficiency improvements; and fuel switching. The results can also be used for assessing the cost/benefit of behavioral changes, such as changing thermostat temperature settings. Similarly, the results can be used for optimizing an HVAC control system algorithm based on current and forecasted outdoor temperature and on current and forecasted solar irradiance to satisfy consumer preferences in a least cost manner. Finally, the results can be used to correctly size a photovoltaic (PV) system to satisfy needs prior to investments by anticipating existing energy usage and the associated change in usage based on planned investments.
G06F 30/20 - Design optimisation, verification or simulation
F24F 11/64 - Electronic processing using pre-stored data
G05B 15/02 - Systems controlled by a computer electric
F24F 11/62 - Control or safety arrangements characterised by the type of control or by internal processing, e.g. using fuzzy logic, adaptive control or estimation of values
A Thermal Performance Forecast approach is described that can be used to forecast heating and cooling fuel consumption based on changes to user preferences and building-specific parameters that include indoor temperature, building insulation, HVAC system efficiency, and internal gains. A simplified version of the Thermal Performance Forecast approach, called the Approximated Thermal Performance Forecast, provides a single equation that accepts two fundamental input parameters and four ratios that express the relationship between the existing and post-change variables for the building properties to estimate future fuel consumption. The Approximated Thermal Performance Forecast approach marginally sacrifices accuracy for a simplified forecast. In addition, the thermal conductivity, effective window area, and thermal mass of a building can be determined using different combinations of utility consumption, outdoor temperature data, indoor temperature data, internal heating gains data, and HVAC system efficiency as inputs.
F24F 11/30 - Control or safety arrangements for purposes related to the operation of the system, e.g. for safety or monitoring
G05B 13/02 - Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric
A system and method for determining seasonal energy consumption with the aid of a digital computer is provided. Through a power metering energy loads for a building situated in a known location are assessed as measured over a seasonal time period. Outdoor temperatures for the building are assessed as measured over the seasonal time period through a temperature monitoring infrastructure. A digital computer comprising a processor and a memory that is adapted to store program instructions for execution by the processor is operated, the program instructions capable of: expressing each energy load as a function of the outdoor temperature measured at the same time of the seasonal time period in point-intercept form; and taking a slope of the point-intercept form as the fuel rate of energy consumption during the seasonal time period.
G06Q 10/04 - Forecasting or optimisation specially adapted for administrative or management purposes, e.g. linear programming or "cutting stock problem"
G06Q 10/02 - Reservations, e.g. for tickets, services or events
A photovoltaic system's configuration specification can be inferred by an evaluative process that searches through a space of candidate values for the variables in the specification. Each variable is selected in a specific ordering that narrows the field of candidate values. A constant horizon is assumed to account for diffuse irradiance insensitive to specific obstruction locations relative to the photovoltaic system's geographic location. Initial values for the azimuth angle, constant horizon obstruction elevation angle, and tilt angle are determined, followed by final values for these variables. The effects of direct obstructions that block direct irradiance in the areas where the actual horizon and the range of sun path values overlap relative to the geographic location are evaluated to find the exact obstruction elevation angle over a range of azimuth bins or directions. The photovoltaic temperature response coefficient and the inverter rating or power curve of the photovoltaic system are determined.
G06F 30/20 - Design optimisation, verification or simulation
G01J 1/42 - Photometry, e.g. photographic exposure meter using electric radiation detectors
G06F 30/13 - Architectural design, e.g. computer-aided architectural design [CAAD] related to design of buildings, bridges, landscapes, production plants or roads
35.
System and method for facilitating building net energy consumption reduction with the aid of a digital computer
Improved energy conservation, including realization of a ZNET (Zero Net Energy including Transportation) paradigm, can be encouraged by providing energy consumers with a holistic view of their overall energy consumption. Current energy consumption in terms of space heating, water heating, other electricity, and personal transportation can be modeled by normalizing the respective energy consumption into the same units of energy. Options for reducing energy that can include traditional energy efficiencies, such as cutting down on and avoiding wasteful energy use and switching to energy efficient fixtures, and improving the thermal efficiency and performance of a building, can be modeled. Additional options can also include non-traditional energy efficiencies, such as replacing a gasoline-powered vehicle with an electric vehicle, fuel switching from a water heater fueled by natural gas to a heat pump water heater, and fuel switching from space heating fueled by natural gas to a heat pump space heater.
Improved energy conservation, including realization of a ZNET (Zero Net Energy including Transportation) paradigm, can be encouraged by providing energy consumers with a holistic view of their overall energy consumption. Current energy consumption in terms of space heating, water heating, other electricity, and personal transportation can be modeled by normalizing the respective energy consumption into the same units of energy. In addition, the passive always-on electricity consumption caused by inactive devices that contributes to the baseload of a building can be identified and addressed by the consumer, as appropriate by expressing baseload as a compound value that combines constant always-on loads and regularly-cycling loads. The baseload is estimated as the peak occurrence in a frequency distribution of net load data, after which the always-on load can be determined by subtracting out any regularly-cycling loads.
Gross energy load can be determined by combining periodic net load statistics, such as provided by a power utility or energy agency, with on-site power generation, such as photovoltaic power generation, as produced over the same time period. The gross energy load provides an indication upon which other types of energy investment choices can be evaluated. These choices can include traditional energy efficiencies, such as implementing electrical efficiency measures, which includes cutting down on and avoiding wasteful energy use and switching to energy efficient fixtures, and improving the thermal efficiency and performance of a building. The choices can also include non-traditional energy efficiencies, such as replacing a gasoline-powered vehicle with an electric vehicle, fuel switching from a water heater fueled by natural gas to a heat pump water heater, and fuel switching from space heating fueled by natural gas to a heat pump space heater.
A system and method for interactively evaluating energy-related investments affecting building envelope with the aid of a digital computer are provided. Obtained is a total amount of fuel purchased for a building over a set period from which an existing amount of the fuel consumed for space heating is derived. Characteristics including thermal performance and furnace and delivery efficiencies of the building for both existing and proposed equipment are obtained, including remotely controlling a heating source inside the building. The thermal performance and furnace and delivery efficiencies characteristics of the existing and proposed equipment are expressed as interrelated ratios. An amount of fuel to be consumed for space heating is evaluated as a function of the existing amount of the fuel consumed for space heating and the ratios of the existing and proposed equipment.
G01K 13/00 - Thermometers specially adapted for specific purposes
G01K 3/08 - Thermometers giving results other than momentary value of temperature giving differences of valuesThermometers giving results other than momentary value of temperature giving differentiated values
G01R 21/02 - Arrangements for measuring electric power or power factor by thermal methods
G01K 17/20 - Measuring quantity of heat conveyed by flowing media, e.g. in heating systems based upon measurement of temperature difference across a radiating surface, combined with ascertainment of the heat-transmission coefficient
39.
