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基于成本-效益分析的温控负荷需求响应模型与方法

王剑晓 钟海旺 夏清 杨胜春

电力系统自动化Issue(5):45-53,9.
电力系统自动化Issue(5):45-53,9.DOI:10.7500/AEPS20150521009

基于成本-效益分析的温控负荷需求响应模型与方法

Model and Method of Demand Response for Thermostatically-controlled Loads Based on Cost-benefit Analysis

王剑晓 1钟海旺 2夏清 1杨胜春2

作者信息

  • 1. 清华大学电机工程与应用电子技术系,北京市 100084
  • 2. 电力系统及发电设备控制和仿真国家重点实验室,清华大学,北京市 100084
  • 折叠

摘要

Abstract

Traditional demand response(DR) research is based on the price elasticity of demand in economics.However,the elasticity can hardly be obtained for lack of historical data,leading to the difficulty in exactly reflecting customers” response behavior.Therefore,an economy-driven model and a method of DR for thermostatically-controlled loads based on cost-benefit analysis are proposed.Take the ice storage equipment as an example.Customers” investment behavior with respect to mid-term and long-term DR response is studied.According to historical operation data,customers” consumption stickiness is recognized and an economy-driven DR model is developed.The DR model is optimized in light of the annual load curve.Then the scenario reducing technique is employed to extract typical annual scenarios,thereby decreasing model dimensions and improving computational efficiency.After analyzing the cost and benefit of DR,the customer DR function is generated,by which the customers” response behavior is accurately reflected.The case study based on an industrial customer in a province shows that the model and method proposed can recognize customers” consumption stickiness,generate DR functions and exactly reflect customers” response behavior,while achieving scientific decision making for mid-term and long-term DR investment.

关键词

需求响应/成本-效益分析/温控负荷/制冰蓄冷/消费粘性/场景削减

Key words

demand response (DR)/cost-benefit analysis/thermostatically-controlled loads/ice storage/consumption stickiness/scenario reduction

引用本文复制引用

王剑晓,钟海旺,夏清,杨胜春..基于成本-效益分析的温控负荷需求响应模型与方法[J].电力系统自动化,2016,(5):45-53,9.

基金项目

国家自然科学基金资助项目(51537005) (51537005)

国家电网公司科技项目(DZ71-14-042)。This work is supported by National Natural Science Foundation of China (No.51537005) and State Grid Corporation of China(No.DZ71-14-042) (DZ71-14-042)

电力系统自动化

OA北大核心CSCDCSTPCD

1000-1026

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