长安大学电子与控制工程学院,西安,710064
网络首发:2014-09-10,
纸质出版:2014
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惠萌, 刘盼芝. 电力系统短期负荷新型Volterra预测模型研究[J]. 西安交通大学学报, 2014,48(9):24-29.
A Novel Volterra Prediction Model for Power System Short-Term Load Prediction[J]. 2014, 48(9): 24-29.
惠萌, 刘盼芝. 电力系统短期负荷新型Volterra预测模型研究[J]. 西安交通大学学报, 2014,48(9):24-29. DOI: 10.7652/xjtuxb201409005.
A Novel Volterra Prediction Model for Power System Short-Term Load Prediction[J]. 2014, 48(9): 24-29. DOI: 10.7652/xjtuxb201409005.
针对电力系统负荷短时预测问题
从分析负荷数据的混沌特性入手
利用相空间重构理论对负荷数据进行重构
构建了一种新型的Volterra模型对电力系统负荷进行预测。该模型采用二次线性微分方程方法对原Volterra级数进行变换
与以往Volterra级数相比
该模型无截断误差
包含了系统更多精确的信息。最后
以某地区实际用电负荷数据为对象进行验证
结果表明:该模型2 d和4 d用电负荷预测结果和实际结果误差不超过5%
完全能够满足电力调度需求
同时也为电力公司制定经济模型和实时电价调整提供了理论支持。
Focusing on short-term load forecasting in power system
a novel Volterra model is proposed. Once determining whether chaotic character exists in the load time series
the load time series is reconstructed following phase space reconstruction theory. Compared with normal Volterra model
the new Volterra model contains more accurate information of system without truncated errors. This Volterra model is used to predict a short-term load and the results show that the error between the predicted load and true load is less than 5%. The predicted short-term load is accurate enough for electric power dispatching
especially for power companies to adjust price.
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