Risk-averse optimization of wind-based electricity generation with battery storage

As the global installed capacity of wind power increases, various solutions have been developed to accommodate the intermittent nature of wind. Investing in battery storage reduces power fluctuations, improves the reliability of delivering power on demand, and decreases wind curtailment. In the literature, power producers are generally modelled as risk-neutral decision makers, and the focus has been on expected profit maximization. For many privately-held small independent power producers, it is more important to capture their risk-aversion through specialized risk measurements driven by the owners’ specific risk preferences, even though the expected value-maximization objective is very desirable for large corporations with diversified investors. We consider a risk-averse, privately-held, small Independent Power Producer interested in investing in a battery storage system and jointly operating the wind farm and storage system with a trans-mission line connected to the market. We formulate the problem as a Markov decision process (MDP) to find optimal investment, generation, and operational storage decisions. Using dynamic coherent risk measures, we incorporate risk-aversion into our formulation. By choosing the risk measure as first-order mean semi-deviation, we obtain optimal threshold-based policy structure as well as optimal storage investment capacity. We perform a sensitivity analysis on optimal storage capacity with respect to the risk-aversion degree and transmission line limitations.