Method And System For Determination Of An Appropriate Strategy For Supply Of Renewal Energy Onto A Power Grid

• US 20080228553A1
• Filed: 03/12/2007
• Published: 09/18/2008
• Est. Priority Date: 03/12/2007
• Status: Abandoned Application

• Current Assignee: Airtricity Holdings Limited
• Original Assignee: Airtricity Holdings Limited
• Inventors: Hurley, Brian, Doherty, Ronan, Bryson, Alexander, Carty, Peter, Dodhia, Khilna M.
• Application Number:
  US11/685,015
• Publication Number:
  US 20080228553A1
• Time in Patent Office: Days
• US Class Current: 705/10
• CPC Class Codes: G06Q 10/06315 Needs-based resource requirements planning or analysis
• CPC Class Codes: G06Q 10/06375 Prediction of business process outcome or impact based on a proposed change
• CPC Class Codes: G06Q 30/0202 Market predictions or forecasting for commercial activities
• CPC Class Codes: G06Q 30/0206 Price or cost determination based on market factors
• CPC Class Codes: G06Q 50/06 Energy or water supply
• CPC Class Codes: H02J 3/008 involving trading of energy or energy transmission rights
• CPC Class Codes: Y04S 50/10 Energy trading, including energy flowing from end-user application to grid
• CPC Class Codes: Y04S 50/14 Marketing, i.e. market research and analysis, surveying, promotions, advertising, buyer profiling, customer management or rewards

Abstract

A system and methodology for determining optimal sales strategy for power from a wind farm to a power grid for a number of different conditions is disclosed. By defining distributions for the forecast for the output of the wind farm and combining that with a forecast for market conditions it is possible to evaluate optimum values for the volume of power that can be contributed by the wind farm for specific time periods.

Claims

1. A computer implemented method for determining an optimal firm sales volume for power provided by a renewable energy generation site into a power grid arrangement within a designated time period, the method including:

1. Providing a generation output forecast for the renewable energy generation site in the form of at least one distribution forecast,

b. Providing a market forecast in the form of at least one distribution forecast,

c. Combining each of the market and wind distribution forecasts to provide an array of possible earnings per energy output from the renewable energy generation site,

d. Determining from within the array, an appropriate proportion of energy output to sell for maximizing the earnings within that settlement period, and providing that proportion of energy output value as an output value for contribution by the renewable energy generation site into the power grid.

2. The method of claim 1 wherein the renewable energy generation site includes a plurality of geographically separated renewable energy generation sites, the method including combining generation output forecasts for each of the plurality of generation sites.

3. The method of claim 1 wherein the renewable energy generation site is a wind farm.

4. The method of claim 1 wherein the renewable energy generation site provides a stochastic output.

5. The method of claim 1 wherein the generation output forecast is provided by inputting live data from at least one geographic location into a model of output behavior for that geographic location.

6. The method of claim 5 wherein the output of the forecast may be constrained using one or more parameters related to performance of the renewable generation site prior to generating the distribution forecast.

7. The method of claim 1 wherein the market price forecast includes one or more prices.

8. The method of claim 7 wherein the one or more prices are provided as probability density functions.

9. The method of claim 8 wherein the probability density functions include a plurality of probability pairs,

10. The method of claim 9 wherein the plurality of probability pairs are utilized to provide forecasts of market prices, spill prices and penalty prices.

11. The method of claim 1 wherein the appropriate energy output is determined by maximizing a function representative of earnings achieved per nominated energy output versus earnings lost by missing that nomination.

12. A computer system configured to provide as an output an estimate of the optimal quantity of energy generated by a renewable energy generation site that should be sold firm for a plurality of intervals within a nominated time period, the system including:

a. A datastore having a plurality of data feeds;

i. A first feed coupled to a renewable energy generation site and configured to receive data pertaining to climatic conditions at that renewable energy generation site,

ii. A second feed coupled to a renewable energy generation site forecast engine, the renewable energy generation site forecast engine configured to receive from the datastore date from the first feed and provide as an output to the datastore a forecast distribution for estimated power output from the renewable energy generation site for specific intervals within a nominated time period,

iii. A third feed coupled to a market forecast engine, the market forecast engine configured to provide as an output to the datastore a forecast distribution for estimated prices within the power grid,

b. An optimization engine coupled to the data store and configured to use data from each of the first, second and third data feeds to;

i. Combine the data from the second and third feeds to provide an array of values for each interval, the array providing a relationship between power output sold from the renewable energy generation site and expected net earnings,

ii. Assess the array of value to determine an optimal value of power output for that time period for a specific set of conditions, and

iii. Output that optimal value as an output from the wind farm to the power grid for that interval.

13. The system of claim 12 wherein the renewable energy generation site is a wind farm.

14. The system of claim 12 wherein the renewable energy generation site is representative of plurality of geographically separated renewable energy generation sites.

15. A computer implemented method to optimize the firmly sold contribution of energy from a renewable generation asset to a power grid, the method including the combining each of market and wind distribution forecasts to provide an array of possible earnings per energy output from the renewable energy generation site, and determining from within the array, an appropriate proportion of energy output to sell for maximizing the earnings within that settlement period, and providing that proportion of energy output value as an output value for contribution by the renewable energy generation site into the power grid.

16. The method of claim 15 wherein the forecasts are provided in the form of a distribution forecast.

17. Method and system for controlling the contribution of renewal energy to a power grid.