Abstract

We consider a wind power producer (WPP) participating in a dynamically evolving two settlement power market. We study the utility of energy storage for a WPP in maximizing its expected profit. With random wind and price processes, the optimal forward contract and storage charging/discharging decisions are formulated as solutions of an infinite horizon stochastic optimal control problem. For the asymptotically small storage capacity regime, we precisely characterize the maximum profit increase brought by utilizing energy storage. We prove that, in this regime, an optimal policy uses storage to compensate for power delivery shortfall/surplus in real time, without changing the forward contracts from the optimal ones in the absence of energy storage. This policy also serves as an approximately optimal policy for the case of relatively small storage capacity. We also design a policy based on model predictive control (MPC) that is approximately optimal for general storage capacities. We numerically evaluate the developed policies for wind and price processes with representative statistics from real world data. It is observed that, as expected, the simple small storage approximation policy performs closely to the optimum when storage is relatively small, while the more complex stochastic MPC policy performs better for larger storage capacities.

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