Wind Park Power Forecast Correction for Black Start Planning
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Solution Overview
Problem
Wind parks face challenges in accurately forecasting wind speeds and power generation due to geographical heterogeneity and the unpredictability of wind, making it difficult to plan power feed-in, especially for network restoration and black start operations.
Innovation Solution
A method to determine the expected power and accuracy of wind power feed-in by using a combination of weather forecasts, local weather data, and operating data to correct wind speed predictions, with a focus on short-term predictions to improve planning capabilities for network restoration and black start operations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If general weather forecasts are used for wind park power prediction, then forecast availability is improved, but prediction accuracy deteriorates due to large geographical area coverage
Solution Approach 1:
The patent divides the wind park into multiple zones and creates local weather forecasts for each zone rather than using a single general forecast for the entire park. This allows the prediction system to account for geographical heterogeneity in wind conditions across different locations within the wind park, improving overall prediction accuracy while maintaining forecast availability.
Solution Approach 2:
The wind park is segmented into multiple zones based on geographical characteristics and wind patterns. Each zone receives its own localized weather forecast, allowing the system to capture spatial variations in wind conditions that would be averaged out in a single general forecast, thereby resolving the contradiction between forecast availability and prediction accuracy.
2Measurement precision
If local weather forecasts are produced for specific wind park regions, then wind speed prediction accuracy is improved, but forecast reliability deteriorates due to low degree of accuracy
Solution Approach 1:
The patent combines multiple local zone forecasts into an aggregated wind park-level prediction. By merging the forecasts from multiple zones and weighting them according to the capacity and wind conditions of each zone, the system achieves both local accuracy benefits and overall forecast reliability, resolving the contradiction between local precision and global reliability.
Solution Approach 2:
The system uses actual measured wind speeds and power generation data from the wind park to validate and adjust the local weather forecasts. This feedback mechanism improves forecast reliability by continuously calibrating the local predictions against real-world observations, ensuring that the high-resolution local forecasts remain reliable over time.
3Reliability
If wind park power prediction is improved for network restoration, then network restoration capability is improved, but planning complexity increases due to multiple variables
Solution Approach 1:
The system performs preliminary power predictions and identifies available wind power resources in advance of network restoration events. By pre-calculating potential power contributions from different zones and storing this information, the system reduces the complexity of real-time decision-making during actual restoration operations, allowing planners to quickly assess available resources without complex calculations during the critical restoration window.
Data Source
AI summary
A method for feeding electric power into an electric supply network using a wind park having wind power installations is provided. An expected power is determined for a predetermined feed-in period, where the expected power indicates a power value or temporal profile of power expected to be available to the park as power from wind in the predetermined feed-in period. An expected accuracy is determined and is a measure of how accurately the power reaches the expected power in the feed-in period. To determine the expected power, at least one expected wind variable representative of the expected wind speed is determined using a weather forecast, and the expected wind variable is additionally determined or verified, proceeding from the weather forecast, using a correction rule based on local weather data and/or operating data of the park. The expected power is determined on the basis of the expected wind variable.