Offshore wind farm layout optimization accounting for participation in secondary reserve markets

Abstract

Wind farm layout optimization usually aims at maximizing annual energy production by placing wind turbines in a strategic way to avoid wake losses. However, this might not lead to optimal profits because of the volatility of electricity prices. Moreover, with the growing unpredictability and variability of future power systems due to the increase in renewable electricity production, wind farm operators will have a more important role in balancing the system through participation in reserve markets. This study presents a new formulation for wind farm layout optimization where the objective function aims at maximizing revenues from both day-ahead and reserve markets. It uses stochastic gradient descent for the optimization and probabilistic forecasts for wind power and electricity prices. The new formulation is applied to a test case based on a real-life offshore wind farm in Belgium. An important conclusion is that annual revenues are expected to increase in a significant way when accounting for participation in reserve markets, while exhibiting a lower supplied energy production. Moreover, layouts optimized for revenue maximization with reserve participation tend to show better yearly revenues than when considering the day-ahead market only in the objective function. Expected revenues are also higher by 0.18 % on average for the new methodology than when using the maximization of annual energy production, widely used in the literature, as the objective function.