System and method for performing power utility remote consumer energy auditing with the aid of a digital computer
A system and method to analyze building performance without requiring an on-site energy audit or customer input is described. The analysis combines total customer energy load from a power utility with externally-supplied meteorological data to analyze each customer's building performance. Building thermal performance is characterized to produce a rich dataset that the power utility can use in planning and operation, including assessing on-going and forecasted power consumption, and for other purposes, such as providing customers with customized information to inform their energy investment decisions and identifying homes for targeted efficiency funding.
H02S 50/00 - Monitoring or testing of PV systems, e.g. load balancing or fault identification
H02J 3/38 - Arrangements for parallelly feeding a single network by two or more generators, converters or transformers
G06Q 10/04 - Forecasting or optimisation specially adapted for administrative or management purposes, e.g. linear programming or "cutting stock problem"
G06Q 10/02 - Reservations, e.g. for tickets, services or events
Improved energy conservation, including realization of a ZNET (Zero Net Energy including Transportation) paradigm, can be encouraged by providing energy consumers with a holistic view of their overall energy consumption. Current energy consumption in terms of space heating, water heating, other electricity, and personal transportation can be modeled by normalizing the respective energy consumption into the same units of energy. Options for reducing energy that can include traditional energy efficiencies, such as cutting down on and avoiding wasteful energy use and switching to energy efficient fixtures, and improving the thermal efficiency and performance of a building, can be modeled. Additional options can also include non-traditional energy efficiencies, such as replacing a gasoline-powered vehicle with an electric vehicle, fuel switching from a water heater fueled by natural gas to a heat pump water heater, and fuel switching from space heating fueled by natural gas to a heat pump space heater.
A graphical workflow definition and management tool enables administrators and other authorized users to implement a workflow process that can be used to evaluate project submissions or other applications that require step-by-step process completion. The steps required to navigate through the workflow are first defined. Inputs, outputs, and actions, including conditional criteria, can be specified for the steps. The flow of control between the individual steps in the workflow is mapped out; changes to the status of a project submission can cause a submission to migrate to a succeeding step in the workflow. A “sandbox” testing environment allows changes to any aspect of the workflow to be safely evaluated without affecting live data. Conflicts between production and test workflows are identified and intelligently resolved.
Long-term photovoltaic system degradation can be predicted through a simple, low-cost solution. The approach requires the configuration specification for a photovoltaic system, as well as measured photovoltaic production data and solar irradiance, such as measured by a reliable third party source using satellite imagery. Note the configuration specification can be derived. This information is used to simulate photovoltaic power production by the photovoltaic system, which is then evaluated against the measured photovoltaic production data. The simulated production is adjusted to infer degradation that can be projected over time to forecast long-term photovoltaic system degradation.
The accuracy of photovoltaic simulation modeling is predicated upon the selection of a type of solar resource data appropriate to the form of simulation desired. Photovoltaic power simulation requires irradiance data. Photovoltaic energy simulation requires normalized irradiation data. Normalized irradiation is not always available, such as in photovoltaic plant installations where only point measurements of irradiance are sporadically collected or even entirely absent. Normalized irradiation can be estimated through several methodologies, including assuming that normalized irradiation simply equals irradiance, directly estimating normalized irradiation, applying linear interpolation to irradiance, applying linear interpolation to clearness index values, and empirically deriving irradiance weights. The normalized irradiation can then be used to forecast photovoltaic fleet energy production.
G01W 1/02 - Instruments for indicating weather conditions by measuring two or more variables, e.g. humidity, pressure, temperature, cloud cover or wind speed
G06Q 10/04 - Forecasting or optimisation specially adapted for administrative or management purposes, e.g. linear programming or "cutting stock problem"
G06F 17/11 - Complex mathematical operations for solving equations
H02J 3/38 - Arrangements for parallelly feeding a single network by two or more generators, converters or transformers
H02S 50/00 - Monitoring or testing of PV systems, e.g. load balancing or fault identification
Improved energy conservation, including realization of a ZNET (Zero Net Energy including Transportation) paradigm, can be encouraged by providing energy consumers with a holistic view of their overall energy consumption. Current energy consumption in terms of space heating, water heating, other electricity, and personal transportation can be modeled by normalizing the respective energy consumption into the same units of energy. In addition, the passive always-on electricity consumption caused by inactive devices that contributes to the baseload of a building can be identified and addressed by the consumer, as appropriate by expressing baseload as a compound value that combines constant always-on loads and regularly-cycling loads. The baseload is estimated as the peak occurrence in a frequency distribution of net load data, after which the always-on load can be determined by subtracting out any regularly-cycling loads.
Total can be empirically estimated through a short-duration controlled test. Preferably, the controlled test is performed at night during the winter. A heating source is turned off after the indoor temperature has stabilized. After an extended period, such as 12 hours, the heating source is briefly turned back on, such as for an hour, then turned off. The indoor temperature is allowed to stabilize. The energy consumed within the building during the test period is assumed to equal internal heat gains. Overall thermal performance is estimated by balancing the heat gained with the heat lost during the test period.
G01K 3/08 - Thermometers giving results other than momentary value of temperature giving differences of valuesThermometers giving results other than momentary value of temperature giving differentiated values
G01R 21/02 - Arrangements for measuring electric power or power factor by thermal methods
G01K 17/20 - Measuring quantity of heat conveyed by flowing media, e.g. in heating systems based upon measurement of temperature difference across a radiating surface, combined with ascertainment of the heat-transmission coefficient
G06Q 10/06 - Resources, workflows, human or project managementEnterprise or organisation planningEnterprise or organisation modelling
The calculation of the variance of a correlation coefficient matrix for a photovoltaic fleet can be completed in linear space as a function of decreasing distance between pairs of photovoltaic plant locations. When obtaining irradiance data from a satellite imagery source, irradiance statistics must first be converted from irradiance statistics for an area into irradiance statistics for an average point within a pixel in the satellite imagery. The average point statistics are then averaged across all satellite pixels to determine the average across the whole photovoltaic fleet region. Where pairs of photovoltaic systems are located too far away from each other to be statistically correlated, the correlation coefficients in the matrix for that pair of photovoltaic systems are effectively zero. Consequently, the double summation portion of the calculation can be simplified to eliminate zero values based on distance between photovoltaic plant locations, substantially decreasing the size of the problem space.
G06Q 10/04 - Forecasting or optimisation specially adapted for administrative or management purposes, e.g. linear programming or "cutting stock problem"
G01W 1/02 - Instruments for indicating weather conditions by measuring two or more variables, e.g. humidity, pressure, temperature, cloud cover or wind speed
H02J 3/38 - Arrangements for parallelly feeding a single network by two or more generators, converters or transformers
H02S 50/00 - Monitoring or testing of PV systems, e.g. load balancing or fault identification
G16Z 99/00 - Subject matter not provided for in other main groups of this subclass
47.
