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基于负荷台阶的工业需求响应用户优选方法

苏湘波 吕睿可 郭鸿业 陈启鑫

中国电力2024,Vol.57Issue(1):18-29,12.
中国电力2024,Vol.57Issue(1):18-29,12.DOI:10.11930/j.issn.1004-9649.202307044

基于负荷台阶的工业需求响应用户优选方法

A Method for Optimal Selection of High-Capacity Industrial Users for Demand Response Based on Load Step Data Processing Mode

苏湘波 1吕睿可 1郭鸿业 1陈启鑫1

作者信息

  • 1. 清华大学电机工程与应用电子技术系,北京 100084
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摘要

Abstract

In the context of future high penetration of new energy,the uncertainty of supply-demand balance gradually increases.Demand response is an important means of ensuring the balance of power and electricity in the system by tapping into user-side flexible resources.When power sector works on demand response,historical data is needed for an initial assessment of load response potential,so as to select the users with high potential and initiate mobilization efforts.This article focuses on defining and providing a mathematical expression for load step that represents the energy consumption characteristics of industrial users.And then a user selection method for industrial demand response based on load step is proposed.Firstly,an index system for the potential of industrial users'demand response across multiple time scales based on load step is proposed.And then,a user selection model is established to conduct an initial evaluation of different users'response potential,and the k-means algorithm and the nearest neighbor propagation algorithm are used to divide groups,allowing for user selection across different time scales.Finally,a case study is presented based on actual load data from several industrial users in industries such as cement and paper,illustrating the user selection results for industrial demand response using the proposed method.

关键词

工业需求响应/负荷台阶效应/潜力评估/用户优选

Key words

industrial demand response/load step effect/potential assessment/user preference

引用本文复制引用

苏湘波,吕睿可,郭鸿业,陈启鑫..基于负荷台阶的工业需求响应用户优选方法[J].中国电力,2024,57(1):18-29,12.

基金项目

国家自然科学基金青年基金资助项目(52107102),国家电网有限公司科技项目(5108-202218280A-2-378-XG).This work is supported by National Natural Science Foundation of China(No.52107102),the Science and Technology Project of SGCC(No.5108-202218280A-2-378-XG). (52107102)

中国电力

OA北大核心CSTPCD

1004-9649

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