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In this paper, we study the strategic investment problem of battery energystorage systems (BESSs) in the wholesale electricity market from theperspective of BESSs owners. Large-scale BESSs planning without considering thepossible wholesale market price change may result in possible locationalmarginal price (LMP) changes. To overcome such limits, we propose a three-phaseapproach for the BESS investment problem. In Phase-1, we conduct a search forthe optimal BESS configurations via a congestion-based heuristics and Bayesianoptimization. In Phases 2 and 3, we alternatively dispatch optimization tasksto optimize the wholesale market clearing for LMPs and identify the optimalschedule for BESSs operations. We validate the model using a ten-yearsimulation on the Electric Reliability Council of Texas (ERCOT) market.Experimental results show that the Bayesian optimization model runs 16 timesfaster than the grid search model in achieving the same solution quality.Further, the iterative method demonstrates that the model without consideringpossible LMP changes makes a 21% profit overestimation.

Strategic Investments of Large Scale Battery Energy Storage Systems in the Wholesale Electricity Market