Computer-implemented system and method for estimating gross energy load of a building
Gross energy load can be determined by combining periodic net load statistics, such as provided by a power utility or energy agency, with on-site power generation, such as photovoltaic power generation, as produced over the same time period. The gross energy load provides an indication upon which other types of energy investment choices can be evaluated. These choices can include traditional energy efficiencies, such as implementing electrical efficiency measures, which includes cutting down on and avoiding wasteful energy use and switching to energy efficient fixtures, and improving the thermal efficiency and performance of a building. The choices can also include non-traditional energy efficiencies, such as replacing a gasoline-powered vehicle with an electric vehicle, fuel switching from a water heater fueled by natural gas to a heat pump water heater, and fuel switching from space heating fueled by natural gas to a heat pump space heater.
Potential energy investment scenarios can be evaluated. Energy performance specifications and prices for both existing and proposed energy-related equipment are selected, from which an initial capital cost is determined. The equipment selections are combined with current fuel consumption data, thermal characteristics of the building, and, as applicable, solar resource and other weather data to create an estimate of the fuel consumption of the proposed equipment. An electricity bill is calculated for the proposed equipment, from which an annual cost is determined. The payback of the proposed energy investment is found by comparing the initial and annual costs.
A graphical workflow definition and management tool enables administrators and other authorized users to implement a workflow process that can be used to evaluate project submissions or other applications that require step-by-step process completion. The steps required to navigate through the workflow are first defined. Inputs, outputs, and actions, including conditional criteria, can be specified for the steps. The flow of control between the individual steps in the workflow is mapped out; changes to the status of a project submission can cause a submission to migrate to a succeeding step in the workflow. A “sandbox” testing environment allows changes to any aspect of the workflow to be safely evaluated without affecting live data. Conflicts between production and test workflows are identified and intelligently resolved.
A system and method to evaluate building heating fuel consumption with the aid of a digital computer is described. The evaluation can be used for quantifying personalized electric and fuel bill savings. Such savings may be associated with investment decisions relating to building envelope improvements; HVAC equipment improvements; delivery system efficiency improvements; and fuel switching. The results can also be used for assessing the cost/benefit of behavioral changes, such as changing thermostat temperature settings. Similarly, the results can be used for optimizing an HVAC control system algorithm based on current and forecasted outdoor temperature and on current and forecasted solar irradiance to satisfy consumer preferences in a least cost manner. Finally, the results can be used to correctly size a photovoltaic (PV) system to satisfy needs prior to investments by anticipating existing energy usage and the associated change in usage based on planned investments.
G06F 30/20 - Design optimisation, verification or simulation
F24F 11/64 - Electronic processing using pre-stored data
G05B 15/02 - Systems controlled by a computer electric
F24F 11/62 - Control or safety arrangements characterised by the type of control or by internal processing, e.g. using fuzzy logic, adaptive control or estimation of values
Long-term photovoltaic system degradation can be predicted through a simple, low-cost solution. The approach requires the configuration specification for a photovoltaic system, as well as measured photovoltaic production data and solar irradiance, such as measured by a reliable third party source using satellite imagery. Note the configuration specification can be derived. This information is used to simulate photovoltaic power production by the photovoltaic system, which is then evaluated against the measured photovoltaic production data to determine the degree of error between simulated and measured production. The simulated production is adjusted to account for the error and to infer degradation that can be projected over time to forecast long-term photovoltaic system degradation.
A system and method for modeling building thermal performance parameters through empirical testing with the aid of a digital computer is described. Three building-specific parameters, thermal conductivity, thermal mass, and effective window area, are empirically derived. Thermal conductivity is evaluated through an empirical test conducted in the absence of solar gain with constant indoor temperature and no HVAC. Thermal mass is evaluated through a second empirical test conducted in the absence of solar gain and no HVAC. Effective window area is evaluated through a third empirical test conducted in the presence of solar gain and no HVAC. Thermal HVAC system power rating and conversion and delivery efficiency are also parametrized. The parameters are estimated using short duration tests that last at most several days. A value of energy savings associated with changing one or more parameters is evaluated.
F24F 11/64 - Electronic processing using pre-stored data
G05B 15/02 - Systems controlled by a computer electric
F24F 11/62 - Control or safety arrangements characterised by the type of control or by internal processing, e.g. using fuzzy logic, adaptive control or estimation of values
53.
System for tuning a photovoltaic power generation plant forecast with the aid of a digital computer
A system for tuning a photovoltaic power generation plant forecast with the aid of a digital computer is provided. Global horizontal irradiance (GHI), ambient temperature and wind speed for a photovoltaic power generation plant over a forecast period are obtained. Simulated plane-of-array (POA) irradiance is generated from the GHI and the plant's photovoltaic array configuration as a series of simulated observations. Inaccuracies in GHI conversion are identified and the simulated POA irradiance at each simulated observation is corrected based on the conversion inaccuracies. Simulated module temperature is generated based on the simulated POA irradiance, ambient temperature and wind speed. Simulated power generation over the forecast period is generated based on the simulated POA irradiance, simulated module temperature and the plant's specifications and status. Inaccuracies in photovoltaic power conversion are identified and the simulated power generation at each simulated input power level is corrected based on the power conversion inaccuracies.
G06F 30/20 - Design optimisation, verification or simulation
H02S 50/00 - Monitoring or testing of PV systems, e.g. load balancing or fault identification
54.
System and method for forecasting fuel consumption for indoor thermal conditioning using thermal performance forecast approach with the aid of a digital computer
A system and method for forecasting fuel consumption for indoor thermal conditioning using thermal performance forecast approach with the aid of a digital computer are provided. Average daily outdoor temperatures for a time period are obtained. Historical daily fuel consumption for the time period is obtained. The historical daily fuel consumption is converted into an average daily fuel usage rates for the time period. A continuous frequency distribution of occurrences of the average daily outdoor temperatures is generated. A plot of the daily fuel usage rates versus the average daily outdoor temperatures is created. Fuel consumption for at least a portion of the time period is calculated based on sampling the daily fuel usage rate along a range of average daily outdoor temperatures times the temperatures' respective frequencies of occurrence.
G01B 13/00 - Measuring arrangements characterised by the use of fluids
F24F 11/30 - Control or safety arrangements for purposes related to the operation of the system, e.g. for safety or monitoring
G05B 13/02 - Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric
A computer-implemented system and method to determine building thermal performance parameters through empirical testing is described. Three building-specific parameters, thermal conductivity, thermal mass, and effective window area, are empirically derived. Thermal conductivity is evaluated through an empirical test conducted in the absence of solar gain with constant indoor temperature and no HVAC. Thermal mass is evaluated through a second empirical test conducted in the absence of solar gain and no HVAC. Effective window area is evaluated through a third empirical test conducted in the presence of solar gain and no HVAC. Thermal HVAC system power rating and conversion and delivery efficiency are also parametrized. The parameters are estimated using short duration tests that last at most several days. The parameters and estimated HVAC system efficiency can be used to simulate a time series of indoor building temperature, annual fuel consumption, or maximum indoor temperature.
