Smarter-Grid: Method to Forecast Electric Energy Production and Utilization Subject to Uncertain Environmental Variables
First Claim
1. A method of establishing a power forecasting service model for use in conjunction with a system, said method comprising estimating energy production, forecasting utilization of said energy and storing said energy, for use in a system by maintaining a balance between a plurality of sources of energy and a plurality of users sinks thereof, said method utilizing:
- at least a first renewable source of said energy sources having an energy output which fluctuates due to environmental energy generation factors, at least a second non-renewable source of said energy sources having an energy output which is accurately controllable through correspondingly accurate control of fuel consumption,at least a first environmentally dependent sink of said energy sinks which is subject to an energy consumption factor which fluctuates due to environmental energy consumption factors, andat least a second directly controllable sink of said energy sinks which is subject to an energy consumption factor which is accurately controllable through correspondingly accurate regulation of controllable energy consumption factors,said method further comprising;
a) taking measurements to obtain a first renewable energy source forecast for each said environmental energy generation factor based on said measurements taken thereof;
b) based on said first renewable energy source forecast, estimating an energy output for said first renewable energy source at a selected point in time;
c) obtaining a sink forecast for each said environmental energy consumption factor based on measurements thereof;
d) based on said sink forecast, estimating an energy consumption value for said first sink at said selected point in time;
e) regulating said fuel consumption by said second non-renewable source of energy, and regulating said energy consumption by said second sink in order to maintain said balance between said plurality of sources of energy and said plurality of usersinks thereof.
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Accused Products
Abstract
A method to forecast the energy sources and energy sinks to facilitate continuous capacity planning, regulation and control of energy state of an entity under variable weather condition is established. Energy sources of specific focus are related to renewable energy forms from wind, solar and wave that are highly dependent on prevailing weather conditions.
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Citations
25 Claims
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1. A method of establishing a power forecasting service model for use in conjunction with a system, said method comprising estimating energy production, forecasting utilization of said energy and storing said energy, for use in a system by maintaining a balance between a plurality of sources of energy and a plurality of users sinks thereof, said method utilizing:
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at least a first renewable source of said energy sources having an energy output which fluctuates due to environmental energy generation factors, at least a second non-renewable source of said energy sources having an energy output which is accurately controllable through correspondingly accurate control of fuel consumption, at least a first environmentally dependent sink of said energy sinks which is subject to an energy consumption factor which fluctuates due to environmental energy consumption factors, and at least a second directly controllable sink of said energy sinks which is subject to an energy consumption factor which is accurately controllable through correspondingly accurate regulation of controllable energy consumption factors, said method further comprising; a) taking measurements to obtain a first renewable energy source forecast for each said environmental energy generation factor based on said measurements taken thereof; b) based on said first renewable energy source forecast, estimating an energy output for said first renewable energy source at a selected point in time; c) obtaining a sink forecast for each said environmental energy consumption factor based on measurements thereof; d) based on said sink forecast, estimating an energy consumption value for said first sink at said selected point in time; e) regulating said fuel consumption by said second non-renewable source of energy, and regulating said energy consumption by said second sink in order to maintain said balance between said plurality of sources of energy and said plurality of usersinks thereof. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11)
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12. (canceled)
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13. A method to forecast the power and energy state of an electric system comprising:
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estimating an electric power production renewable energy source, said energy source selected from the group consisting of solar, wind and wave energy, said estimate being based upon technology-dependent parameters and weather-driven variables, said parameters and said variables derived from distributed power sensors, satellite-based cloud cover images, ground-based wind velocity data and ocean-based wave height/period data respectively; forecasting national power utilization sink levels wherein the impact of weather including temperature, humidity and wind on consumption by a system is correlated to establish a model from historical data and applied for enhanced accuracy of consumption projection; estimating stored energy available for time delayed consumption; integrating said production, utilization and storage, to establish a power-forecasting service model to provide an “
energy map”
displaying the power generation or consumption forecast to detailed databases of an “
energy-state”
of a geographic entity. - View Dependent Claims (14, 15, 16, 17, 18, 19)
