基于灰狼算法的多目标智能家居负荷控制算法
|
摘要
为实现智能家居负荷智能控制,以电器用电量为依据,设计三级电价模型。设计多参数舒适度模型,将开关电器和温度控制电器分类建模,以智能设备收集的温湿度、光照强度、人体活动情况数据为基础进行负荷优化控制。采用灰狼算法对多目标问题进行求解,灰狼算法在求解高维、多峰的复杂函数问题有其优越性,理论和实验分析都证明灰狼算法在求解精度和稳定性均优于粒子群算法和差分进化算法等。经过实验仿真分析,提出的算法能够兼顾用户舒适度的同时有效降低电器用电量。
A three level electricity price model is designed based on the electricity consumption. A comfort model of multi parameters is designed for optimizing the grid load control of temperature and the humidity, light intensity and human activity. Grey wolf algorithm is used to solve the multi-objective problem. The grey wolf algorithm has its superiority in solving high dimensional and multi peak of complex function problems. Theoretical and experimental analysis shows that the grey wolf algorithm in accuracy and stability is better than particle swarm optimization algorithm and differential evolution algorithm. The simulation results show that the proposed algorithm can make user comfort and reduce the power consumption.
A three level electricity price model is designed based on the electricity consumption. A comfort model of multi parameters is designed for optimizing the grid load control of temperature and the humidity, light intensity and human activity. Grey wolf algorithm is used to solve the multi-objective problem. The grey wolf algorithm has its superiority in solving high dimensional and multi peak of complex function problems. Theoretical and experimental analysis shows that the grey wolf algorithm in accuracy and stability is better than particle swarm optimization algorithm and differential evolution algorithm. The simulation results show that the proposed algorithm can make user comfort and reduce the power consumption.
引文
[1]Heleno M,Matos M A,Lopes J A P,et al.Estimating the flexible residential load using appliances availability[C]//Power Engineering and Optimization Conference.IEEE,2014:352-357.
[2]高雪莹,唐昊,苗刚中,等.储能系统能量调度与需求响应联合优化控制[J].系统仿真学报,2016,28(5):1165-1172.Gao Xueying,Tang Hao,Miao Gangzhong,et al.Joint optimization control of energy storage system management and demand response[J].Journal of System Simulation,2016,28(5):1165-1172.
[3]高元海,王淳,游宇堃,等.满足辐射状约束的编码和遗传算子及其在配电网重构中的应用[J].系统工程理论与实践,2016,36(1):234-242.Gao Yuanhai,Wang Chun,You Yukun,et al.Coding and genetic operators of satisfying network radial constraint and application in distribution network reconfiguration[J].Systems Engineering-Theory&Practice,2016,36(1):234-242.
[4]Laki E,Arta G,Gubina A F.Agent-based modeling of the demand-side system reserve provision[J].Electric Power Systems Research(S0378-7796),2015,124:85-91.
[5]王远,陶烨,袁军,等.一种基于HBase的智能电网时序大数据处理方法[J].系统仿真学报,2016,28(3):559-568.Wang Yuan,Tao Ye,Yuan Jun,et al.Approach to process smart grid time-serial big data on HBase[J].Journal of System Simulation,2016,28(3):559-568.
[6]杨胜春,刘建涛,姚建国,等.多时间尺度协调的柔性负荷互动响应调度模型与策略[J].中国电机工程学报,2014,34(22):3664-3673.Yang Shengchun,Liu Jiantao,Yao Jianguo,et al.Model and strategy for multi-time scale coordinated flexible load interactive scheduling[J].Proceedings of The Chinese Society for Electrical Engineering,2014,34(22):3664-3673.
[7]阮冰洁,杨强,颜文骏.计及实时电价的柔性负荷系统需求侧响应机制研究[J].机电工程,2015,32(6):857-862.Ruan Bingjie,Yang Qiang,Yan Wenjun.Demand response under real-time price for domestic energy system[J].Journal of Mechanical&Electrical Engineering,2015,32(6):857-862.
