袁静,杭晨阳,方杰,张新,郑晓楠,杨杰

• 1:中国电建集团华东勘测设计研究院有限公司
• 2:河海大学电气与动力工程学院

摘要(Abstract)：

【目的】在抽水蓄能电站技术供水系统的实际运行过程中，对于冷却水量的调节较为粗放，其历史数据并不能直接用于研究，因此考虑将机组温度作为中间变量，通过研究工况-温度-流量的映射关系，实现技术供水系统的智能调控。【方法】针对该问题，首先通过建立改进的长短期神经网络(LSTM)技术供水系统温度预测模型，将负荷等工况参数作为输入量预测技术供水对象的温度，随后通过Fluent仿真建立温度与流量的映射关系，最后根据拉依达准则计算得到的温度阈值判断是否报警，并给出推荐流量。【结果】实例计算结果显示：所提改进LSTM方法相较于其他方法，预测精度至少提高58.45%,同时仿真所得推荐流量基本符合电站实际运行数据，在满足安全运行的前提下节水量至少达到2.33%。【结论】结果表明：所提方法可以对目标温度做到较为精准地预测，并在此基础上通过内置仿真模型，实现更合理地分配用水量，对抽水蓄能电站技术供水系统智能调节具有一定指导意义。

关键词(KeyWords)： 抽水蓄能电站;技术供水系统;改进长短期神经网络LSTM;Fluent仿真;阈值报警

Abstract:

Keywords:

基金项目(Foundation): 国家自然科学基金重点项目(52339006);; 国网新源集团(控股)有限公司科技项目(SGXYTB00YWJS2100090)

作者(Author): 袁静,杭晨阳,方杰,张新,郑晓楠,杨杰

DOI: 10.13928/j.cnki.wrahe.2024.10.012

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