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Nodal load forecasting method considering spatial correlation and redundancy
- HAN Xueshan, WANG Junxiong, SUN Donglei, LI Wenbo, ZHANG Xinyi, WEI Zhiqing
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JOURNAL OF SHANDONG UNIVERSITY (ENGINEERING SCIENCE). 2017, 47(6):
7-12.
doi:10.6040/j.issn.1672-3961.0.2017.530
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Aiming at the problem that existing nodal load forecasting methods had no effective use for the nodes spatial correlation information, a new nodal load forecasting method with estimated correction characteristic was proposed, which had considered spatial correlation and redundancy. The correlation between the time dimension and the spatial dimension of the measurement information, and the spatial correlation and redundancy characteristics which combined these two dimensions were analyzed, and the mutual correction prediction principle was given. Two spatial correlations between state and measured values were analyzed deeply to establish measuring equations, which could characterise state features indirectly on the spatial correlation topology. Based on the analysis results, the forecasting model was established, and the forecasting method in which pre-prediction model was support vector machine was given, and advantages of the forecasting method were elaborated. Case studies demonstrated that compared with SVM model, the proposed 山 东 大 学 学 报 (工 学 版)第47卷 - 第6期韩学山,等:计及空间关联冗余的节点负荷预测方法 \=-method could effectively decrease forecasting errors and improve forecasting results.
