Optimal bid-offer strategy for a virtual energy storage merchant: A stochastic bi-level model with all-scenario feasibility

Abstract Increased penetration of renewable resources emphasizes opportunities for virtual energy storage (VES) to offer the needed flexibility to the power system. The VES, quite common in China, is in fact the large electricity industrial consumers with a thermal source of electricity generation that allows them to self-supply. The emerging VES concept breaks through the traditional self-supply off-grid status and enables them to interact with the grid as storage facilities by modulating their power source and load in bi-direction. Within this context, this paper analyzes the implications of the strategic participation of a price-making VES with the ability to exercise market power in the electricity market. We develop a stochastic bi-level optimization model, which presents the VES profit-maximization problem, subject to a day-ahead energy clearing optimization under renewable uncertainty. An all-scenario-feasible stochastic (ASFS) method is applied for the first time to the bid-offer problem to deal with the uncertainty, guaranteeing the feasibility of decision making for all scenarios. The proposed stochastic decision-making model is evaluated by using two illustrative test systems and a practical case based on Gansu Province, China. Numerical results reveal the various abilities of the VES merchant in different operating modes in manipulating the market power and gaining profits from price arbitrage under uncertainty. Our proposed model and approach provide an insight for the market operator to track the behaviors of the VES into the market clearing process and to evaluate the portfolio value of VES in spatio-temporal coordination of electricity production.