| 引用本文: | 齐结红,钱 虹,吴文军.超短期热负荷预测在发电机组厂级供热调度的应用[J].电力系统保护与控制,2023,51(18):117-124. |
| QI Jiehong,QIAN Hong,WU Wenjun.Application of ultra-short-term heat load forecasting in power plant level heat supply dispatching[J].Power System Protection and Control,2023,51(18):117-124 |
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| 摘要: |
| 对于火力发电厂的综合能源应用，存在供热蒸汽调度控制和管道延迟导致的供热蒸汽不能及时满足供热用户需求的问题。根据所延时的时间长度提出采用对供热用户需求的预测值取代实时供热需求值作为供热调度的约束条件，基于Informer建立一个热负荷多步时序预测模型。构建的Informer模型采用的概率稀疏自注意力机制能够有效获取热负荷时序数据中的信息，并建立热负荷与相关气象因素之间的非线性关系，进而提高热负荷预测精确度。通过实际现场数据验证表明，建立的基于Informer的热负荷多步时序预测模型能够与未来一段时间内的热负荷有很强的拟合度，并满足实际调度控制延迟对热负荷的需求。 |
| 关键词: 套索回归 Informer 热负荷流量预测 供热调度 |
| DOI：10.19783/j.cnki.pspc.221874 |
| 分类号: |
| 基金项目:上海市自然科学基金项目资助(19ZR1420700)；上海市2019年度“科技创新行动计划”高新技术领域项目资助(195111037) |
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| Application of ultra-short-term heat load forecasting in power plant level heat supply dispatching |
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QI Jiehong1, QIAN Hong2, 3, WU Wenjun1
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1. School of Electric Power Engineering, Shanghai University of Electric Power, Shanghai 200090, China;
2. School of Automation Engineering, Shanghai University of Electric Power, Shanghai 200090, China;
3. Shanghai Key Laboratory of Power Station Automation Technology, Shanghai 200090, China
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| Abstract: |
| For comprehensive energy application by thermal power plants, the heating steam caused by the heating steam dispatching control and pipeline delay does not meet, in timely fashion, the needs of heating users. From the length of time delay, it is proposed to replace the real-time heating demand with the predicted value of heating user demand as the constraint condition of heating dispatch. Based on Informer, a multi-step time series prediction model of heat load is established. The prob-sparse self-attention mechanism adopted in the Informer model can effectively obtain the information in the heat load time series data, and establish the nonlinear relationship between heat load and related meteorological factors, thus improving the accuracy of heat load prediction. The verification of actual field data shows that the multi-step time series prediction model of heat load based on Informer established in this paper can have a strong fit with the heat load in a future period of time, and meet the demand of actual scheduling control delay for heat load. |
| Key words: LASSO regression Informer heat load flow prediction heat supply dispatching |