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20. A method of forecasting the supply and demand condition of an electric grid using renewable and non-renewable sources of electric power comprising:
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forecasting total electrical power capacity which is the sum of renewable and non-renewable energy sources; forecasting the total renewable source of electric power using a sensor network to; obtain cloud cover data according to the relationship;
Psolar(t)=f(C(x,y,t+Δ
t),θ
hat)obtain wind streamline data according to the relationship;
Pwind(t)=f(V(x,y,t+Δ
t),θ
Wave hat)obtain wave data according to the relationship;
Pwave(t)=f(W(x,y,t+Δ
t),θ
Wave hat)wherein (x,y) in each instance above is location, t is time dependent and θ
Wave hat is an estimate of a selected group of parameters from each power source, not yet known, which are estimated using sensor data and equations governing basic physics of power conversion;determining the non-renewable source of electric power by; obtaining known non-renewable energy power capacity; combining said data obtained from said renewable sources with said known non-renewable energy user capacity to result in information that comprises a total forecast capacity; said combined data is composed into an electric state vector X which defines location (x,y) and is time (t) dependent and incorporates transmission line voltage (V), current (I), power (P), energy (E) parameters therein; using the parameters in said X state, estimating stored energy from resources that are used in forming direct and indirect estimates, that are based upon historic trend data from home consumption data and from industry data; combining said estimates obtained from said X state to result in information that comprises a total forecast demand; evaluating forecast capacity and forecast demand, in a planning and control stage, and then balancing supply and demand limitations within an electric system. - View Dependent Claims (21)
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22. An article of manufacture comprising a computer usable medium having computer readable program code means embodied therein for causing a forecasting of electrical energy production and utilization subject to uncertain environmental variables, the computer readable program code means in said article of manufacture comprising computer readable program code means for causing a computer to effect:
- estimating an electric power production renewable energy source, said energy source selected from the group consisting of solar, wind and wave energy, said estimate being based upon technology-dependent parameters and weather-driven variables, said parameters and said variables derived from distributed power sensors, satellite-based cloud cover images, ground-based wind velocity data and ocean-based wave height/period data respectively;
forecasting national power utilization sink levels wherein the impact of weather including temperature, humidity and wind on consumption by a system is correlated to establish a model from historical data and applied for enhanced accuracy of consumption projection; estimating stored energy available for time delayed consumption; integrating said production, utilization and storage, to establish a power-forecasting service model to provide an “
energy map”
displaying the power generation or consumption forecast to detailed databases of an “
energy-state”
of a geographic entity.
- estimating an electric power production renewable energy source, said energy source selected from the group consisting of solar, wind and wave energy, said estimate being based upon technology-dependent parameters and weather-driven variables, said parameters and said variables derived from distributed power sensors, satellite-based cloud cover images, ground-based wind velocity data and ocean-based wave height/period data respectively;
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23. An article of manufacture comprising a computer usable medium having computer readable program code means embodied therein for causing a forecasting of electrical energy production and utilization subject to uncertain environmental variables, the computer readable program code means in said article of manufacture comprising computer readable program code means for causing a computer to effect:
- forecasting total electrical power capacity which is the sum of renewable and non-renewable energy sources;
forecasting the total renewable source of electric power using a sensor network to; obtain cloud cover data according to the relationship;
Psolar(t)=f(C(x,y,t+Δ
t),θ
Solar hat)obtain wind streamline data according to the relationship;
Pwind(t)=f(V(x,y,t+Δ
t),θ
Wind hat)obtain wave data according to the relationship;
Pwave(t)=f(W(x,y,t+Δ
t),θ
Wave hat)wherein (x,y) in each instance above is location, t is time dependent and θ
Wave hat is an estimate of a selected group of parameters from each power source, not yet known, which are estimated using sensor data and equations governing basic physics of power conversion;determining the non-renewable source of electric power by; obtaining known non-renewable energy power capacity; combining said data obtained from said renewable sources with said known non-renewable energy user capacity to result in information that comprises a total forecast capacity; said combined data is composed into an electric state vector X which defines location (x,y) and is time (t) dependent and incorporates transmission line voltage (V), current (I), power (P), energy (E) parameters therein; using the parameters in said X state, estimating stored energy from resources that are used in forming direct and indirect estimates, that are based upon historic trend data from home consumption data and from industry data; combining said estimates obtained from said X state to result in information that comprises a total forecast demand; evaluating forecast capacity and forecast demand, in a planning and control stage, and then balancing supply and demand limitations within an electric system.