[8]张延宇,曾鹏,李忠文,等.智能电网环境下空调系统多目标优化控制算法[J].电网技术,2014,38(7):1819-1826.Zhang Yanyu,Zeng Peng,Li Zhongwen,et al.Amulti-objective optimal control algorithm for air conditioning system in smart grid[J].Power System Technology,2014,38(7):1819-1826.
[9]Mirjalili S,Mirjalili S M,Lewis A.Grey Wolf Optimizer[J].Advances in Engineering Software(S0965-9978),2014,69(3):46-61.
[10]Logenthiran T,Srinivasan D,Shun T Z.Demand Side Management in Smart Grid Using Heuristic Optimization[J].IEEE Transactions on Smart Grid(S1949-3053),2012,3(3):1244-1252.
[11]Luo F,Zhao J,Wang H,et al.Direct load control by distributed imperialist competitive algorithm[J].Journal of Modern Power Systems and Clean Energy(S2196-5625),2014,2(4):385-395.
[12]Liu G,Tomsovic K.A full demand response model in co-optimized energy and reserve market[J].Electric Power Systems Research(S0378-7796),2014,111(2):62-70.
[2]高雪莹,唐昊,苗刚中,等.储能系统能量调度与需求响应联合优化控制[J].系统仿真学报,2016,28(5):1165-1172.Gao Xueying,Tang Hao,Miao Gangzhong,et al.Joint optimization control of energy storage system management and demand response[J].Journal of System Simulation,2016,28(5):1165-1172.
[3]高元海,王淳,游宇堃,等.满足辐射状约束的编码和遗传算子及其在配电网重构中的应用[J].系统工程理论与实践,2016,36(1):234-242.Gao Yuanhai,Wang Chun,You Yukun,et al.Coding and genetic operators of satisfying network radial constraint and application in distribution network reconfiguration[J].Systems Engineering-Theory&Practice,2016,36(1):234-242.
[4]Laki E,Arta G,Gubina A F.Agent-based modeling of the demand-side system reserve provision[J].Electric Power Systems Research(S0378-7796),2015,124:85-91.
[5]王远,陶烨,袁军,等.一种基于HBase的智能电网时序大数据处理方法[J].系统仿真学报,2016,28(3):559-568.Wang Yuan,Tao Ye,Yuan Jun,et al.Approach to process smart grid time-serial big data on HBase[J].Journal of System Simulation,2016,28(3):559-568.
[6]杨胜春,刘建涛,姚建国,等.多时间尺度协调的柔性负荷互动响应调度模型与策略[J].中国电机工程学报,2014,34(22):3664-3673.Yang Shengchun,Liu Jiantao,Yao Jianguo,et al.Model and strategy for multi-time scale coordinated flexible load interactive scheduling[J].Proceedings of The Chinese Society for Electrical Engineering,2014,34(22):3664-3673.
[7]阮冰洁,杨强,颜文骏.计及实时电价的柔性负荷系统需求侧响应机制研究[J].机电工程,2015,32(6):857-862.Ruan Bingjie,Yang Qiang,Yan Wenjun.Demand response under real-time price for domestic energy system[J].Journal of Mechanical&Electrical Engineering,2015,32(6):857-862.
[8]张延宇,曾鹏,李忠文,等.智能电网环境下空调系统多目标优化控制算法[J].电网技术,2014,38(7):1819-1826.Zhang Yanyu,Zeng Peng,Li Zhongwen,et al.Amulti-objective optimal control algorithm for air conditioning system in smart grid[J].Power System Technology,2014,38(7):1819-1826.
[9]Mirjalili S,Mirjalili S M,Lewis A.Grey Wolf Optimizer[J].Advances in Engineering Software(S0965-9978),2014,69(3):46-61.
[10]Logenthiran T,Srinivasan D,Shun T Z.Demand Side Management in Smart Grid Using Heuristic Optimization[J].IEEE Transactions on Smart Grid(S1949-3053),2012,3(3):1244-1252.
[11]Luo F,Zhao J,Wang H,et al.Direct load control by distributed imperialist competitive algorithm[J].Journal of Modern Power Systems and Clean Energy(S2196-5625),2014,2(4):385-395.
[12]Liu G,Tomsovic K.A full demand response model in co-optimized energy and reserve market[J].Electric Power Systems Research(S0378-7796),2014,111(2):62-70.