考虑广义需求侧资源的深度置信网络短期负荷预测方法
随着智能电网信息化水平的不断提高以及可控负荷、分布式电源和储能等广义需求侧资源的大量接入,将产生海量负荷数据集并改变负荷特性.为了提高负荷预测精度,提出了一种考虑广义需求侧资源的深度置信网络(DBN)负荷预测方法.首先,借助负荷聚合商确定了广义需求侧资源参与电力市场的机制,构建了基于合同的广义需求侧资源调度模型,并利用该模型求解广义需求侧资源参与电力市场的最优调度计划.其次,引入DBN结构,并将广义需求侧资源的最优调度计划作为其输入量,建立了短期负荷预测模型.最后,以实际数据进行仿真测试,结果表明,本文所提方法具有更高的预测精度....
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| Published in | 控制理论与应用 Vol. 40; no. 3; pp. 493 - 501 |
|---|---|
| Main Authors | , , , |
| Format | Journal Article |
| Language | Chinese |
| Published |
合肥工业大学电气与自动化工程学院,安徽合肥230009
01.03.2023
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| Subjects | |
| Online Access | Get full text |
| ISSN | 1000-8152 |
| DOI | 10.7641/CTA.2021.10209 |
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| Abstract | 随着智能电网信息化水平的不断提高以及可控负荷、分布式电源和储能等广义需求侧资源的大量接入,将产生海量负荷数据集并改变负荷特性.为了提高负荷预测精度,提出了一种考虑广义需求侧资源的深度置信网络(DBN)负荷预测方法.首先,借助负荷聚合商确定了广义需求侧资源参与电力市场的机制,构建了基于合同的广义需求侧资源调度模型,并利用该模型求解广义需求侧资源参与电力市场的最优调度计划.其次,引入DBN结构,并将广义需求侧资源的最优调度计划作为其输入量,建立了短期负荷预测模型.最后,以实际数据进行仿真测试,结果表明,本文所提方法具有更高的预测精度. |
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| AbstractList | 随着智能电网信息化水平的不断提高以及可控负荷、分布式电源和储能等广义需求侧资源的大量接入,将产生海量负荷数据集并改变负荷特性.为了提高负荷预测精度,提出了一种考虑广义需求侧资源的深度置信网络(DBN)负荷预测方法.首先,借助负荷聚合商确定了广义需求侧资源参与电力市场的机制,构建了基于合同的广义需求侧资源调度模型,并利用该模型求解广义需求侧资源参与电力市场的最优调度计划.其次,引入DBN结构,并将广义需求侧资源的最优调度计划作为其输入量,建立了短期负荷预测模型.最后,以实际数据进行仿真测试,结果表明,本文所提方法具有更高的预测精度. |
| Author | 唐昊 吕凯 胡实 杨晨芳 |
| AuthorAffiliation | 合肥工业大学电气与自动化工程学院,安徽合肥230009 |
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| Keywords | 深度置信网络 广义需求侧资源 负荷聚合商 短期负荷预测 |
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| Title | 考虑广义需求侧资源的深度置信网络短期负荷预测方法 |
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