Day-ahead Optimal Scheduling of Regenerative Electric Heating System Considering Load Imbalance

Abstract

For the regenerative electric heating system, on the premise of ensuring reliable heat supply to users, a day-ahead optimization scheduling method for the regenerative electric heating system considering the load imbalance is proposed. First, users heating demand under normal working conditions and grid power rationing scenarios are calculated by estimate index method. Then, in order to match the heating demand of users and reduce the load imbalance caused by thermal storage electric heating in the distribution network, comprehensive consideration of grid constraints and the adjustable capacity of regenerative electric heating load, the operating strategy of the thermal storage electric heating system is studied. Reasonable control of heat storage and release in regenerative electric heating can not only reduce the distribution line pressure during heating period, but also maximize the accommodation of low-cost electricity such as surplus renewable energy and improve the economic benefits of the system. Taking the regenerative electric heating system in Chongli area of Zhangjiakou, Hebei Province as an example, the multi-objective optimal scheduling model is simulated and analyzed, and the feasibility and effectiveness of the proposed optimal scheduling strategy are verified.