Wind Turbine Power Forecast Control for Grid Frequency Support
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Solution Overview
Problem
Inaccurate power production forecasts by wind farms lead to grid frequency imbalances, resulting in power production loss, reduced profits, and penalty payments, despite existing forecasting and control strategies.
Innovation Solution
A method that determines power production capacity based on actual grid frequency and a frequency support power reserve, adjusting forecasts to ensure stable grid frequency and avoid penalties, using fuzzy logic algorithms for responsiveness.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If wind farms operate at theoretical maximum output level based on power production forecasts, then power production and profits are improved, but grid frequency instability and penalty payments increase due to forecast inaccuracies
Solution Approach 1:
The power production capacity is dynamically adjusted based on real-time grid frequency measurements and forecasted frequency support power reserves. The system continuously adapts the operational capacity of wind turbines to match both the power production forecast and the actual grid frequency conditions, transforming a static maximum output approach into a dynamic responsive system that resolves the contradiction between maximizing production and maintaining grid stability
Solution Approach 2:
The system implements a feedback mechanism by continuously monitoring actual grid frequency and comparing it with nominal frequency. Based on this feedback and the determined frequency support power reserve, the power production capacity is adjusted to ensure both accurate power delivery and grid frequency stability, eliminating the need to choose between maximum production and grid reliability
2Measurement precision
If power production forecast accuracy is improved, then power delivery reliability is improved, but device complexity and control system requirements increase
Solution Approach 1:
The power plant controller performs multiple functions: it receives and processes power production forecasts, monitors actual grid frequency in real-time, determines frequency support power reserves, and adjusts power production capacity accordingly. By consolidating these diverse functions into a single multi-functional control system, the patent improves forecast accuracy and power delivery reliability without proportionally increasing overall system complexity
Solution Approach 2:
The system changes operational parameters dynamically by adjusting power production capacity based on varying grid frequency conditions and forecast data. Rather than requiring complex hardware, the solution relies on parameter adjustments (power output levels) controlled through software algorithms that process forecast accuracy data and frequency measurements
Data Source
AI summary
A method is provided for determining a power production capacity of at least one wind turbine connected to a power grid. The method includes receiving, e.g. from a power grid control center, a power production forecast for the at least one wind turbine, and then monitoring an actual grid frequency of the power grid. Based on the actual grid frequency and a nominal grid frequency, a frequency support power reserve is determined. The power production capacity is then determined in dependence of the determined frequency support power reserve and the power production forecast.