Multi-Objective Optimal Scheduling of CHP Microgrid Considering Conditional Value-at-Risk

Abstract

A combined heating and power (CHP) microgrid has high flexibility and economy, but the output of renewable energy is uncertain. Meanwhile, excessive flexible load adjustment in the demand response process will increase user dissatisfaction. In order to solve the above problems, this paper quantifies uncertainty with the conditional value-at-risk (CVaR) of relative disturbance. Additionally, a multi-objective optimal scheduling model that takes into account both the operating economy and the demand-side power consumption satisfaction is established. In order to solve the multi-objective mixed-integer nonlinear programming problem well, we propose an improved sparrow search algorithm (ISSA), which solves the problem that the sparrow search algorithm (SSA) is prone to low accuracy, insufficient in population diversity and easy to be trapped in local optimum. Combined with the non-dominated solution ranking method, ISSA has the ability of multi-objective optimization. Finally, simulation on a typical CHP microgrid is performed. The optimization results under different confidence levels and risk preference coefficients are compared and analyzed. When the risk preference coefficient is 0.1, 2 and 5, the minimum rotating reserve capacity is 75.17 kW, 82.83 kW, and 105.70 kW in the electric part and 40.08 kW, 59.89 kW, and 61.94 kW in the thermal part. The effectiveness of the proposed CVaR of relative disturbance is verified.