A system and method to evaluate building heating fuel consumption with the aid of a digital computer is described. The evaluation can be used for quantifying personalized electric and fuel bill savings. Such savings may be associated with investment decisions relating to building envelope improvements; HVAC equipment improvements; delivery system efficiency improvements; and fuel switching. The results can also be used for assessing the cost/benefit of behavioral changes, such as changing thermostat temperature settings. Similarly, the results can be used for optimizing an HVAC control system algorithm based on current and forecasted outdoor temperature and on current and forecasted solar irradiance to satisfy consumer preferences in a least cost manner. Finally, the results can be used to correctly size a photovoltaic (PV) system to satisfy needs prior to investments by anticipating existing energy usage and the associated change in usage based on planned investments.
A system and method to determine building thermal performance parameters through empirical testing is described. The parameters can be formulaically applied to determine fuel consumption and indoor temperatures. To generalize the approach, the term used to represent furnace rating is replaced with HVAC system rating. As total heat change is based on the building's thermal mass, heat change is relabeled as thermal mass gain (or loss). This change creates a heat balance equation that is composed of heat gain (loss) from six sources, three of which contribute to heat gain only. No modifications are required for apply the empirical tests to summer since an attic's thermal conductivity cancels out and the attic's effective window area is directly combined with the existing effective window area. Since these tests are empirically based, the tests already account for the additional heat gain associated with the elevated attic temperature and other surface temperatures.
G06F 30/13 - Architectural design, e.g. computer-aided architectural design [CAAD] related to design of buildings, bridges, landscapes, production plants or roads
G06Q 10/04 - Forecasting or optimisation specially adapted for administrative or management purposes, e.g. linear programming or "cutting stock problem"
G06F 119/08 - Thermal analysis or thermal optimisation
58.
System and method for estimating photovoltaic energy generation through linearly interpolated irradiance observations with the aid of a digital computer
The accuracy of photovoltaic simulation modeling is predicated upon the selection of a type of solar resource data appropriate to the form of simulation desired. Photovoltaic power simulation requires irradiance data. Photovoltaic energy simulation requires normalized irradiation data. Normalized irradiation is not always available, such as in photovoltaic plant installations where only point measurements of irradiance are sporadically collected or even entirely absent. Normalized irradiation can be estimated through several methodologies, including assuming that normalized irradiation simply equals irradiance, directly estimating normalized irradiation, applying linear interpolation to irradiance, applying linear interpolation to clearness index values, and empirically deriving irradiance weights. The normalized irradiation can then be used to forecast photovoltaic fleet energy production.
G01W 1/02 - Instruments for indicating weather conditions by measuring two or more variables, e.g. humidity, pressure, temperature, cloud cover or wind speed
G06Q 10/04 - Forecasting or optimisation specially adapted for administrative or management purposes, e.g. linear programming or "cutting stock problem"
G06F 17/11 - Complex mathematical operations for solving equations
H02J 3/38 - Arrangements for parallelly feeding a single network by two or more generators, converters or transformers
H02S 50/00 - Monitoring or testing of PV systems, e.g. load balancing or fault identification
A computer-implemented system and method for tuning photovoltaic power generation plant forecasting is provided. Global horizontal irradiance (GHI), ambient temperature and wind speed for a photovoltaic power generation plant over a forecast period are obtained. Simulated plane-of-array (POA) irradiance is generated from the GHI and the plant's photovoltaic array configuration as a series of simulated observations. Inaccuracies in GHI conversion are identified and the simulated POA irradiance at each simulated observation is corrected as a function of the conversion inaccuracies. Simulated module temperature is generated based on the simulated POA irradiance, ambient temperature and wind speed. Simulated power generation over the forecast period is generated based on the simulated POA irradiance, simulated module temperature and the plant's specifications and status. Inaccuracies in photovoltaic power conversion are identified and the simulated power generation at each simulated input power level is corrected as a function of the power conversion inaccuracies.
A Thermal Performance Forecast approach is described that can be used to forecast heating and cooling fuel consumption based on changes to user preferences and building-specific parameters that include indoor temperature, building insulation, HVAC system efficiency, and internal gains. A simplified version of the Thermal Performance Forecast approach, called the Approximated Thermal Performance Forecast, provides a single equation that accepts two fundamental input parameters and four ratios that express the relationship between the existing and post-change variables for the building properties to estimate future fuel consumption. The Approximated Thermal Performance Forecast approach marginally sacrifices accuracy for a simplified forecast. In addition, the thermal conductivity, effective window area, and thermal mass of a building can be determined using different combinations of utility consumption, outdoor temperature data, indoor temperature data, internal heating gains data, and HVAC system efficiency as inputs.
G05B 13/00 - Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion
F24F 11/30 - Control or safety arrangements for purposes related to the operation of the system, e.g. for safety or monitoring
G05B 13/02 - Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric
F24F 110/00 - Control inputs relating to air properties
A computer-implemented system and method to assist consumers with decisions affecting a change in fuel requirements is provided. Fuel consumption for heating can be considered by evaluating changes that would affect thermal conductivity, average indoor temperature, HVAC efficiency, and solar gain. In a further embodiment, a computer-implemented system and method to evaluate investment's in a building's shell is provided. Thermal conductivity and the surface area of a surface that is under consideration for improvement are obtained, after which revised thermal conductivity can be modeled based on the existing and proposed thermal performance of that building surface. In a still further embodiment, fuel consumption for heating modeling results can be comparatively evaluated, with one fuel consumption model operating over an annual (or periodic) scope and another fuel consumption model operating on an hourly (or interval) scope.
A computer-implemented system and method to evaluate building heating fuel consumption is described. The evaluation can be used for quantifying personalized electric and fuel bill savings. Such savings may be associated with investment decisions relating to building envelope improvements; HVAC equipment improvements; delivery system efficiency improvements; and fuel switching. The results can also be used for assessing the cost/benefit of behavioral changes, such as changing thermostat temperature settings. Similarly, the results can be used for optimizing an HVAC control system algorithm based on current and forecasted outdoor temperature and on current and forecasted solar irradiance to satisfy consumer preferences in a least cost manner. Finally, the results can be used to correctly size a photovoltaic (PV) system to satisfy needs prior to investments by anticipating existing energy usage and the associated change in usage based on planned investments.
A system and method to determine building thermal performance parameters through empirical testing is described. The parameters can be formulaically applied to determine fuel consumption and indoor temperatures. To generalize the approach, the term used to represent furnace rating is replaced with HVAC system rating. As total heat change is based on the building's thermal mass, heat change is relabeled as thermal mass gain (or loss). This change creates a heat balance equation that is composed of heat gain (loss) from six sources, three of which contribute to heat gain only. No modifications are required for apply the empirical tests to summer since an attic's thermal conductivity cancels out and the attic's effective window area is directly combined with the existing effective window area. Since these tests are empirically based, the tests already account for the additional heat gain associated with the elevated attic temperature and other surface temperatures.
