| 注册
首页|期刊导航|山东电力技术|基于EBSILON的母管制热电联产系统多目标负荷优化研究

基于EBSILON的母管制热电联产系统多目标负荷优化研究

胡一鸣 陈斌 李明 钟江 李蔚 肖颖

山东电力技术2024,Vol.51Issue(7):61-67,7.
山东电力技术2024,Vol.51Issue(7):61-67,7.DOI:10.20097/j.cnki.issn1007-9904.2024.07.008

基于EBSILON的母管制热电联产系统多目标负荷优化研究

Multi-objective Load Optimization Study of Main-pipeline CHP Units Based on EBSILON

胡一鸣 1陈斌 1李明 1钟江 1李蔚 2肖颖2

作者信息

  • 1. 桐乡泰爱斯环保能源有限公司,浙江 桐乡 314500
  • 2. 浙江大学能源工程学院,浙江 杭州 310027
  • 折叠

摘要

Abstract

At present,the optimal distribution of power plant load is one of the most important technical means to reduce coal consumption,pollutant emissions,and improve economic efficiency.For a main-pipeline CHP(Combined Heat and Power)unit composed of four boilers and two steam turbines,EBSILON simulation software is applied to establish an optimal operation model for power and heat supply,and the model accuracy is verified based on the comparison between the historical operation data of the plant and the simulation values.Considering the environmental protection and economy,each optimization objective is assigned weight,and the multi-objective optimization system is constructed based on the integrated weight assignment of subjective weighting method-Analytic Hierarchy Process and objective weighting method-CRITIC.Then enumeration method and flower pollination algorithm were used to select real-time production data to optimize load distribution calculation,and EBSILON was used to calculate and verify the variable working conditions.The results show that this optimisation method can achieve better energy saving and carbon reduction effect.In one month,the amount of coal consumption can be reduced by about 550 tons,carbon dioxide emissions by about 1139 tons and pollutant emissions by about 0.24 tons,which provides a new idea for the optimal operation of CHP units.

关键词

多目标负荷优化/EBSILON建模/层次分析法/CRITIC法

Key words

multi-objective load optimization/EBSILON modeling/analytic hierarchy process/CRITIC method

分类

信息技术与安全科学

引用本文复制引用

胡一鸣,陈斌,李明,钟江,李蔚,肖颖..基于EBSILON的母管制热电联产系统多目标负荷优化研究[J].山东电力技术,2024,51(7):61-67,7.

基金项目

国家重点研发计划项目(2019YFE0126000). National Key Research and Development Program of China(2019YFE0126000). (2019YFE0126000)

山东电力技术

OACSTPCD

1007-9904

访问量0
|
下载量0
段落导航相关论文