Real-time optimal operation of integrated electricity and heat system considering reserve provision of large-scale heat pumps

Abstract

The day-ahead operational schedule of the integrated electricity and heat system may be suboptimal due to prediction errors of renewables and loads. This paper proposes a real-time optimal operation scheme for the integrated electricity and heat system considering reserve provision from large scale heat pumps, which utilizes model predictive control and different operating reserves to gradually balance forecast errors of renewables and loads in the co-optimization of reserve deployment and heat regulation. The real-time operation is divided into two stages including real-time pre-scheduling and real-time balancing. A two-stage model predictive control approach is proposed to deploy following reserve and regulating reserve for real-time pre-scheduling and real-time balancing, respectively. The following reserve in the real-time pre-scheduling is used to deal with the day-ahead forecast errors, while the regulating reserve in the real-time balancing is to handle real-time forecast errors. In addition, a detailed reserve provision model of large-scale heat pumps is built. The case studies are conducted on a 6-bus integrated electricity and heat system. The simulation results show that the proposed two-stage approach uses following and regulating reserves from large-scale heat pumps to further reduce operational cost, wind power curtailment, and load shedding. The MPC approach can obtain a feasible solution closer to the ideal solution.