Abstract：Research on load monitoring and decomposition has broad prospects. Electricity information can be refined to internal load composition details, which has high application value for the two-way interaction and demand-side management in the smart grid, achieving benefits to electric power companies and power consumers. However, the existing non-intrusive load monitoring and disaggregation (NILMD) methods lack the concern about electricity consumption characteristics and solution to multi-state electrical appliances. Thus, this paper considers the difference between load patterns, and then divides the loads of weekdays and weekends separately into certain clusters based on the affinity propagation (AP) method. After that, combining with the conditional judgment to working state rationality, this paper realizes the decomposition of different electrical appliances and the corresponding state-changes from the total load signal according to multi-feature genetic iteration. The case study shows that the proposed method can effectively identify various electrical appliances. The proposed method uses steady state power signatures, reduces hardware cost to some extent, and is friendly to the general sampling equipment.
[1] 徐建军, 王保娥, 闫丽梅, 等. 混合能源协同控制的智能家庭能源优化控制策略[J]. 电工技术学报, 2017, 32(12): 214-223. Xu Jianjun, Wang Bao’e, Yan Limei, et al.The strategy of the smart home energy optimization control of the hybrid energy coordinated control[J]. Transactions of China Electrotechnical Society, 2017, 32(12): 214-223. [2] 余晓丹, 徐宪东, 陈硕翼, 等. 综合能源系统与能源互联网简述[J]. 电工技术学报, 2016, 31(1): 1-13. Yu Xiaodan, Xu Xiandong, Chen Shuoyi, et al.A brief review to integrated energy system and energy internet[J]. Transactions of China Electrotechnical Society, 2016, 31(1): 1-13. [3] 范黎, 隗震, 娄素华, 等. 配电项目最大供电能力及增供电量效益的评估[J]. 电工技术学报, 2017, 32(增刊1): 84-91. Fan Li, Wei Zhen, Lou Suhua, et al.The evaluation for maximum power supply capability and benefit of increasing power supply of distribution system[J]. Transactions of China Electrotechnical Society, 2017, 32(S1): 84-91. [4] 樊玮, 刘念, 张建华. 事件驱动的智能家庭在线能量管理算法[J]. 电工技术学报, 2016, 31(13): 130-140. Fan Wei, Liu Nian, Zhang Jianhua.An online algorithm based on event triggering for energy management of smart home[J]. Transactions of China Electrotechnical Society, 2016, 31(13): 130-140. [5] 陶顺, 陈鹏伟, 肖湘宁, 等. 智能配电网不确定性建模与供电特征优化技术综述[J]. 电工技术学报, 2017, 32(10): 77-91. Tao Shun, Chen Pengwei, Xiao Xiangning, et al.Review on uncertainty modeling and power supply characteristics optimization technology in smart distribution network[J]. Transactions of China Electrotechnical Society, 2017, 32(10): 77-91. [6] 卢锦玲, 於慧敏. 考虑风电相依结构的虚拟发电厂内部资源随机调度策略[J]. 电工技术学报, 2017, 32(17): 67-74. Lu Jinling, Yu Huimin.Stochastic scheduling strategy of resources in virtual power plant con- sidering wind power dependence structure[J]. Transactions of China Electrotechnical Society, 2017, 32(17): 67-74. [7] 王守相, 孙智卿, 孔繁钢, 等. 面向需求响应的建筑用能在线分解方法[J]. 电力自动化设备, 2017, 37(3): 1-6. Wang Shouxiang, Sun Zhiqing, Kong Fangang, et al.Online building energy disaggregation orienting to demand response[J]. Electric Power Automation Equipment, 2017, 37(3): 1-6. [8] 李滨, 杜孟远, 祝云, 等. 基于准实时数据的智能配电网状态估计[J]. 电工技术学报, 2016, 31(1): 34-44. Li Bin, Du Mengyuan, Zhu Yun, et al.A state estimator for smart distribution networks with quasi- real time data[J]. Transactions of China Electro- technical Society, 2016, 31(1): 34-44. [9] 吴聪, 唐巍, 白牧可, 等. 基于二层规划的用户侧能源互联网规划[J]. 电工技术学报, 2017, 32(21): 122-131. Wu Cong, Tang Wei, Bai Muke, et al.Optimal planning of energy internet near user side based on bi-level programming[J]. Transactions of China Electrotechnical Society, 2017, 32(21): 122-131. [10] 程祥, 李林芝, 吴浩, 等. 非侵入式负荷监测与分解研究综述[J]. 电网技术, 2016, 40(10): 3108-3117. Cheng Xiang, Li Linzhi, Wu Hao, et al.A survey of the research on non-intrusive load monitoring and disaggregation[J]. Power System Technology, 2016, 40(10): 3108-3117. [11] 余贻鑫, 刘博, 栾文鹏. 非侵入式居民电力负荷监测与分解技术[J]. 