Risk-factor-oriented stochastic dominance approach for industrial integrated energy system operation leveraging physical and financial flexible resources

The rapid development of renewable energy resources poses challenges to the economic and reliable operation of energy systems, necessitating the risk management by utilizing various flexible resources and optimization techniques. However, when there exist multiple risk factors faced by decision maker, it might be difficult to clearly control the risks of intermittent renewables. To resolve this issue, a stochastic dominance-constrained operation strategy leveraging flexible resources is developed for an industrial integrated energy system (IIES), and a risk factor-oriented benchmark selection method is proposed to manage the risks of intermittent renewables given the full profit distribution, which makes the proposed strategy superior to the stochastic strategies using certain risk measures. Firstly, the theory and mathematics of stochastic dominance are systematically introduced, and a stochastic dominance-constrained model is then developed for an IIES in electricity markets. Next, a risk factor-oriented benchmark distribution selection method is proposed by solving the stochastic model without considering a specific risk factor, based on which a stochastic dominance-constrained operation strategy for IIES leveraging flexible resources is obtained. Finally, case studies are conducted by using realistic data in the electricity markets of the United States. It is shown that the intermittent renewables decreased the profits by more than 7 % in half of the scenarios, while the proposed risk-factor-oriented stochastic dominance-constrained approach is shown to effectively manage this type of risk in all scenarios by employing flexible financial and physical resources. If the financial resource in trading account is increased by 33.33 %, the fixed investment cost of installing storage could be decreased by 92.59 %.