期刊名称：Bulletin of the Institute of Heat Engineering
印刷版ISSN：2083-4187
出版年度：2016
卷号：96
期号：4
页码：219
语种：English
出版社：Warsaw University of Technology
摘要：Microgrids (MGs) are recognized as cores and clusters of smart distribution networks. The optimal planning and clusteringof smart low-voltage distribution networks into autonomous MGs within a greenfield area is modeled and discussed in thispaper. In order to form and determine the electrical boundary of MGs set, some predefined criteria such as power mismatch,supply security and load density are defined. The network includes an external grid as backup and both dispatchable andnon-dispatchable Distributed Energy Resources (DERs) as MGs resources. The proposed strategy offers optimum sizing andsiting of DERs and MV substations for the autonomous operation of multiple MGs simultaneously. The imperialist competitivealgorithm (ICA) is used to optimize the cost function to determine the optimal linked MG clustering boundary. To evaluate thealgorithm the proposed method is applied to a greenfield area which is planned to become a mixed residential and commercialtown. The MGs’ optimal border, DERs location, size and type within each MG and LV feeders route are illustrated in bothgraphical and tabular form.
其他摘要：Microgrids (MGs) are recognized as cores and clusters of smart distribution networks. The optimal planning and clustering of smart low-voltage distribution networks into autonomous MGs within a greenfield area is modeled and discussed in this paper. In order to form and determine the electrical boundary of MGs set, some predefined criteria such as power mismatch, supply security and load density are defined. The network includes an external grid as backup and both dispatchable and non-dispatchable Distributed Energy Resources (DERs) as MGs resources. The proposed strategy offers optimum sizing and siting of DERs and MV substations for the autonomous operation of multiple MGs simultaneously. The imperialist competitive algorithm (ICA) is used to optimize the cost function to determine the optimal linked MG clustering boundary. To evaluate the algorithm the proposed method is applied to a greenfield area which is planned to become a mixed residential and commercial town. The MGs’ optimal border, DERs location, size and type within each MG and LV feeders route are illustrated in both graphical and tabular form.
