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基于态势感知的配电网空间负荷预测系统

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针对动态地区配电网空间负荷优化预测问题,设计了一种基于实时自控态势感知的配电网空间负荷预测系统.首先构建配电网空间负荷预测目标决策要素经验池;然后利用深度长短期神经网络对配电网历史运行数据集进行处理,实现配电网实时自控态势感知;最后利用深度确定性策略梯度算法构建空间负荷预测与目标决策要素经验池之间的耦合模型,实现配电网空间负荷高效精准预测.对模型展开了实际算例分析,多类型配网供电区域场景下配电网空间负荷预测精度达到91.03%,多类型配网供电区域场景下配电网空间负荷预测效率提高了23.71%.
Spatial load forecasting system for distribution network based on situational awareness
To solve the optimization and forecasting problem of spatial load of distribution network in dy-namic areas,the spatial load forecasting system of distribution network based on real-time self-control situa-tional awareness is designed.Firstly,the experience pool of objective decision-making elements of distribu-tion network spatial load forecasting is constructed.Then,the deep long-term and short-term neural network is used to process the historical operation data set of distribution network,so as to realize the real-time auto-matic situational awareness of distribution network.Finally,the coupling model between spatial load fore-casting and the experience pool of target decision-making elements is constructed by using the deep deter-ministic strategy gradient algorithm to realize the efficient and accurate spatial load forecasting of distribution network.The actual example analysis of the model shows that the accuracy of distribution network spatial load forecasting under the scenario of multi type distribution network power supply area is 91.03%,and the efficiency of distribution network spatial load forecasting under the scenario of multi type distribution net-work power supply area is improved by 23.71%.

automatic control situation awarenessdistribution network systemspatial load forecastinglimit mapping relationshipcoupling forecasting model

周忠强、黄育松、梁铃、施诗、覃海、陈胜

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中国南方电网贵州电网有限责任公司电力调度控制中心,贵阳 550002

自控态势感知 配电网系统 空间负荷预测 限制映射关系 耦合预测模型

中国南方电网有限责任公司科技研究项目贵州电网有限责任公司科技研究项目

06650-0KK521800170665002019070305FS00009

2024

10.13274/j.cnki.hdzj.2024.03.018

信息技术
黑龙江省信息技术学会 中国电子信息产业发展研究院　中国信息产业部电子信息中心

信息技术

CSTPCD
影响因子：0.413
ISSN：1009-2552
年,卷(期)：2024.(3)
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