期刊文献+

计及用户舒适性的家庭智能用电调度优化 被引量:9

Optimal Scheduling for Smart Home Power Consumption Considering User's Comfort
下载PDF
导出
摘要 随着智能家居、家庭分布式能源的广泛应用,以及分时电价的推广,家庭能源系统有了更多更高的功能需求。文中通过分析家庭用电行为和家庭负载工作方式的关系,建立了一种兼顾家庭用电的经济性和舒适性的调度优化模型,同时考虑了分布式能源和需求响应技术的应用,具有重要的实际意义。针对该模型采用了一种改进粒子群算法进行求解,并通过家庭用电的算例进行了验证。算例表明,该模型和算法能够很好地调度家庭电器的用电行为。 ABSTRACT:With the wide application of smart home,more utilization of distributed generations,and the expanding scope of using time-sharing electricity prices,home energy system has more higher functional requirements. By analyzing the relation between household electricity utilizations and household load working modes,this paper presents an optimal scheduling model considering the economy and amenity of home power consumption,and this model has the important practical signi-ficance because its consideration to the application of distri-buted generations and demand response. Aimed at the model, an improved PSO is adopted to solve,and it is verified through the example of home power consumption. The example shows that the model and the algorithm are able to dispatch power behaviors of household appliances.
出处 《电网与清洁能源》 北大核心 2016年第4期58-62,共5页 Power System and Clean Energy
基金 国家电网公司总部科技项目:面向智慧城市的多元能源互联与管理关键技术研究(SGTJDK00DWJS1500097)~~
关键词 HEMS 家庭智能用电 粒子群算法 HEMS smart home power consumption
  • 相关文献

参考文献11

  • 1张延宇,曾鹏,臧传治.智能电网环境下家庭能源管理系统研究综述[J].电力系统保护与控制,2014,42(18):144-154. 被引量:77
  • 2何永秀,王冰,熊威,张婷,刘洋洋.基于模糊综合评价的居民智能用电行为分析与互动机制设计[J].电网技术,2012,36(10):247-252. 被引量:72
  • 3HAZAS M,FRIDAY A, SCOTT J. Look back before lea-ping forward: four decades of domestic energy inquiry [J].IEEE Pervasive Computing, 2011,10(1): 13-19.
  • 4OZTURK Y, SENTHILKUMAR D,KUMAR S, et a]. Anintelligent home energy management system to improvedemand response[J]. IEEE Trans on Smart Grid, 2013, 4(2): 694-701.
  • 5PIPAITANASOMPORN M,KUZLU M, RAHMAN S. Analgorithm for intelligent home energy management anddemand response analysis[J]. IEEE Trans on Smart Grid,2012,3(4): 2166-2173.
  • 6CHEN C,NAGANANDA K G,XIONG G, et al. Acommunication—based appliance scheduling scheme forconsumer —premise energy management systems[J], IEEETrans on Smart Grid, 2013,4(1 ): 56—65.
  • 7王继东,杨羽昊,周越,石坤,李德智,赵建立.家庭智能用电系统建模及优化策略分析[J].电力系统及其自动化学报,2014,26(11):63-66. 被引量:9
  • 8HAN D M,LIM J H. Smart home energy managementaystem using IEEE 802.15.4 and ZigBeefJ]. ConsumerElectronics IEEE Transactions on, 2010,56(3): 1403-1410.
  • 9钱振,蔡世波,顾宇庆,童建军,鲍官军.光伏发电功率预测方法研究综述[J].机电工程,2015,32(5):651-659. 被引量:29
  • 10LONG D H,PLOIX S,ZAMAI E, et al. Tabu search forthe optimization of household energy consumptionfC]//Information Reuse and Integration,2006 IEEE Intema-tional Conference on IEEE,2006: 86-92.

二级参考文献107

共引文献259

同被引文献107

引证文献9

二级引证文献45

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部