The calculation of the variance of a correlation coefficient matrix for a photovoltaic fleet can be completed in linear space as a function of decreasing distance between pairs of photovoltaic plant locations. When obtaining irradiance data from a satellite imagery source, irradiance statistics must first be converted from irradiance statistics for an area into irradiance statistics for an average point within a pixel in the satellite imagery. The average point statistics are then averaged across all satellite pixels to determine the average across the whole photovoltaic fleet region. Where pairs of photovoltaic systems are located too far away from each other to be statistically correlated, the correlation coefficients in the matrix for that pair of photovoltaic systems are effectively zero. Consequently, the double summation portion of the calculation can be simplified to eliminate zero values based on distance between photovoltaic plant locations, substantially decreasing the size of the problem space.
G01W 1/02 - Instruments for indicating weather conditions by measuring two or more variables, e.g. humidity, pressure, temperature, cloud cover or wind speed
G06Q 10/04 - Forecasting or optimisation specially adapted for administrative or management purposes, e.g. linear programming or "cutting stock problem"
H02J 3/38 - Arrangements for parallelly feeding a single network by two or more generators, converters or transformers
H02S 50/00 - Monitoring or testing of PV systems, e.g. load balancing or fault identification
H02J 3/00 - Circuit arrangements for ac mains or ac distribution networks
G06F 19/00 - Digital computing or data processing equipment or methods, specially adapted for specific applications (specially adapted for specific functions G06F 17/00;data processing systems or methods specially adapted for administrative, commercial, financial, managerial, supervisory or forecasting purposes G06Q;healthcare informatics G16H)
65.
System and method for aligning HVAC consumption with photovoltaic production with the aid of a digital computer
HVAC load can be shifted to change indoor temperature. A time series change in HVAC load data is used as input modified scenario values that represent an HVAC load shape. The HVAC load shape is selected to meet desired energy savings goals, such as reducing or flattening peak energy consumption load to reduce demand charges, moving HVAC consumption to take advantage of lower utility rates, or moving HVAC consumption to match PV production. Time series change in indoor temperature data can be calculated using only inputs of time series change in the time series HVAC load data combined with thermal mass, thermal conductivity, and HVAC efficiency. The approach is applicable for both winter and summer and can be applied when the building has an on-site PV system.
F24F 11/62 - Control or safety arrangements characterised by the type of control or by internal processing, e.g. using fuzzy logic, adaptive control or estimation of values
F24F 11/46 - Improving electric energy efficiency or saving
2 concentration monitoring device, which enables the infiltration component of total thermal conductivity to be measured directly. The conduction component of thermal conductivity can then be determined by subtracting the infiltration component from the building's total thermal conductivity.
A photovoltaic system's configuration specification can be inferred by an evaluative process that searches through a space of candidate values for the variables in the specification. Each variable is selected in a specific ordering that narrows the field of candidate values. A constant horizon is assumed to account for diffuse irradiance insensitive to specific obstruction locations relative to the photovoltaic system's geographic location. Initial values for the azimuth angle, constant horizon obstruction elevation angle, and tilt angle are determined, followed by final values for these variables. The effects of direct obstructions that block direct irradiance in the areas where the actual horizon and the range of sun path values overlap relative to the geographic location are evaluated to find the exact obstruction elevation angle over a range of azimuth bins or directions. The photovoltaic temperature response coefficient and the inverter rating or power curve of the photovoltaic system are determined.
G06F 30/20 - Design optimisation, verification or simulation
G01J 1/42 - Photometry, e.g. photographic exposure meter using electric radiation detectors
G06F 30/13 - Architectural design, e.g. computer-aided architectural design [CAAD] related to design of buildings, bridges, landscapes, production plants or roads
H02S 50/00 - Monitoring or testing of PV systems, e.g. load balancing or fault identification
System and method for providing constraint-based heating, ventilation and air-conditioning (HVAC) system optimization with the aid of a digital computer
HVAC load can be shifted to change indoor temperature. A time series change in HVAC load data is used as input modified scenario values that represent an HVAC load shape. The HVAC load shape is selected to meet desired energy savings goals, such as reducing or flattening peak energy consumption load to reduce demand charges, moving HVAC consumption to take advantage of lower utility rates, or moving HVAC consumption to match PV production. Time series change in indoor temperature data can be calculated using only inputs of time series change in the time series HVAC load data combined with thermal mass, thermal conductivity, and HVAC efficiency. The approach is applicable for both winter and summer and can be applied when the building has an on-site PV system.
G05B 15/02 - Systems controlled by a computer electric
F24F 11/30 - Control or safety arrangements for purposes related to the operation of the system, e.g. for safety or monitoring
F24F 11/62 - Control or safety arrangements characterised by the type of control or by internal processing, e.g. using fuzzy logic, adaptive control or estimation of values
2 concentration monitoring device, which enables the infiltration component of total thermal conductivity to be measured directly. The conduction component of thermal conductivity can then be determined by subtracting the infiltration component from the building's total thermal conductivity.
A photovoltaic system's configuration specification can be inferred by an evaluative process that searches through a space of candidate values for the variables in the specification. Each variable is selected in a specific ordering that narrows the field of candidate values. A constant horizon is assumed to account for diffuse irradiance insensitive to specific obstruction locations relative to the photovoltaic system's geographic location. Initial values for the azimuth angle, constant horizon obstruction elevation angle, and tilt angle are determined, followed by final values for these variables. The effects of direct obstructions that block direct irradiance in the areas where the actual horizon and the range of sun path values overlap relative to the geographic location are evaluated to find the exact obstruction elevation angle over a range of azimuth bins or directions. The photovoltaic temperature response coefficient and the inverter rating or power curve of the photovoltaic system are determined.
Total can be empirically estimated through a short-duration controlled test. Preferably, the controlled test is performed at night during the winter. A heating source, such as a furnace, is turned off after the indoor temperature has stabilized. After an extended period, such as 12 hours, the heating source is briefly turned back on, such as for an hour, then turned off. The indoor temperature is allowed to stabilize. The energy consumed within the building during the test period is assumed to equal internal heat gains. Overall thermal performance is estimated by balancing the heat gained with the heat lost during the test period.
G01K 13/00 - Thermometers specially adapted for specific purposes
G01K 3/08 - Thermometers giving results other than momentary value of temperature giving differences of valuesThermometers giving results other than momentary value of temperature giving differentiated values
G01R 21/02 - Arrangements for measuring electric power or power factor by thermal methods
G01K 17/20 - Measuring quantity of heat conveyed by flowing media, e.g. in heating systems based upon measurement of temperature difference across a radiating surface, combined with ascertainment of the heat-transmission coefficient
72.
Apparatus and method for empirically estimating overall thermal performance of a building with the aid of a digital computer
Total can be empirically estimated through a short-duration controlled test. Preferably, the controlled test is performed at night during the winter. A heating source, such as a furnace, is turned off after the indoor temperature has stabilized. After an extended period, such as 12 hours, the heating source is briefly turned back on, such as for an hour, then turned off. The indoor temperature is allowed to stabilize. The energy consumed within the building during the test period is assumed to equal internal heat gains. Overall thermal performance is estimated by balancing the heat gained with the heat lost during the test period.
