SYSTEMS AND METHODS FOR FORECASTING SOLAR POWER

• US 20110282514A1
• Filed: 05/09/2011
• Published: 11/17/2011
• Est. Priority Date: 05/07/2010
• Status: Abandoned Application

• Current Assignee: Advanced Energy Industries Incorporated
• Original Assignee: Advanced Energy Industries Incorporated
• Inventors: Ropp, Michael, Hummel, Steven G.
• Application Number:
  US13/103,629
• Publication Number:
  US 20110282514A1
• Time in Patent Office: Days
• US Class Current: 700/297
• CPC Class Codes: F24S 2201/00 Prediction; Simulation
• CPC Class Codes: G01W 1/10 Devices for predicting weather conditions computers per se G06; display devices G09
• CPC Class Codes: H02J 2300/22 The renewable source being solar energy
• CPC Class Codes: H02J 2300/24 of photovoltaic origin
• CPC Class Codes: H02J 2310/54 according to a pre-established time schedule
• CPC Class Codes: H02J 2310/60 Limiting power consumption in the network or in one section of the network, e.g. load shedding or peak shaving
• CPC Class Codes: H02J 3/004 Generation forecast, e.g. methods or systems for forecasting future energy generation
• CPC Class Codes: H02J 3/144 Demand-response operation of the power transmission or distribution network
• CPC Class Codes: H02J 3/381 Dispersed generators
• CPC Class Codes: H02J 7/35 with light sensitive cells
• CPC Class Codes: H02M 3/156 with automatic control of output voltage or current, e.g. switching regulators
• CPC Class Codes: H02S 40/32 comprising DC/AC inverter means associated with the PV module itself, e.g. AC modules
• CPC Class Codes: Y02B 70/3225 Demand response systems, e.g. load shedding, peak shaving
• CPC Class Codes: Y02E 10/56 Power conversion systems, e.g. maximum power point trackers
• CPC Class Codes: Y04S 20/222 Demand response systems, e.g. load shedding, peak shaving

Abstract

A solar power forecasting system can provide forecasts of solar power output by photovoltaic plants over multiple time frames. A first time frame may be several hours from the time of the forecast, which can allow utility personnel sufficient time to make decisions to counteract a forecasted shortfall in solar power output. For example, the utility personnel can decide to increase power production and/or to purchase additional power to make up for any forecasted shortfall in solar power output. A second time frame can be several minutes from the time of the forecast, which can allow for operations to mitigate effects of a forecasted shortfall in solar power output. Such mitigation operations can include directing an energy management system to shed noncritical loads and/or ramping down the power produced by the photovoltaic plants at a rate that is acceptable to the utility to which the photovoltaic plants provide power.

Claims

1. A method of forecasting power output of a photovoltaic plant having a photovoltaic array, the method comprising:

receiving meteorological data that include, for each of multiple future times, a prediction of global horizontal irradiance for each of multiple locations, wherein—

the photovoltaic plant has a location corresponding to one of the multiple locations, and

the prediction of global horizontal irradiance is based upon satellite data;

determining, from the meteorological data, the predicted global horizontal irradiance for the location of the photovoltaic plant at a future time;

accessing array data for the photovoltaic array of the photovoltaic plant, wherein the array data includes at least one of a tilt of the photovoltaic array and an azimuth of the photovoltaic array;

calculating a predicted plane of array irradiance for the photovoltaic array at the future time based upon the predicted global horizontal irradiance and the array data; and

forecasting, by a computing system having a processor and a memory, a power output of the photovoltaic plant at the future time based on the predicted plane of array irradiance.

2. The method of claim 1 wherein the meteorological data further include, for each of one or more points of time in the future, an estimated ambient temperature for each of the multiple locations, wherein the array data further includes nominal operating cell temperature data of the photovoltaic array, and wherein the method further comprises:

determining, from the meteorological data, the estimated ambient temperature for the photovoltaic plant;

calculating an estimated operating temperature of the photovoltaic array based upon the estimated ambient temperature for the photovoltaic plant and the nominal operating cell temperature data; and

forecasting power output of the photovoltaic plant at the future time based on the predicted plane of array irradiance and the estimated operating temperature.

