基于多目标分子动理论的楼宇负荷用电调度优化

Optimal Scheduling of Building Load Electricity Consumption Based on Multi-Objective Molecular Motion Theory

针对智能用电环境下保证用电经济性、舒适性以及电网侧稳定性目标的楼宇多用户日负荷调度问题,提出一种基于多目标分子动理论的智能楼宇负荷用电调度优化策略。首先根据楼宇用户中不同负荷特征,对楼宇用电负荷进行分类,搭建楼宇多用户负荷用电调度模型;其次,针对该模型对分子动理论优化算法进行多目标改进,引入基于按维审查的模糊拥挤判定思想得到最优解集可供选择,提高种群多样性和分布性,然后将其用于楼宇多用户负荷调度模型中进行多目标优化;最后,通过算例仿真实验及对比分析可知,所提优化策略能较好地实现楼宇用户用电经济性和舒适性目标,同时达到平抑电网侧波动的效果。

Aiming to ensure electricity economy, comfort and grid side stability in intelligent electricity environment for multi-user daily load scheduling in building, an intelligent building load electricity scheduling strategy based on multi-objective molecular motion theory was proposed. Firstly, according to characteristic of different loads for building users, the building electricity load was classified and a multi-user load electricity scheduling model was built. Secondly, this paper made a multi-objective improvement of molecular motion theory optimization algorithm and introduced the idea of fuzzy congestion decision based on dimension review to get and choose the optimal solution. The improved algorithm increased diversity and distribution of the population, and then used it to carry out multi-objective optimization of multi-user load scheduling model. Finally, according to example simulation and comparative analysis, the proposed optimization strategy can better realize economy and comfort goals of building users’ electricity, and achieve effect of stabilizing fluctuation of grid side.