电器与能效管理技术Issue(2)：25-31,37,8.DOI:10.16628/j.cnki.2095-8188.2019.02.005
厨房电器设备非侵入式粒子群搜索辨识及参数优化方法研究
Research on Kitchen Electrical Equipment Identification and Parameter Optimization Method by PSO Based on NIML
张云翔 1赵少东 1饶竹一 1秦毅 2吴恒3
作者信息
- 1. 南方电网深圳供电局有限公司,广东 深圳 518001
- 2. 深圳微网能源管理系统实验室有限公司,广东 深圳 518001
- 3. 江苏智臻能源科技有限公司,江苏 南京 211100
- 折叠
摘要
Abstract
In order to explore the potential of residents' load to participate the demand side response and avoid the problem that intrusive load monitoring (ILM) is difficult to popularize in residential load collection, a method based on non-intrusive load monitoring (NILM) was proposed to search and identify the steady-state characteristics of the gate through particle swarm optimization (PSO) .Furthermore, an optimization method of identification coefficient was proposed, to solve the problem of low identification accuracy rate based on single in multi-feature and difficult to determine the identification coefficient of comprehensive of multi-feature quantity.Finally, the effectiveness of the proposed method was verified based on a set of examples, which can effectively improve the accuracy rate of kitchen equipment identification through electrical steady-state characteristics.关键词
需求侧响应/非侵入量测/粒子群算法/参数优化Key words
demand side response/non-intrusive load monitoring (NILM)/particle swarm optimization (PSO)/parameter optimization分类
信息技术与安全科学引用本文复制引用
张云翔,赵少东,饶竹一,秦毅,吴恒..厨房电器设备非侵入式粒子群搜索辨识及参数优化方法研究[J].电器与能效管理技术,2019,(2):25-31,37,8.