3. The method of claim 2 wherein the array data further includes structure data indicating a structure of the photovoltaic array, and wherein the method further comprises calculating an estimated operating temperature of the photovoltaic array based upon the estimated ambient temperature for the photovoltaic plant, the nominal operating cell temperature data, and the structure data.

4. The method of claim 1 wherein the array data further includes efficiency data indicating an overall efficiency of the photovoltaic array, and wherein the method further comprises forecasting power output of the photovoltaic plant at the future time based on the predicted plane of array irradiance, the estimated operating temperature, and the efficiency data.

5. The method of claim 1, further comprising:

accessing environment data for the photovoltaic plant, wherein the environment data includes horizon profile data; and

calculating a predicted plane of array irradiance based upon the predicted global horizontal irradiance, the array data, and the horizon profile data.

6. The method of claim 5, wherein the environment data further includes ground albedo data, and wherein the method further comprises calculating a predicted plane of array irradiance based upon the predicted global horizontal irradiance, the array data, the horizon profile data, and the ground albedo data.

7. The method of claim 5, wherein horizon profile data is based upon satellite data, and wherein the method further comprises:

determining that a horizon obstacle shades at least a portion of the photovoltaic array at the future time; and

calculating a predicted plane of array irradiance at the future time based upon the predicted global horizontal irradiance, the array data, and the determination that the horizon obstacle shades at least a portion of the photovoltaic array at the future time.

8. The method of claim 1, further comprising:

determining a solar azimuth of the sun at the future time; and

calculating a predicted plane of array irradiance based upon the predicted global horizontal irradiance, the array data, and the solar azimuth.

9. The method of claim 1, further comprising transmitting the power output of the photovoltaic plant at the future time to a utility control system.

10. The method of claim 1 wherein receiving meteorological data includes receiving first meteorological data at a first time, and wherein the method further comprises:

receiving second meteorological data at a second time that include, for each of multiple future times, a prediction of global horizontal irradiance for each of the multiple locations, wherein the prediction of global horizontal irradiance is based upon satellite data;

determining, from the second meteorological data, the predicted global horizontal irradiance for the location of the photovoltaic plant at a future time; and

calculating a predicted plane of array irradiance for the photovoltaic array at the future time based upon the predicted global horizontal irradiance and the array data; and

forecasting a power output of the photovoltaic plant at the future time based on the predicted plane of array irradiance.

11. The method of claim 1, further comprising:

accessing data indicating actual solar power output of the photovoltaic plant at the future time;

determining if the actual solar power output is less than the forecasted power output of the photovoltaic plant at the future time by a predetermined amount; and

providing an indication that the actual solar power output is less than the forecasted power output.

12. The method of claim 1 wherein the photovoltaic array includes multiple solar cells including material that absorb light of a range of wavelengths, and wherein the method further comprises forecasting a power output of the photovoltaic plant at the future time based on the predicted plane of array irradiance and the range of light wavelengths absorbed by the solar cell material.

13. A computing system for forecasting solar power output of a photovoltaic plant having a photovoltaic array, the computing system comprising:

a processor; and

a memory containing;

a predicted global horizontal irradiance for the photovoltaic plant at a future time, the predicted global horizontal irradiance based upon satellite data;

tilt data indicating a tilt of the photovoltaic array;

azimuth data indicating an azimuth of the photovoltaic array; and

a facility programmed to forecast solar power output of the photovoltaic plant at the future time, wherein the facility utilizes the predicted global horizontal irradiance, the tilt data, and the azimuth data to forecast solar power output of the photovoltaic plant at the future time.

14. The computing system of claim 13 wherein the memory further contains estimated ambient temperature for the photovoltaic plant, and wherein the facility also utilizes the estimated ambient temperature to forecast solar power output of the photovoltaic plant at the future time.

15. The computing system of claim 13 wherein the memory further contains horizon profile data for the photovoltaic plant, and wherein the facility also utilizes the horizon profile data to forecast solar power output of the photovoltaic plant at the future time.