南方电网技术, 2013, 7(4): 1-5. Yu Yixin, Liu Bo, Luan Wenpeng.Nonintrusive residential load monitoring and decomposition technology[J]. Southern Power System Technology, 2013, 7(4): 1-5. [12] Hart G W.Nonintrusive appliance load monitoring[J]. Proceedings of the IEEE, 1992, 80(12): 1870-1891. [13] Marchiori A, Hakkarinen D, Han Q, et al.Circuit- level load monitoring for household energy management[J]. IEEE Pervasive Computing, 2011, 10(1): 40-48. [14] Suzuki K, Inagaki S, Suzuki T, et al.Nonintrusive appliance load monitoring based on integer programming[C]//SICE Annual Conference, Tokyo, Japan, 2008: 2742-2747. [15] Lai Y X, Lai C F, Huang Y M, et al.Multi-appliance recognition system with hybrid SVM/GMM classifier in ubiquitous smart home[J]. Information Sciences, 2013, 230(4): 39-55. [16] 高云, 杨洪耕. 基于暂态特征贴近度匹配的家用负荷识别[J]. 电力系统自动化, 2013, 37(9): 54-59. Gao Yun, Yang Honggeng.Household load identi- fication based on closeness matching of transient characteristics[J]. Automation of Electric Power Systems, 2013, 37(9): 54-59. [17] Leeb S B, Shaw S R, Kirtley J L.Transient event detection in spectral envelope estimates for nonintrusive load monitoring[J]. IEEE Transactions on Power Delivery, 1995, 10(3): 1200-1210. [18] 曲朝阳, 于华涛, 郭晓利. 基于开启瞬时负荷特征的家电负荷识别[J]. 电工技术学报, 2015, 30(增刊1): 358-364. Qu Zhaoyang, Yu Huatao, Guo Xiaoli.The recognition of appliances instantaneous load[J]. Transactions of China Electrotechnical Society, 2015, 30(S1): 358-364. [19] 高云, 杨洪耕. 基于明可夫斯基距离的家用负荷分类计量[J]. 电测与仪表, 2013, 50(5): 86-90. Gao Yun, Yang Honggeng.Household load measure- ment by classification based on minkowski distance[J]. Electrical Measurement & Instrumentation, 2013, 50(5): 86-90. [20] Cox R, Leeb S B, Shaw S R, et al.Transient event detection for nonintrusive load monitoring and demand side management using voltage distortion[C]// Twenty-First Annual Meeting on Applied Power Electronics Conference and Exposition, Dallas, TX, USA, 2006: 1751-1757. [21] Liang J, Ng S K K, Kendall G, et al. Load signature study-Part I: Basic concept, structure, and methodo- logy[J]. IEEE Transactions on Power Delivery, 2010, 25(2): 551-560. [22] Liang J, Ng S K K, Kendall G, et al. Load signature study—Part II: Disaggregation framework, simu- lation, and applications[J]. IEEE Transactions on Power Delivery, 2010, 25(2): 561-569. [23] 祁兵, 程媛, 武昕. 基于Fisher有监督判别的非侵入式居民负荷辨识方法[J]. 电网技术, 2016, 40(8): 2484-2490. Qi Bing, Cheng Yuan, Wu Xin.Non-intrusive household appliance load identification method based on fisher supervised discriminant[J]. Power System Technology, 2016, 40(8): 2484-2490. [24] Egarter D, Bhuvana V P, Elmenreich W.PALDi: Online load disaggregation via particle filtering[J]. IEEE Transactions on Instrumentation and Measurement, 2015, 64(2): 467-477. [25] 陈思运, 高峰, 刘烃, 等. 基于因子隐马尔可夫模型的负荷分解方法及灵敏度分析[J]. 电力系统自动化, 2016, 40(21): 128-136. Chen Siyun, Gao Feng, Liu Ting, et al.Load disaggregation method based on factorial hidden Markov model and its sensitivity analysis[J]. Automation of Electric Power Systems, 2016, 40(21): 128-136. [26] Frey B J, Dueck D.Clustering by passing messages between data points[J]. Science, 2007, 315(5814): 972-976. [27] 周琼, 贠志皓, 丰颖, 等. 风电接入下基于AP聚类的无功功率—电压控制分区方法[J]. 电力系统自动化, 2016, 40(13): 19-27, 158. Zhou Qiong, Yun Zhihao, Feng Ying, et al.Reactive power-voltage control partitioning of wind power integration system based on affinity propagation clustering[J]. Automation of Electric Power Systems, 2016, 40(13): 19-27, 158. [28] 褚壮壮, 梁军, 张旭, 等. 基于仿射传播聚类算法的广义负荷稳态特性建模及其应用[J]. 电力自动化设备, 2016, 36(3): 115-123. Chu Zhuangzhuang, Liang Jun, Zhang Xu, et al.Modeling of generalized load steady-state characteri- stics based on affinity propagation clustering algorithm and its application[J]. Electric Power Automation Equipment, 2016, 36(3): 115-123. [29] 曾博, 李英姿, 冯家欢, 等. 计及电动汽车无功支撑能力的分布式电源与智能停车场联合规划方法[J]. 电工技术学报, 2017, 32(15): 78-90. Zeng Bo, Li Yingzi, Feng Jiahuan, et al.A combinatorial planning method for distributed generation and intelligent parking lots considering reactive supporting capability of electric vehicles[J]. Transactions of China Electrotechnical Society, 2017, 32(15): 78-90.
2018, Vol. 33 
