Multi-objective generators commitment model of power system for energy conservation and emission reduction

DING Linjun; CHEN Jinghua; GUO Zhuangzhi; LIANG Lili; Li Jinbei

doi:10.3969/j.issn.1672-3643.2016.05.004

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Multi-objective generators commitment model of power system for energy conservation and emission reduction

更新时间：2025-09-24

- Multi-objective generators commitment model of power system for energy conservation and emission reduction
- Ningxia Electric Power Issue 5, (2016)
- 作者机构：
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- DOI：10.3969/j.issn.1672-3643.2016.05.004
  CLC：
- Published Online：26 October 2020，
  
  Published：2016
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DING Linjun, CHEN Jinghua, GUO Zhuangzhi, et al. Multi-objective generators commitment model of power system for energy conservation and emission reduction[J]. Ningxia electric power, 2016, (5).
DOI：

DING Linjun, CHEN Jinghua, GUO Zhuangzhi, et al. Multi-objective generators commitment model of power system for energy conservation and emission reduction[J]. Ningxia electric power, 2016, (5). DOI： 10.3969/j.issn.1672-3643.2016.05.004.

摘要

针对电力系统发电机组节能减排问题

通过建立连续变量和离散变量之间的关系

利用互补约束和最优化极值理论

构建了电力系统的多目标机组组合互补约束优化模型

并引入熵权法进行多目标决策

采用原对偶内点法进行了仿真验证。仿真结果表明:(1)以火电机组煤耗量

污染气体 CO2 和 SO2 排放量为优化目标的多目标机组组合模型

符合实际的工程需求。(2)利用模糊熵权法对建立的模型进行多目标决策

可实现节能、CO2 和 SO2 排放目标之间的转化和相互协调

从而有效降低火电机组的煤耗量

同时也减少了污染气 CO2 和 SO2的排放总量。

Abstract

Aiming at the energy conservation and emission reduction problem of generation unit inpower system

by establishing the relationship between continuous variables and discrete variables andusing complementarity constraints and optimization extreme value theory

builds a complementarityconstraint optimization model of multi- objective unit commitment in power system

and introducesentropy weight method to make multi- objective decision

adopts the original dual interior pointmethod to validate. The simulation results show that: (1) The multi-objective generators commitmentmodel with the optimization aim for coal consumption of coal- fired generators and the emissioncapacity of pollutant gas CO2 and SO2 meet the practical engineering requirements. (2) Using fuzzyentropy weight to make multi-objective decision can realize the conversion and mutual coordinationbetween the energy saving and emission aims of CO2 and SO2

effectively reduce both the coalconsumption of coal-fired generators and the total emission amounts of CO2 and SO2.

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