Research on Methods for Converting Controllable Loads of Household Appliances Into Intelligent Loads in the Ubiquitous Power Internet of Things

Qinchun HE; Xiuyuan YANG

doi:10.12096/j.2096-4528.pgt.19176

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Research on Methods for Converting Controllable Loads of Household Appliances Into Intelligent Loads in the Ubiquitous Power Internet of Things

Key Technologies for Ubiquitous Power Internet of Things and Integrated | 更新时间：2025-07-04

- Research on Methods for Converting Controllable Loads of Household Appliances Into Intelligent Loads in the Ubiquitous Power Internet of Things
- Power Generation Technology Vol. 41, Issue 1, Pages: 94-102(2020)
- 作者机构：
  
  北京信息科技大学自动化学院, 北京市海淀区 100192
- 作者简介：
- 基金信息：
  
  National Natural Science Foundation of China(51377011)
- DOI：10.12096/j.2096-4528.pgt.19176
  CLC： TM73
- Received：20 November 2019，
  
  Published：29 February 2020
- 稿件说明：
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Qinchun HE, Xiuyuan YANG. Research on Methods for Converting Controllable Loads of Household Appliances Into Intelligent Loads in the Ubiquitous Power Internet of Things[J]. Power Generation Technology, 2020, 41(1): 94-102.
DOI：

Qinchun HE, Xiuyuan YANG. Research on Methods for Converting Controllable Loads of Household Appliances Into Intelligent Loads in the Ubiquitous Power Internet of Things[J]. Power Generation Technology, 2020, 41(1): 94-102. DOI： 10.12096/j.2096-4528.pgt.19176.

摘要

为了实现负荷控制，传统的需求响应针对居民用户主要采用拉闸限电的调峰策略，用电方式较为被动。泛在电力物联网概念的提出使可控负荷转化成智能负荷成为可能。为了实现可控负荷控制的智能化，研究了泛在电力物联网在家电可控负荷控制中的应用。在智能家电控制算法中增加电网闲时的填谷作用，不仅实现了用电高峰期电网削峰，而且有效利用了用电低谷时期的容量闲置。并且允许用户预先设定负荷需求范围和不同时段家电重要系数，最大限度地满足了用户的舒适度需求。仿真结果验证了改进后智能家电控制算法的合理性。

Abstract

In order to achieve load control

the traditional demand response mainly uses the peak-adjusting strategy of the power-limiting for residents

and the power consumption is more passive. The concept of ubiquitous power internet of things makes it possible to convert controllable loads into intelligent loads. In order to realize the intelligentization of controllable load control

the application of ubiquitous power internet of things in the controllable load control of household appliances was studied. Increasing the valley-filling function in the smart household appliance control algorithm not only achieved peak-cutting of the power grid during peak periods of power consumption

but also effectively utilized idle capacity during periods of low-power consumption. It also allowed users to set the load demand range and important coefficients of household appliances at different time in advance

which satisfied the user's comfort needs to the greatest extent. The simulation results verified the rationality of the improved control algorithm for intelligent household appliances.

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references

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