基于自适应粒子群算法的楼宇智能用电策略  

A strategy for intelligent power utilization in building based on adaptive PSO

作　　者：颜庆国 杨斌 许高杰[2] 杨永标[3] 王璐[4] 高辉[4] 谢俊[4] 

机构地区：[1]国网江苏省电力公司,南京210024 [2]中国电力科学研究院,南京210003 [3]国电南瑞科技股份有限公司,南京211106 [4]南京邮电大学自动化学院,南京210023

出　　处：《电力需求侧管理》2016年第4期1-5,30,共6页Power Demand Side Management

基　　金：国家电网公司总部科技项目:基于复合信息的需求响应多级调控关键技术研究

摘　　要：考虑楼宇拥有光伏发电、储能电池、微型燃气轮机、可控负荷和不可控负荷等电源和负荷,以最小化电费支出,同时保证用户用电舒适度为目标,提出一种楼宇智能用电策略的数学模型。采用基于成功率的自适应混沌惯性权重粒子群算法求解建立的智能用电数学模型,对比于标准粒子群算法表现出更高的收敛精度和收敛速度。成功率计算包含的混沌性和自适应性,在搜索过程中提供更多的状态信息,改善粒子趋优运动。仿真结果证明了智能用电策略的有效性,可以帮助楼宇用户根据自我需求,优化运行电源设备和用电设备,降低电费支出,并提高用电舒适度。This paper presents a strategy for intelligent power utilization in building based on particle swarm optimization with adaptive chaotic inertia weights to minimize electric cost and maximize user＇s comfort. It supposes that photovoltaic generation, batteries, micro turbines, controllable loads and uncontrollable loads exist in smart building. The proposed AIWPSO algorithm used in solving the intelligent power utilization model can further improve the performance of PSO algorithm in terms of convergence speed and accuracy as well as the global searching ability because of the chaotic characteristics and adaptive nature provided by the success rate which can provide the state information of the swarm and help them adjust the inertia value for better position. The simulation results demonstrate the effectiveness of the proposed intelligent power utilization strategy, which can reduce electric cost and increase user＇s comfort through optimally operate power equipments and appliances according to self demand.

关 键 词：粒子群算法(PSO) 自适应混沌惯性权重 智能楼宇 智能用电 

分 类 号：TM73[电气工程—电力系统及自动化]