Day-ahead scheduling optimization of microgrid with solar energy storage heat pump

Under the dual-carbon target, heat pumps are currently regarded as devices with substantial potential for carbon neutrality. In order to improve the coefficient of performance (COP) of heat pumps, solar heat pumps are proposed. There are few studies on the dynamic characteristics of solar ejector heat pump thermal storage systems (SEHPTES). This paper establishes a solar assist ejector heat pump phase change energy storage system, which simultaneously utilizes solar photothermal and photovoltaic energy, thus increasing the utilization rate of renewable energy in the system. A solar heat pump electrical heating microgrid model is then developed, taking into account user comfort and demand response. The day-ahead scheduling of the microgrid is optimized, and the optimized results under various scenarios are economically and technically assessed using multiple evaluation indices. Dynamic simulation analysis of the solar thermal pump is performed, which aims at improving the COP, coupled with the optimization of its geometric and operating parameters using a multi-objective genetic algorithm (GA) under typical meteorological conditions for a typical day. After optimization, the COP of the solar thermal pump is improved by 10.8%, and the average instantaneous heat storage capacity of the thermal storage tank is increased by 13.09%. The peak-shaving and valley-filling coefficient of the solar jet thermal pump-based microgrid is increased by 4.5% after demand response, indicating that demand response can enhance the flexibility of the microgrid. Finally, a case study is passed on to study the anti-risk ability of microgrids, which also confirms that the consideration of elastic thermal energy load can make microgrids operate flexibly and stably.