计及用户舒适度与用电成本的空调负荷优化控制方法

合理使用空调和暖气，控制温度在舒适区间 #生活技巧# #节省生活成本# #生活优化# #居家节约#

摘要: 智能电网环境下,应用于空调(商业与居民用户最主要的用电负荷)的需求响应措施对电网稳定运行有重要意义。针对用户参与需求响应过程中导致舒适度明显降低的问题,本文提出了一种用户可参与自主决策的空调负荷优化控制方法,基于改进的免疫克隆选择算法,建立了同时考虑用户舒适度与用电成本的空调负荷多目标优化调控模型;并将原始免疫克隆选择算法中的变异算子改进为一种自适应的非一致性变异算子,进一步提高算法的收敛能力,逼近Pareto最优面。仿真及实验结果表明,本文算法在对空调负荷执行基于分时电价的需求响应过程中,能够有效兼顾用户对经济性和舒适性的需求;优化结果相对用户期望值的亲和力得到明显提升,验证了该算法的有效性和优越性。

Abstract: In smart grid, the demand response applied to air conditioning load, which is the major load of the commercial and residential electricity system, is of great significance for the stable operation of power network. However, participating in demand response may lead to the reduction of consumers comfort. Thus an efficient optimal control method of air conditioning load is put forward, which allows the decision-making of electricity consumers, and a multi-objective optimization model is built based on the improved immune clonal selection algorithm, which optimizes comfort and electricity expense of air conditioning users. In this paper, the mutation operator of the traditional immune clonal selection algorithm is improved as an adaptive non-uniformity mutation operator, which further enhances the convergence of the algorithm and gets a more optimal Pareto-frontier. Results of simulation and tests indicate that multi-objective optimization can effectively balance the users demand for economy and comfort during the process of demand response based on Time-of-Use (TOU) price. Moreover, the antigen affinity can be optimized by improved algorithm, which verifies the effectiveness and advantage of the improved algorithm.

高赐威,梁甜甜,李扬.自动需求响应的理论与实践综述[J].电网技术,2014,38(2):353359.[2] Biao Sun,Peter B L,Qing-Shan Jia,etc.Building Energy Management: Integrated Control of Active and Passive Heating,Cooling,Lighting,Shading,and Ventilation Systems[J].Automation Science and Engineering,2012,10(3):588602.[3] Sankur M,Arnold D,Auslander D.An architecture for integrated commercial building demand response[C]// Power and Energy Society General Meeting (PES),2013 IEEE.IEEE,2013:15.[4] 牛丽仙.需求响应控制系统在智能建筑中的应用案例研究[J].电力需求侧管理,2014,16(4):2125. [5] 张志丹,黄小庆,曹一家,等.电网友好型空调负荷的主动响应策略研究[J].中国电机工程学报,2014,34(25):42074218.[6] 雍静.满足舒适要求的空调系统需求响应及错峰运行策略研究[D].重庆:重庆大学,2011.[7] 付蔚,敬章浩,罗志勇,等.基于分时电价的智能家电控制方案[J].电网技术,2015,39(3):717723.[8] 辛洁晴,吴亮.商务楼中央空调周期性暂停分档控制策略[J].电力系统自动化,2013,37(5):4954.[9] ASHRAE.ANSI/ASHRAE Standard552004. Thermal Environmental Conditions for Human Occupancy[S].Atlanta.GA,2004.[10]Marwan M,Ledwich G,Ghosh A.Smart grid-demand side response model for optimization air conditioning[C]∥Universities Power Engineering Conference (AUPEC),2012 22nd Australasian IEEE,2012:16.[11]Constantopoulos P,Schweppe F C,Larson R C.ESTIA:a real-time consumer control scheme for space conditioning usage under spot electricity pricing[J].Computers & Operations Research,1991,18(8):751765.[12]黄友锐.智能优化算法及其应用[M].北京:国防工业出版社,2008:5468.[13]崔逊学.多目标进化算法及其应用[M].北京:国防工业出版社,2006:416.[14]Hong Ying-Yi, Lin Jie-Kai,Wu Ching-Ping,etc. Multi-Objective Air-Conditioning Control Considering Fuzzy Parameters Using Immune Clonal Selection Programming[J].IEEE TRANSACTIONS ON SMART GRID,2012(3):16031610.[15]徐玉琴,李雪冬.基于改进免疫克隆选择算法的含分布式电源配电网规划方法[J].电网技术,2010,34(8):97101.[16]尚荣华,焦李成,公茂果,等.免疫克隆算法求解动态多目标优化问题[J].软件学报,2007(18):27002711.[17]雍静,文充,曾礼强.夏季空调热舒适响应空间及节能潜力研究[J].四川建筑科学研究,2012(38):304308.

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