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1.东北电力大学电气工程学院,吉林省吉林市 132012
2.北华大学计算机科学技术学院,吉林省吉林市 132021
3.国网吉林省电力有限公司吉林供电公司,吉林省吉林市 132001
肖 白(1973—),男,通信作者,博士,教授,主要研究方向:电力系统规划、空间电力负荷预测、多能源电力系统互补协调发电、电力系统继电保护。E-mail:xbxiaobai@126.com
张小娜(1995—),女,硕士研究生,主要研究方向:城市电网空间电力负荷预测。E-mail:1289700338@qq.com
姜 卓(1978—),女,硕士,副教授,主要研究方向:智能优化算法、软件工程。E-mail:abbey1998@sina.com
收稿日期:2020-11-07,
修回日期:2021-01-12,
网络出版日期:2021-03-01,
纸质出版日期:2021-06-25
移动端阅览
肖白,张小娜,姜卓等.考虑本位元胞接受能力和相邻元胞负荷影响的空间负荷预测[J].电力系统自动化,2021,45(12):57-64.
XIAO Bai,ZHANG Xiaona,JIANG Zhuo,et al.Spatial Load Forecasting Considering Acceptability of Standard Cell and Influence of Load of Adjacent Cells[J].Automation of Electric Power Systems,2021,45(12):57-64.
肖白,张小娜,姜卓等.考虑本位元胞接受能力和相邻元胞负荷影响的空间负荷预测[J].电力系统自动化,2021,45(12):57-64. DOI: 10.7500/AEPS20201107002.
XIAO Bai,ZHANG Xiaona,JIANG Zhuo,et al.Spatial Load Forecasting Considering Acceptability of Standard Cell and Influence of Load of Adjacent Cells[J].Automation of Electric Power Systems,2021,45(12):57-64. DOI: 10.7500/AEPS20201107002.
针对现有空间电力负荷预测方法没有考虑待预测区域内各供电小区之间的负荷相互影响关系的情况,提出一种考虑本位元胞接受能力和相邻元胞负荷影响的空间负荷预测方法,主要适用于城市电网规划年负荷预测。首先,利用变异系数建立本位元胞接受负荷影响的量化模型,来反映本位元胞对相邻元胞负荷影响的接受能力;其次,考虑待预测区域内各元胞之间的距离因素和用电负荷相似性因素生成空间复合权重矩阵,并利用空间卷积建立相邻元胞产生负荷影响的量化模型,来反映相邻元胞对本位元胞产生的负荷影响;然后,综合考虑本位元胞接受负荷影响的能力和相邻元胞产生负荷影响的共同作用,构建空间电力负荷预测模型;最后,通过工程实例分析验证了所提方法及模型的正确性和有效性。
In view of the fact that the existing spatial power load forecasting methods do not consider the load interaction relationship among the power supply cells in the area to be forecasted
a spatial load forecasting method which considers the acceptability of the standard cell and the influence of the load of adjacent cells is proposed
and it is mainly applicable to the annual load forecasting of urban power grid planning. Firstly
a quantitative model of the standard cell accepting the load influence is established by using the coefficient of variation to reflect the acceptability of the standard cell to the load of adjacent cells. Secondly
the spatial composite weight matrix is generated by considering the distance factor between cells and the power load similarity factor in the region to be forecasted
and the quantitative model of the load influence of adjacent cells is established by using the spatial convolution to reflect the load influence of adjacent cells on the standard cell. Then
the spatial power load forecasting model is constructed by comprehensively considering the joint effect of the acceptability of the standard cell to the load influence and the load influence generated by adjacent cells. Finally
the correctness and effectiveness of the proposed method and model are verified by an engineering example.
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