In the centralized scheduling of multi-residents, the complexity of scheduling time will be greatly increased as the number of resident increases. In order to reduce the time complexity caused by centralized scheduling, a probability model based on the Time-of-use electricity tariff difference is proposed and applied to distributed estimation of the algorithm. According to the impact factor mechanism of the probability model of Time-of-use electricity tariff difference, not only the time complexity of centralized scheduling is reduced, but also the optimization of the algorithm will not fall into a local optimal situation. In the centralized scheduling model of building residents, the controllable load of residents and new energy are centralized. The consumption rate of new energy was improved by changing the new energy power supply mechanism. Under the conditions of ensuring the comfort of household electricity consumption, three objective functions of the model include: (a) to reduce the total daily electricity consumption, (b) to flatten the peak-to-valley difference of daily electricity, (c) to decrease the discarded rate of new energy. The simulation of the calculation example verifies the feasibility and effectiveness of the proposed method.

在多居民集中调度中，调度时间的复杂度将随着居民数量的增加而大大增加。为了降低集中调度带来的时间复杂度，提出了一种基于使用时间电价差的概率模型，并将其应用于算法的分布式估计。根据分时电价差概率模型的影响因素机制，不仅降低了集中调度的时间复杂度，而且算法的优化也不会陷入局部最优的情况。在建筑物居民集中调度模型中，居民的可控负荷和新能源是集中的。改变新能源供电机制，提高了新能源消耗率。在确保家庭用电舒适的条件下，该模型的三个目标功能包括：（a）减少每日总用电量；（b）缩小每日用电峰谷差；（c）降低新能源的废弃率。仿真算例验证了该方法的可行性和有效性。