Intelligent load distribution of cogeneration units in deep peak regulation mode

WU Tao; LAI Fei; LIU Zhen; WANG Zhiwei; HE Xin; XU Chuangxue; XUE Hanguang; SHI Lei; XU Chen

doi:10.19666/j.rlfd.202101018

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Intelligent load distribution of cogeneration units in deep peak regulation mode

更新时间：2025-09-28

- Intelligent load distribution of cogeneration units in deep peak regulation mode
- Thermal Power Generation Vol. 50, Issue 9, Pages: 119-127(2021)
- 作者机构：
  
  1. 西安热工研究院有限公司
  2. 上海海事大学物流科学与工程研究院
- 作者简介：
- 基金信息：
- DOI：10.19666/j.rlfd.202101018
  CLC： TM621;TM714
- Published：2021
- 稿件说明：
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WU Tao, LAI Fei, LIU Zhen, et al. Intelligent load distribution of cogeneration units in deep peak regulation mode[J]. Thermal power generation, 2021, 50(9): 119-127.
DOI：

WU Tao, LAI Fei, LIU Zhen, et al. Intelligent load distribution of cogeneration units in deep peak regulation mode[J]. Thermal power generation, 2021, 50(9): 119-127. DOI： 10.19666/j.rlfd.202101018.

摘要

本文提出一种新的不同供热负荷、发电负荷下的供热煤耗率和发电煤耗率的计算方法

并据此拟合出不同供热负荷下

随发电负荷变化的供热煤耗率曲线、供电煤耗率曲线以及最大发电功率和最小发电功率

利用拉格朗日插值法得到机组在可行域内随发电负荷和供热负荷变化的供热、发电煤耗率曲面。然后结合当地的深度调峰政策、燃料成本和热电售价等

准确计算出热电联产机组的实时成本和利润。最后基于自适应遗传算法找出在给定供热负荷的条件下使得2台机组总利润最大的发电负荷分配方式。本文方法既能给出热电联产企业实时成本和利润

又能给出机组当前调峰时期较优的负荷分配方式

从而指导运行决策人员做出更合理的运行策略。

Abstract

A new method is proposed to calculate the heating coal consumption rate and power generation coal consumption rate at different heating loads and power generation loads. On this basis

the heating coal consumption rate curve and power supply coal consumption rate curve that change with the power generation load

as well as the maximum and minimum generating power at different heating loads

are fitted. By using the Lagrangian interpolation method

the curved surface of coal consumption rate of heating and power generation which changes with the power generation load and the heating load in feasible region is obtained. Combined with the local in-depth peak shaving policy and fuel cost

the real-time cost and profit of the cogeneration plant is accurately calculated. Finally

based on the self-adaptive genetic algorithm

the load distribution method that maximizes the total profit of the two units under the conditions of given heating power is determined. The final method can both give the current real-time cost and profit of the cogeneration company

and also give the best load distribution method during the current peak shaving period of the power plant

and guide the operation decision-maker to make the optimal operation strategy.

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