Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.