G01K 13/00 - Thermometers specially adapted for specific purposes
G01R 21/02 - Arrangements for measuring electric power or power factor by thermal methods
G01K 3/08 - Thermometers giving results other than momentary value of temperature giving differences of valuesThermometers giving results other than momentary value of temperature giving differentiated values
73.
System and method for net load-based inference of operational specifications of a photovoltaic power generation system with the aid of a digital computer
A system and method for net load-based inference of operational specifications of a photovoltaic power generation system with the aid of a digital computer are provided. Photovoltaic plant configuration specifications can be accurately inferred with net load data and measured solar resource data. Power generation data is simulated for a range of hypothetical photovoltaic system configurations based on a normalized solar power simulation model. Net load data is estimated based on one or more component loads. The set of key parameters corresponding to the net load estimate that minimizes total squared error represents the inferred specifications of the photovoltaic plant configuration.
G06Q 10/04 - Forecasting or optimisation specially adapted for administrative or management purposes, e.g. linear programming or "cutting stock problem"
G06Q 10/02 - Reservations, e.g. for tickets, services or events
A computer-implemented system and method for inferring operational specifications of a photovoltaic power generation system using net load is provided. Photovoltaic plant configuration specifications can be accurately inferred with net load data and measured solar resource data. A time series of net load data is evaluated to identify, if possible, a time period with preferably minimum and consistent power consumption. Power generation data is simulated for a range of hypothetical photovoltaic system configurations based on a normalized solar power simulation model. Net load data is estimated based on a base load and, if applicable, any binary loads and any variable loads. The set of key parameters corresponding to the net load estimate that minimizes total squared error represents the inferred specifications of the photovoltaic plant configuration.
The accuracy of photovoltaic simulation modeling is predicated upon the selection of a type of solar resource data appropriate to the form of simulation desired. Photovoltaic power simulation requires irradiance data. Photovoltaic energy simulation requires normalized irradiation data. Normalized irradiation is not always available, such as in photovoltaic plant installations where only point measurements of irradiance are sporadically collected or even entirely absent. Normalized irradiation can be estimated through several methodologies, including assuming that normalized irradiation simply equals irradiance, directly estimating normalized irradiation, applying linear interpolation to irradiance, applying linear interpolation to clearness index values, and empirically deriving irradiance weights. The normalized irradiation can then be used to forecast photovoltaic fleet energy production.
G01R 21/133 - Arrangements for measuring electric power or power factor by using digital technique
G01W 1/02 - Instruments for indicating weather conditions by measuring two or more variables, e.g. humidity, pressure, temperature, cloud cover or wind speed
G06Q 10/04 - Forecasting or optimisation specially adapted for administrative or management purposes, e.g. linear programming or "cutting stock problem"
The accuracy of photovoltaic simulation modeling is predicated upon the selection of a type of solar resource data appropriate to the form of simulation desired. Photovoltaic power simulation requires irradiance data. Photovoltaic energy simulation requires normalized irradiation data. Normalized irradiation is not always available, such as in photovoltaic plant installations where only point measurements of irradiance are sporadically collected or even entirely absent. Normalized irradiation can be estimated through several methodologies, including assuming that normalized irradiation simply equals irradiance, directly estimating normalized irradiation, applying linear interpolation to irradiance, applying linear interpolation to clearness index values, and empirically deriving irradiance weights. The normalized irradiation can then be used to forecast photovoltaic fleet energy production.
Probabilistic forecasts of the expected power production of renewable power sources, such as solar and wind, are generally provided with a degree of uncertainty. The expected power production for a fleet can be projected as a time series of power production estimates over a time period ahead of the current time. The uncertainty of each power production estimate can be combined with the costs and risks associated with power generation forecasting errors, and displayed or visually graphed as a single, deterministic result to assist power grid operators (or planners) in deciding whether to rely on the renewable power source.
42 - Scientific, technological and industrial services, research and design
Goods & Services
(1) Providing an on-line computer database featuring trade information in the field of irradiance data.
(2) Providing online non-downloadable software and an online non-downloadable application programming interface for providing irradiance data and simulation services for planning, mapping, validation and management of grid-connect energy systems.
The calculation of the variance of a correlation coefficient matrix for a photovoltaic fleet can be completed in linear space as a function of decreasing distance between pairs of photovoltaic plant locations. When obtaining irradiance data from a satellite imagery source, irradiance statistics must first be converted from irradiance statistics for an area into irradiance statistics for an average point within a pixel in the satellite imagery. The average point statistics are then averaged across all satellite pixels to determine the average across the whole photovoltaic fleet region. Where pairs of photovoltaic systems are located too far away from each other to be statistically correlated, the correlation coefficients in the matrix for that pair of photovoltaic systems are effectively zero. Consequently, the double summation portion of the calculation can be simplified to eliminate zero values based on distance between photovoltaic plant locations, substantially decreasing the size of the problem space.
G01W 1/02 - Instruments for indicating weather conditions by measuring two or more variables, e.g. humidity, pressure, temperature, cloud cover or wind speed
G06F 19/00 - Digital computing or data processing equipment or methods, specially adapted for specific applications (specially adapted for specific functions G06F 17/00;data processing systems or methods specially adapted for administrative, commercial, financial, managerial, supervisory or forecasting purposes G06Q;healthcare informatics G16H)
G06Q 10/04 - Forecasting or optimisation specially adapted for administrative or management purposes, e.g. linear programming or "cutting stock problem"
H02J 3/38 - Arrangements for parallelly feeding a single network by two or more generators, converters or transformers
H02S 50/00 - Monitoring or testing of PV systems, e.g. load balancing or fault identification
The calculation of the variance of a correlation coefficient matrix for a photovoltaic fleet can be completed in linear space as a function of decreasing distance between pairs of photovoltaic plant locations. When obtaining irradiance data from a satellite imagery source, irradiance statistics must first be converted from irradiance statistics for an area into irradiance statistics for an average point within a pixel in the satellite imagery. The average point statistics are then averaged across all satellite pixels to determine the average across the whole photovoltaic fleet region. Where pairs of photovoltaic systems are located too far away from each other to be statistically correlated, the correlation coefficients in the matrix for that pair of photovoltaic systems are effectively zero. Consequently, the double summation portion of the calculation can be simplified to eliminate zero values based on distance between photovoltaic plant locations, substantially decreasing the size of the problem space.
G06F 19/00 - Digital computing or data processing equipment or methods, specially adapted for specific applications (specially adapted for specific functions G06F 17/00;data processing systems or methods specially adapted for administrative, commercial, financial, managerial, supervisory or forecasting purposes G06Q;healthcare informatics G16H)
Statistically representing point-to-point photovoltaic power estimation and area-to-point conversion of satellite pixel irradiance data are described. Accuracy on correlated overhead sky clearness is bounded by evaluating a mean and standard deviation between recorded irradiance measures and the forecast irradiance measures. Sky clearness over the two locations is related with a correlation coefficient by solving an empirically-derived exponential function of the temporal distance. Each forecast clearness index is weighted by the correlation coefficient to form an output set of forecast clearness indexes and the mean and standard deviation are proportioned. Additionally, accuracy on correlated satellite imagery is bounded by converting collective irradiance into point clearness indexes. A mean and standard deviation for the point clearness indexes is evaluated. The mean is set as an area clearness index for the bounded area. For each point, a variance of the point clearness index is determined and the mean and standard deviation are proportioned.
