Trading wind generation in short term energy markets

TLDR

Wind farm generation forecasts are highly uncertain, causing imbalance costs that threaten market stability as wind penetration and deregulated electricity systems grow. The study seeks a method to optimally set advance market contract volumes under imbalance price uncertainty. The authors develop a Markov‑based probabilistic model to compute optimal contract volumes. The model achieves significant imbalance cost savings and reveals how market closure delays and forecast horizons influence performance.

Abstract

Even with state of the art forecasting methods, the short-term generation of wind farms cannot be predicted with a high degree of accuracy. In a market situation, these forecasting errors lead to commercial risk through imbalance costs when advance contracting. This situation is one that needs to be addressed due to the steady increase in the amount of grid connected wind generation, combined with the rise of deregulated, market orientated electricity systems. In the presence of imbalance prices and uncertain generation, a method is required to determine the optimum level of contract energy to be sold on the advance markets. Such a method is presented here using Markov probabilities for a wind farm and demonstrates substantial reductions in the imbalance costs. The effect of market closure delays and forecasting window lengths are also shown.