Multi-time scale dynamic robust optimal scheduling of CCHP microgrid based on rolling optimization

Abstract

Combined cooling, heating and power (CCHP) microgrid can effectively improve the efficiency of renewable energy and reduce the operating cost of microgrids. However, the uncertainties of renewable energy sources and variety load demands make the optimal scheduling of CCHP microgrid complex and difficult to achieve. In this paper, a novel multi-time scale dynamic robust optimal scheduling strategy is proposed for the coordinated operation of CCHP microgrid, which includes two time scales: the day-ahead scheduling scale and the intraday adjustment scale. In the day-ahead scheduling scale, the uncertainties of CCHP microgrid are introduced by describing the day-ahead forecast data as interval numbers with upper and lower bounds. The scheduling decision-making variables and the interaction power with power grid are obtained by considering the regulation cost in the worst-case scenario. In the intraday scheduling operation scale, the rolling optimization strategy is applied to obtain intraday optimal power allocation by minimizing the scheduling cost at each prediction horizon based on the intraday ultra-short-term forecast data, which preserves the day-ahead scheduling decision. Finally, the power deviation of the intraday ultra-short-term optimal power allocation is smoothed based on real-time operating data. The simulation results demonstrate that the proposed strategy can effectively reduce the operating cost and improve the robustness for the coordinated operation of CCHP microgrid.