Optimal intra-day operations of behind-the-meter battery storage for primary frequency regulation provision: A hybrid lookahead method

Abstract

Battery energy storage systems (BESSs) are being widely installed behind-the-meter to reduce electricity bill. By providing grid ancillary services, behind-the-meter BESSs can increase potential revenue streams. This study targets the simultaneous electricity bill reduction and primary frequency regulation (PFR) provision. With the expansion of the application spectrum, the intra-day operations become more and more complicated. In this paper, a hybrid lookahead method with value function approximation strategy is proposed for intra-day operations, wherein the concept of “offline calculation—online application” is devised and implemented. The approximate value function is trained offline to represent the expected long-term benefit. A two-stage robust approximate dynamic programming (ADP) model is formulated for one day operation which is optimized to adjust the power baseline with a forward rolling horizon. Furthermore, multi-dimensional indicators are introduced to evaluate the proposed strategy. Simulations and benchmarking comparisons are performed for a 0.5 MW/1.0 MWh BESS to verify the superior performance of the proposed strategy. The results show that the approximate value function can be obtained offline with 99.07% convergence precision. Moreover, the proposed strategy can ensure the economic benefit and PFR provision within a short online computing time. The resulting intra-day economic benefit can reach 95.55% of the theoretical optimum, and the online optimization consumes only 4.65s for a prediction horizon of 5 min, which ensures the feasibility of real-time predictive optimization.