Assessing Trading Strategies for Distributed Generation Based on Min-Max Regret Approach

Distributed generations (DG) have shown great potential in contributing to the decarbonization of the distributed electricity networks in many countries such as China. However, under different trading programs, market profits vary greatly according to the DG connection status and the consumed electricity volume. Further, long-term uncertainties associated with energy price, subsidies and environmental resource pose risks to the financial sustaina-bility of DGs. Researchers have proposed a range of approaches to inform trading strategies under different DG programs considering uncertainties. However, most of them focus on the possibilities of the worst scenario to ensure the robust trading income, such as stochastic programming and distributionally robust optimization. In this research, a min-max regret approach was adopted to investigate the optimal trading strategy for DGs under multiple trading programs considering long-term uncertainties. A real case study based in Jiangsu was analyzed. The preliminary results showed the efficacy of the min-max regret approach to inform the optimal trading strategy and the optimal choice of DG program.