- forecasting total electrical power capacity which is the sum of renewable and non-renewable energy sources;
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24. A computer program product comprising a computer usable medium having computer readable program code means embodied therein for causing a forecasting of electrical energy production and utilization subject to uncertain environmental variables, the computer readable program code means in said computer program product comprising computer readable program code means for causing a computer to effect:
- estimating an electric power production renewable energy source, said energy source selected from the group consisting of solar, wind and wave energy, said estimate being based upon technology-dependent parameters and weather-driven variables, said parameters and said variables derived from distributed power sensors, satellite-based cloud cover images, ground-based wind velocity data and ocean-based wave height/period data respectively;
forecasting national power utilization sink levels wherein the impact of weather including temperature, humidity and wind on consumption by a system is correlated to establish a model from historical data and applied for enhanced accuracy of consumption projection; estimating stored energy available for time delayed consumption; integrating said production, utilization and storage, to establish a power-forecasting service model to provide an “
energy map”
displaying the power generation or consumption forecast to detailed databases of an “
energy-state”
of a geographic entity.
- estimating an electric power production renewable energy source, said energy source selected from the group consisting of solar, wind and wave energy, said estimate being based upon technology-dependent parameters and weather-driven variables, said parameters and said variables derived from distributed power sensors, satellite-based cloud cover images, ground-based wind velocity data and ocean-based wave height/period data respectively;
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25. A computer program product comprising a computer usable medium having computer readable program code means embodied therein for causing a forecasting electrical energy production and utilization subject to uncertain environmental variables, said computer readable program code means in said computer program product comprising computer readable program code means for causing a computer to effect:
- forecasting total electrical power capacity which is the sum of renewable and non-renewable energy sources;
forecasting the total renewable source of electric power using a sensor network to; obtain cloud cover data according to the relationship;
Psolar(t)=f(C(x,y,t+Δ
t),θ
Solar hat)obtain wind streamline data according to the relationship;
Pwind(t)=f(V(x,y,t+Δ
t),θ
Wind hat)obtain wave data according to the relationship;
Pwave(t)=f(W(x,y,t+Δ
t),θ
Wave hat)wherein (x,y) in each instance above is location, t is time dependent and θ
Wave hat is an estimate of a selected group of parameters from each power source, not yet known, which are estimated using sensor data and equations governing basic physics of power conversion;determining the non-renewable source of electric power by; obtaining known non-renewable energy power capacity; combining said data obtained from said renewable sources with said known non-renewable energy user capacity to result in information that comprises a total forecast capacity; said combined data is composed into an electric state vector X which defines location (x,y) and is time (t) dependent and incorporates transmission line voltage (V), current (I), power (P), energy (E) parameters therein; using the parameters in said X state, estimating stored energy from resources that are used in forming direct and indirect estimates, that are based upon historic trend data from home consumption data and from industry data; combining said estimates obtained from said X state to result in information that comprises a total forecast demand; evaluating forecast capacity and forecast demand, in a planning and control stage, and then balancing supply and demand limitations within an electric system.
- forecasting total electrical power capacity which is the sum of renewable and non-renewable energy sources;
Specification