Two-stage information-gap optimization decision model of electricity-hydrogen integrated virtual power plant with shared energy storage

Amidst the escalating challenges of energy security and environmental crises, the transition towards a renewable energy-centric energy mix has become imperative. Consequently, the development of distributed energy storage systems, including shared energy storage system (SESS) and hydrogen energy system (HSS), holds immense potential in addressing the consumption challenges posed by renewable energy. In this paper, a near-zero carbon emission electric-hydrogen integrated virtual power plant (VPP) is proposed, incorporating the generation uncertainties of wind power (WT) and photovoltaic (PV). Firstly, the model's foundation comprises the mathematical formulations of the HSS model, SESS model, and demand response (DR) model. Secondly, in the dayahead stage, the optimal electricity purchase and sale strategies is determined. In the real-time stage, the output deviation at each time point of renewable energy is determined by the real time information gap decision theory. Finally, to comprehensively evaluate the impact of the risk avoidance and opportunity pursuit strategies, four cases are designed to compare the role of SESS and HSS. The results show that: (1) The average equivalent utilization coefficient of SESS increased by 8.15 % and 22.94 %. (2) In the day-ahead market, the net income of purchasing and selling electricity increased by & YEN; 653.58. And in the real-time market, the net income increased by & YEN; 208.57 and & YEN; 885.48. (3) The devised strategy presents decision-making support for VPP operators, catering to their diverse risk preferences.