Energy storage technologies are vital in improving the operation performance of grid-connected distributed energy systems. The adjustability of indoor temperature and the thermal inertia of buildings can form an excellent virtual energy storage. However, there are few studies on the impact of this virtual energy storage on the operation performance of grid-connected distributed energy systems. Therefore, this study first calculates the equivalent thermal resistance and thermal capacitance of a building by using EnergyPlus and establishes the first-order thermodynamic load calculation model. Subsequently, the system dynamic optimal scheduling model, considering the virtual energy storage, was developed based on the first-order thermodynamic load calculation model. The Gurobi nonconvex solver is used to optimize the model, and the results are compared with the optimal scheduling results without considering the virtual energy storage. The results indicate that, guided by time-of-use electricity pricing, the virtual energy storage effectively reduces the air conditioning load during high and peak tariff periods while increasing it during valley tariff periods. This change in air conditioning load leads to an increase in grid power consumption during valley tariff periods. However, it also improves the system's operation efficiency and ultimately reduces the total grid power and gas consumption. The lower energy consumption makes the primary energy saving rate and carbon dioxide emission reduction rate of Scenario 2 greater than zero compared to Scenario 1 and increases with the increase of renewable energy penetration of the integrated power system. Furthermore, affected by the difference in the proportion of grid power consumption under time-of-use electricity pricing and the total energy consumption, the system's operating cost in Scenario 2 is less than in Scenario 1. The reduction rates in summer and winter typical days are 1.95 % and 6.48 %, respectively. Therefore, fully utilizing the virtual energy storage under air conditioning and building coupling can reduce the operating cost, primary energy consumption, and carbon dioxide emissions of grid-connected distributed energy systems.

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评估空调与建筑耦合下虚拟储能对并网分布式能源系统性能的影响

储能技术对于提高并网分布式能源系统的运行性能至关重要。室内温度的可调性和建筑物的热惯性可以形成优良的虚拟能量存储。然而，关于这种虚拟储能对并网分布式能源系统运行性能影响的研究还很少。因此，本研究首先利用EnergyPlus计算建筑物的等效热阻和热容，建立一阶热力负荷计算模型。随后，基于一阶热力负荷计算模型，建立了考虑虚拟储能的系统动态优化调度模型。采用Gurobi非凸求解器对模型进行优化，并将结果与​​不考虑虚拟储能的最优调度结果进行比较。结果表明，在分时电价指导下，虚拟储能有效降低了高电价和高峰电价时段的空调负荷，同时增加了低谷电价时段的空调负荷。空调负荷的这种变化导致谷电价期间电网耗电量的增加。然而，它也提高了系统的运行效率，最终减少了电网总电力和天然气消耗。较低的能耗使得情景2的一次能源节约率和二氧化碳减排率相比情景1大于零，并且随着综合电力系统可再生能源渗透率的增加而增加。此外，受分时电价下电网用电比例与总能耗差异的影响，场景2的系统运行成本低于场景1。夏季和冬季典型日的降低率分别为 1.95% 和 6.48%。因此，充分利用空调与建筑耦合下的虚拟储能可以降低并网分布式能源系统的运行成本、一次能源消耗和二氧化碳排放。