Intelligent coal blending optimization decision method for efficient and flexible operation of coal-fired units

ZHANG Hailin; YANG Bo; DONG Yuliang; ZHANG Jian; YUAN Jiahai

doi:10.19666/j.rlfd.202110222

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Intelligent coal blending optimization decision method for efficient and flexible operation of coal-fired units

更新时间：2025-09-28

- Intelligent coal blending optimization decision method for efficient and flexible operation of coal-fired units
- Thermal Power Generation Vol. 51, Issue 4, Pages: 30-37(2022)
- 作者机构：
  
  1. 中国华能集团有限公司
  2. 华北电力大学能源动力与机械工程学院
  3. 华北电力大学经济与管理学院
- 作者简介：
- 基金信息：
- DOI：10.19666/j.rlfd.202110222
  CLC： TM621
- Published：2022
- 稿件说明：
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ZHANG Hailin, YANG Bo, DONG Yuliang, et al. Intelligent coal blending optimization decision method for efficient and flexible operation of coal-fired units[J]. Thermal power generation, 2022, 51(4): 30-37.
DOI：

ZHANG Hailin, YANG Bo, DONG Yuliang, et al. Intelligent coal blending optimization decision method for efficient and flexible operation of coal-fired units[J]. Thermal power generation, 2022, 51(4): 30-37. DOI： 10.19666/j.rlfd.202110222.

摘要

针对当前燃煤机组灵活运行中存在的配煤掺烧决策难题，提出了一种智能化配煤掺烧优化决策方法。该方法在对机组历史运行数据进行稳态数据筛选的基础上，建立机组效率SBM动态评价模型，并对稳态数据进行运行效率评价，进而建立包含环境温度、湿度、机组功率、全局效率和配煤方案的配煤掺烧决策数据库。对于未来某一决策周期，根据日前计划负荷曲线和天气预报获得机组运行工况，并利用余弦相似度在决策数据库搜索最佳匹配历史运行工况，根据匹配结果按照效率最高原则，实现配煤掺烧方案的决策。实例证明该方法可行有效，可以实现燃煤机组配煤掺烧优化决策，提高机组运行的高效性和灵活性，为新能源电力系统安全运行提供保障。

Abstract

Aiming at solving the problem of coal blending decision-making in flexible operation of coal-fired power units

an intelligent coal blending optimization decision-making method is proposed. Based on the steady-state data screening of the unit operation history data

the SBM dynamic evaluation model of unit efficiency is established

and the unit operation efficiency evaluation is carried out for the steady-state data

and then the coal blending decision database including ambient temperature

humidity

unit power

global efficiency and coal blending scheme is established. For a future decision-making cycle

the unit operating condition vector is obtained according to the day ahead load plan and weather forecast

and the cosine similarity is used to search the best matching historical operating conditions in the decision-making database. According to the matching results and the principle of the highest energy efficiency

the decision-making of coal blending scheme is realized. The example shows that this method is feasible and effective

which can realize the optimization decision of coal blending of coal-fired units

improve the efficiency and flexibility of unit operation

and provide guarantee for the safe operation of new energy power system.

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