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面向燃煤机组高效灵活运行的智能化配煤掺烧优化决策方法

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

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【作者】 张海林杨博董玉亮张健袁家海

【Author】 ZHANG Hailin;YANG Bo;DONG Yuliang;ZHANG Jian;YUAN Jiahai;China Huaneng Group Co., Ltd.;School of Energy, Power and Mechanical Engineering, North China Electric Power University;School of Economics and Management, North China Electric Power University;

【机构】 中国华能集团有限公司华北电力大学能源动力与机械工程学院华北电力大学经济与管理学院

【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.

【基金】 国家重点研发计划项目(2020YFC0827001);中国华能集团有限公司总部软科学项目(2021-8技术研究)~~
  • 【文献出处】 热力发电 ,Thermal Power Generation , 编辑部邮箱 ,2022年04期
  • 【分类号】TM621
  • 【下载频次】234
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