G06F 17/18 - Complex mathematical operations for evaluating statistical data
G06N 7/00 - Computing arrangements based on specific mathematical models
G06Q 10/04 - Forecasting or optimisation specially adapted for administrative or management purposes, e.g. linear programming or "cutting stock problem"
H02J 3/38 - Arrangements for parallelly feeding a single network by two or more generators, converters or transformers
Value of solar (VOS) analysis begins with the observation that photovoltaic power production represents a unique form of energy resource that is indifferent to demand and price signals. Accurate VOS assessment requires consideration of technical and economic components. The technical analysis predicts future central power generation requirements, as reflected by estimated customer demand, using an energy balance approach. A customer demand forecasting equation with three unknown values, distributed photovoltaic power production, centralized power generation, and losses associated with the centralized power generation, is solved by applying key rational assumptions in combination with historical data of centralized power generation and distributed photovoltaic power production. The solution to the demand equation is then provided with economic data, such as avoided fuel cost, avoided plant operations and maintenance cost, avoided generation capacity cost, avoided reserve capacity cost, avoided transmission and distribution capacity cost, fuel price guarantee value, and avoided environmental cost.
42 - Scientific, technological and industrial services, research and design
Goods & Services
Providing online non-downloadable computer software for
providing individuals and businesses with a personalized
energy, economic and environmental analysis that supports
decision-making, planning and the validation of energy
related technologies; providing online non-downloadable
computer software for providing energy recommendations based
on optimized technologies, configurations, utility rates,
and financial scenarios; providing online non-downloadable
computer software that facilitates a marketplace for
energy-related technologies and connecting consumers to
contractors.
42 - Scientific, technological and industrial services, research and design
Goods & Services
(1) Providing online non-downloadable computer software for providing individuals and businesses with a personalized energy, economic and environmental analysis that supports decision-making, planning and the validation of energy related technologies; computer software for providing energy recommendations based on optimized technologies, configurations, utility rates, and financial scenarios; computer software that facilitates a marketplace for energy-related technologies and connecting consumers to contractors
42 - Scientific, technological and industrial services, research and design
Goods & Services
Providing online non-downloadable computer software for providing individuals and businesses with a personalized energy, economic and environmental analysis that supports decision-making, planning and the validation of energy related technologies; Providing online non-downloadable computer software for providing energy recommendations based on optimized technologies, configurations, utility rates, and financial scenarios; Providing online non-downloadable computer software that facilitates a marketplace for energy-related technologies and connecting consumers to contractors
87.
System and method for inferring operational specifications of a fleet of photovoltaic power generation systems with the aid of a digital computer
Operational specifications of a photovoltaic plant configuration can be inferred through evaluation of historical measured system production data and measured solar resource data. Based upon the location of the photovoltaic plant, a time-series power generation data set is simulated based on a normalized and preferably substantially linearly-scalable solar power simulation model. The simulation is run for a range of hypothetical photovoltaic system configurations. The simulation can be done probabilistically. A power rating is derived for each system configuration by comparison of the measured versus simulated production data, which is applied to scale up the simulated time-series data. The simulated energy production is statistically compared to actual historical data, and the system configuration reflecting the lowest overall error is identified as the inferred (and optimal) system configuration. Inferred configurations of photovoltaic plants in a photovoltaic fleet can be aggregated into a configuration of the fleet.
G06Q 10/04 - Forecasting or optimisation specially adapted for administrative or management purposes, e.g. linear programming or "cutting stock problem"
H02J 3/38 - Arrangements for parallelly feeding a single network by two or more generators, converters or transformers
H02S 50/10 - Testing of PV devices, e.g. of PV modules or single PV cells
H02J 3/00 - Circuit arrangements for ac mains or ac distribution networks
A computer-implemented system and method for inferring operational specifications of a photovoltaic power generation system is provided. The operational specifications of a photovoltaic plant configuration can be inferred through evaluation of historical measured system production data and measured solar resource data. Preferably, the solar resource data includes both historical and forecast irradiance values. Based upon the location of the photovoltaic plant, a time-series power generation data set is simulated based on a normalized and preferably substantially linearly-scalable solar power simulation model. The simulation is run for a range of hypothetical photovoltaic system configurations. A power rating is derived for each system configuration by comparison of the measured versus simulated production data, which is applied to scale up the simulated time-series data. The simulated energy production is statistically compared to actual historical data, and the system configuration reflecting the lowest overall error is identified as the inferred (and optimal) system configuration.
Statistically representing point-to-point photovoltaic power estimation and area-to-point conversion of satellite pixel irradiance data are described. Accuracy on correlated overhead sky clearness is bounded by evaluating a mean and standard deviation between recorded irradiance measures and the forecast irradiance measures. Sky clearness over the two locations is related with a correlation coefficient by solving an empirically-derived exponential function of the temporal distance. Each forecast clearness index is weighted by the correlation coefficient to form an output set of forecast clearness indexes and the mean and standard deviation are proportioned. Additionally, accuracy on correlated satellite imagery is bounded by converting collective irradiance into point clearness indexes. A mean and standard deviation for the point clearness indexes is evaluated. The mean is set as an area clearness index for the bounded area. For each point, a variance of the point clearness index is determined and the mean and standard deviation are proportioned.
G01W 1/02 - Instruments for indicating weather conditions by measuring two or more variables, e.g. humidity, pressure, temperature, cloud cover or wind speed
G01V 3/38 - Processing data, e.g. for analysis, for interpretation or for correction
G01B 5/14 - Measuring arrangements characterised by the use of mechanical techniques for measuring distance or clearance between spaced objects or spaced apertures
G01B 5/16 - Measuring arrangements characterised by the use of mechanical techniques for measuring distance or clearance between spaced objects or spaced apertures between a succession of regularly spaced objects or regularly spaced apertures
G06Q 10/04 - Forecasting or optimisation specially adapted for administrative or management purposes, e.g. linear programming or "cutting stock problem"
A computer-implemented system and method for bounding accuracy on a forecast of photovoltaic fleet power generation is provided. Measured irradiance observations for a plurality of locations are retrieved. The measured observations include a time series recorded at successive time periods. Forecast irradiance observations are retrieved. Error between the forecast and the measured observations is identified. A mean and standard deviation of the error is determined and combined into a fleet mean and fleet standard deviation. Sky clearness indexes are generated as a ratio of each measured observation and clear sky irradiance. A time series of the sky clearness indexes is formed. Fleet irradiance statistics are determined through statistical evaluation of the sky clearness indexes time series. A time series of power statistics is generated as a function of the fleet irradiance statistics and photovoltaic fleet power rating. A statistical confidence is associated with each power statistic in the time series.