16. The computing system of claim 13 wherein the memory further contains albedo data for the photovoltaic plant, and wherein the facility also utilizes the albedo data to forecast solar power output of the photovoltaic plant at the future time.

17. The computing system of claim 13 wherein the memory further contains solar azimuth data, and wherein the facility also utilizes the solar azimuth data to forecast solar power output of the photovoltaic plant at the future time.

18. The computing system of claim 13, further comprising a data input/output component, and wherein the facility is further programmed to transmit the forecasted solar power output of the photovoltaic plant at the future time to a utility control system via the data input/output component.

19. A computer-readable storage medium whose contents cause a computing system to perform a method of forecasting power output of a photovoltaic plant having a photovoltaic array, the method comprising:

utilizing

     1) a prediction of global horizontal irradiance at the photovoltaic plant at a future time, wherein the prediction of global horizontal irradiance is based upon satellite data,

     2) tilt data indicating a tilt of the photovoltaic array, and

     3) azimuth data indicating an azimuth of the photovoltaic array to forecast power output of the photovoltaic plant at the future time; and

storing an indication of the forecasted power output of the photovoltaic plant at the future time.

20. The computer-readable storage medium of claim 19 wherein the method further comprises utilizing 4) an estimated ambient temperature for the photovoltaic plant to forecast power output of the photovoltaic plant at the future time.

21. The computer-readable storage medium of claim 19 wherein the method further comprises utilizing 4) horizon profile data to forecast power output of the photovoltaic plant at the future time.

22. The computer-readable storage medium of claim 19 wherein the method further comprises utilizing 4) albedo data to forecast power output of the photovoltaic plant at the future time.

23. The computer-readable storage medium of claim 19 wherein the method further comprises utilizing 4) solar azimuth data to forecast power output of the photovoltaic plant at the future time.

24. The computer-readable storage medium of claim 19 wherein the computing system is a first computing system and wherein the method further comprises transmitting the indication of the forecasted power output of the photovoltaic plant at the future time to a second computing system.

25. The computer-readable storage medium of claim 19 wherein the prediction of global horizontal irradiance at the photovoltaic plant at a future time is a first prediction of global horizontal irradiance at the photovoltaic plant at a first future time, wherein the satellite data is first satellite data, the indication is a first indication, and wherein the method further comprises:

receiving a second prediction of global horizontal irradiance at the photovoltaic plant at a second future time, wherein the second prediction of global horizontal irradiance is based upon second satellite data;

utilizing

     1) the second prediction of global horizontal irradiance at the photovoltaic plant at the second future time,

     2) the tilt data, and

     3) the azimuth data to forecast power output of the photovoltaic plant at the second future time; and

storing a second indication of the forecasted power output of the photovoltaic plant at the second future time.

26. A tangible computer memory encoding a data structure, the data structure comprising:

first information specifying a forecasted global horizontal irradiance at a first location at a first time, the forecasted global horizontal irradiance derived from satellite data;

second information specifying a photovoltaic plant having a photovoltaic array at the first location; and

third information specifying an orientation of the photovoltaic array,

such that the data structure may be used by a computing system at a second time prior to the first time to calculate a prediction of solar power output of the photovoltaic plant at the first time.

27. A method of forecasting power output of a photovoltaic plant, the method comprising:

receiving cloud forecast data containing information about one or more clouds affecting a predetermined area, the predetermined area including a photovoltaic plant having a photovoltaic array;

utilizing the cloud forecast data to predict an effect of a cloud upon plane of array irradiance at the photovoltaic array of the photovoltaic plant; and

utilizing, by a computing system having a processor and memory, the predicted effect upon the plane of array irradiance to predict a power transient of the photovoltaic plant.

28. The method of claim 27 wherein receiving cloud forecast data includes receiving cloud forecast data containing information about cloud location, cloud transmissivity, cloud shape, and cloud velocity of the one or more clouds.

29. The method of claim 27 wherein receiving cloud forecast data includes:

receiving first cloud forecast data at a first time;

receiving second cloud forecast data at a second time; and

based upon the first and second cloud forecast data, determining that a cloud is likely to cover at least a portion of the photovoltaic array.

