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计及需求价格弹性的区域能源中心建模与日前优化调度

陈泽兴 张勇军 许志恒 蔡泽祥 Thanhtung HA

电力系统自动化2018,Vol.42Issue(12):27-35,9.
电力系统自动化2018,Vol.42Issue(12):27-35,9.DOI:10.7500/AEPS20170524007

计及需求价格弹性的区域能源中心建模与日前优化调度

Modelling and Optimal Day-ahead Dispatch of District Energy Centre Considering Price Elasticity of Energy Load Demand

陈泽兴 1张勇军 1许志恒 1蔡泽祥 1Thanhtung HA1

作者信息

  • 1. 广东省绿色能源技术重点实验室,华南理工大学电力学院,广东省广州市 510640
  • 折叠

摘要

Abstract

As the energy market is being deregulated,the energy price,as a controllable resource,is expected to promote the optimized operation of multi-energy (such as electricity,gas,heat/cool) in the district energy centre (DEC).Based on the energy hub modelling method,the general linear modelling method of power balance equation in DEC is presented.In addition, after taking into account the price elasticity of energy load demand,piecewise linearization modeling of energy load demand is conducted,and the description of piecewise linear function is unified by introducing a 0-1 logic variable and several linear constraints.Further,aiming at DEC net revenue maximization,the mixed integral quadratic programming model for optimal day-ahead dispatch of DEC is developed,in which the controllability of energy price is taken into consideration,and CPLEX called from GAMS is used for solution.Finally,with a case study on microgrid-type DEC,the proposed modeling method is verified,and the influences of control of energy price,different price elasticity and prediction error of new energy on the dispatch results are analyzed.The results show that full use of load price elasticity will help reduce load variance and peak-valley difference,and deep the optimization potential of DEC,while maximize the DEC revenue.

关键词

价格弹性/区域能源中心/分段线性化/GAMS/优化调度

Key words

price elasticity/district energy centre (DEC)/piecewise linearization/GAMS/optimal dispatch

引用本文复制引用

陈泽兴,张勇军,许志恒,蔡泽祥,Thanhtung HA..计及需求价格弹性的区域能源中心建模与日前优化调度[J].电力系统自动化,2018,42(12):27-35,9.

基金项目

国家自然科学基金资助项目(51777077) (51777077)

广东省自然科学基金资助项目(2017A030313304).This work is supported by National Natural Science Foundation of China (No.51777077) and Guangdong Provincial Natural Science Foundation of China(No.2017A030313304). (2017A030313304)

电力系统自动化

OA北大核心CSCDCSTPCD

1000-1026

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