42 - Scientific, technological and industrial services, research and design
Goods & Services
Providing online non-downloadable computer software and application programming interface for providing irradiance data and simulation services for planning, mapping, validation and management of grid-connect energy systems
42 - Scientific, technological and industrial services, research and design
Goods & Services
Providing online non-downloadable computer software and an online non-downloadable application programming interface for providing data for assessing the performance of energy systems
42 - Scientific, technological and industrial services, research and design
Goods & Services
Providing online non-downloadable software and an online non-downloadable application programming interface for providing irradiance data and simulation services for planning, mapping, validation and management of grid-connect energy systems
94.
SYSTEM FOR ESTIMATING POWER DATA FOR A PHOTOVOLTAIC POWER GENERATION FLEET
A computer-implemented system (20) and method (10) for estimating power data for a photovoltaic power generation fleet is provided. Solar irradiance data (29a-c) is assembled for locations representative of a geographic region. The data includes a time series of solar irradiance observations recorded at successive time periods spaced at fixed intervals. Each observation includes measured irradiance. The time series data is converted over each time period into clearness indexes relative to clear sky global horizontal irradiance and the clearness indexes are interpreted as irradiance statistics. Each location's irradiance statistics are combined into fleet irradiance statistics applicable over the geographic region. Fleet power statistics are built as a function of the fleet irradiance statistics and the fleet's power rating. A time series of the power statistics (26) is generated by applying a time lag correlation coefficient for an output time interval to the power statistics over each input time interval.
95.
SYSTEM FOR ESTIMATING POWER DATA FOR A PHOTOVOLTAIC POWER GENERATION FLEET
A computer-implemented system (20) and method (10) for estimating power data for a photovoltaic power generation fleet is provided. Solar irradiance data (29a-c) is assembled for locations representative of a geographic region. The data includes a time series of solar irradiance observations recorded at successive time periods spaced at fixed intervals. Each observation includes measured irradiance. The time series data is converted over each time period into clearness indexes relative to clear sky global horizontal irradiance and the clearness indexes are interpreted as irradiance statistics. Each location's irradiance statistics are combined into fleet irradiance statistics applicable over the geographic region. Fleet power statistics are built as a function of the fleet irradiance statistics and the fleet's power rating. A time series of the power statistics (26) is generated by applying a time lag correlation coefficient for an output time interval to the power statistics over each input time interval.
A computer-implemented system and method for generating a probabilistic forecast of photovoltaic fleet power generation is provided. A temporal distance between two locations is determined in proportion to cloud speed within a geographic region. Input clearness indexes are generated as a ratio of irradiance observations for one location, and clear sky irradiance. The clearness indexes are ordered into a time series. A clearness index correlation coefficient is determined as a function of temporal distance. The input clearness indexes are weighted by the clearness index correlation coefficient to form a time series of output clearness indexes. Means and standard deviations of both time series are respectively determined and combined into fleet irradiance statistics. Deterministic fleet power statistics are forecast as a function of the fleet irradiance statistics and photovoltaic fleet power rating. A time series of the forecast power statistics is generated by applying a time lag correlation coefficient.
A computer-implemented system and method for estimating photovoltaic power generation for use in photovoltaic fleet operation is provided. A set of sky clearness indexes is generated as a ratio of each irradiance observation in a set of irradiance observations that has been regularly measured for a plurality of locations, which are each within a geographic region suitable for operation of a photovoltaic fleet, and clear sky irradiance. A time series of the set of the sky clearness indexes is formed for all of the locations within the geographic region. Fleet irradiance statistics for the photovoltaic fleet are generated through statistical evaluation of the time series of the set of the sky clearness indexes. Power statistics for the photovoltaic fleet are built as a function of the fleet irradiance statistics and an overall power rating of the photovoltaic fleet.
G06F 19/00 - Digital computing or data processing equipment or methods, specially adapted for specific applications (specially adapted for specific functions G06F 17/00;data processing systems or methods specially adapted for administrative, commercial, financial, managerial, supervisory or forecasting purposes G06Q;healthcare informatics G16H)
98.
Computer-implemented system and method for correlating overhead sky clearness for use in photovoltaic fleet output estimation
A computer-implemented system and method for correlating overhead sky clearness for use in photovoltaic fleet output estimation is provided. A temporal distance that includes a physical distance between two locations, which are each within a geographic region suitable for operation of a photovoltaic fleet, is determined in proportion to cloud speed within the geographic region. A set of input sky clearness indexes is generated as a ratio of each irradiance observation in a set of irradiance observations that has been regularly measured for one of the locations within the geographic region, and clear sky irradiance. A clearness index correlation coefficient between the two locations is determined as an empirically-derived function of the temporal distance. The set of input sky clearness indexes is weighted by the clearness index correlation coefficient to form a set of output sky clearness indexes, which indicates the sky clearness for the other of the locations.
G06F 19/00 - Digital computing or data processing equipment or methods, specially adapted for specific applications (specially adapted for specific functions G06F 17/00;data processing systems or methods specially adapted for administrative, commercial, financial, managerial, supervisory or forecasting purposes G06Q;healthcare informatics G16H)
99.
Computer-implemented system and method for correlating satellite imagery for use in photovoltaic fleet output estimation
A computer-implemented system and method for correlating satellite imagery for use in photovoltaic fleet output estimation is provided. Pixels in satellite imagery data of overhead sky clearness is correlated to a bounded area within a geographic region. Each pixel represents collective irradiance that is converted into point clearness indexes for the points within the bounded area relative to clear sky irradiance. The point clearness indexes in the point clearness indexes are averaged for the points within the bounded area into an area clearness index. A variance of the area clearness index is determined in proportion to a physical area covered by each pixel. For each point, a variance of the point clearness index is determined as a ratio of the area clearness index variance and the physical area relative to the point clearness index, regional cloud speed, and a time interval relating to a time resolution of collective irradiance observation.
G06F 19/00 - Digital computing or data processing equipment or methods, specially adapted for specific applications (specially adapted for specific functions G06F 17/00;data processing systems or methods specially adapted for administrative, commercial, financial, managerial, supervisory or forecasting purposes G06Q;healthcare informatics G16H)
100.
Computer-implemented system and method for determining point-to-point correlation of sky clearness for photovoltaic power generation fleet output estimation
A computer-implemented system and method for determining point-to-point correlation of sky clearness for photovoltaic power generation fleet output estimation is provided. A physical distance between two points is obtained, each point being suitable for operation of a photovoltaic station. A temporal distance that includes the physical distance between the two points in proportion to cloud speed is determined. A correlation between sky clearness over the two points is evaluated as an empirically-derived exponential function of the temporal distance. A set of input clearness indexes for one of the points is correlated into a set of output clearness indexes indicating the sky clearness for the other of the points using a coefficient of the clearness index correlation.
G06F 19/00 - Digital computing or data processing equipment or methods, specially adapted for specific applications (specially adapted for specific functions G06F 17/00;data processing systems or methods specially adapted for administrative, commercial, financial, managerial, supervisory or forecasting purposes G06Q;healthcare informatics G16H)