30. The method of claim 27 wherein the photovoltaic array is coupled to a load having an energy management system, and wherein the method further comprises:

based upon the predicted solar power transient, calculating a load shedding profile; and

providing the load shedding profile to the energy management system,

such that the energy management system may utilize the load shedding profile to reduce power required by the load.

31. The method of claim 27 wherein the photovoltaic array is coupled to a solar power inverter that generates power, and wherein the method further comprises:

calculating an expected depth of the power transient;

determining a time at which to start ramping down the power generated by the solar power inverter; and

at the determined start time, beginning ramping down the power generated by the solar power inverter.

32. The method of claim 31 wherein the solar power inverter implements a maximum power point tracking algorithm that affects how much power is generated by the solar power inverter, and wherein the method further comprises:

at the determined start time, adjusting the maximum power point tracking algorithm to begin ramping down the power generated by the solar power inverter.

33. A computing system for predicting a decrease in solar power output of a photovoltaic plant having a photovoltaic array and sited at a location, the computing system comprising:

a processor; and

a memory containing;

cloud forecast data containing information about one or more clouds proximate to the location;

plane of array irradiance data containing information about a predictive plane of array irradiance at the photovoltaic array at a future time; and

a facility programmed to—

utilize the cloud forecast data to predict an effect of a cloud upon plane of array irradiance at the photovoltaic array at the future time; and

utilize the predicted effect upon the plane of array irradiance to predict a power transient of the photovoltaic plant at the future time.

34. The computing system of 33, further comprising a data input component configured to periodically receive cloud forecast data and plane of array irradiance data.

35. A solar power inverter comprising:

a direct current (DC) input component configured to receive DC produced by one or more photovoltaic modules;

a power generation component configured to generate alternating current (AC) from the DC;

an AC output component configured to output generated AC;

a data input component configured to receive signals indicating solar power forecast data; and

a controller configured to—

implement a maximum power point tracking algorithm for the one or more photovoltaic modules; and

adjust the maximum power point tracking algorithm based on the solar power forecast data.

36. The solar power inverter of claim 35 wherein the controller is further configured to adjust the maximum power point tracking algorithm by decreasing a frequency with which an operating voltage of the photovoltaic modules is changed.

37. A method of controlling power produced by one or more photovoltaic modules, the method comprising:

receiving a prediction of future power output by a photovoltaic plant, wherein the photovoltaic plant includes one or more photovoltaic modules that produce direct current (DC) and a solar power inverter that generates alternating current (AC) from the DC, and wherein the solar power inverter implements a maximum power point tracking algorithm for the one or more photovoltaic modules; and

based on the prediction of future power output, controlling the maximum power point tracking algorithm.

38. The method of claim 37 wherein controlling the maximum power point tracking algorithm includes modifying a frequency with which the solar power inverter adjusts an operating parameter for the one or more photovoltaic modules.

39. The method of claim 37 wherein controlling the maximum power point tracking algorithm includes modifying an operating parameter for the one or more photovoltaic modules.

40. A method of controlling an energy storage device, the method comprising:

accessing a prediction of future solar power output by a photovoltaic plant, wherein the photovoltaic plant includes—

a photovoltaic array that generates direct current (DC);

a solar power inverter that converts DC from the photovoltaic array to alternating current (AC) usable by a utility grid;

an energy storage device that stores energy; and

an controller that controls transfer of energy to and from the energy storage device;

controlling, by the controller, transfer of energy to or from the energy storage device based upon the prediction of future solar power output.

41. The method of claim 40 wherein the energy storage device includes a battery and wherein controlling transfer of energy to or from the energy storage device includes charging the battery at a rate based upon the prediction of future solar power output.

42. The method of claim 40, further comprising transferring energy from the energy storage device for provision to the utility grid based upon a predicted decrease in future solar power output.

43. The method of claim 42, further comprising providing energy to the utility grid according to a predetermined profile.

44. The method of claim 40, further comprising transferring energy to the energy storage device based upon a predicted increase in future solar power output.