improved genetic algorithm for distribution system performance analysis by taking advantage of essential spanning trees

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ID: 176744
2018
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Abstract
Growing interest in the smart grid, increasing use of distributed generation, and classical distribution system reconfiguration (DSR) and restoration problems have led to the search for efficient distribution automation tools. One such tool, the improved Fast Nondominated Sorting Genetic Algorithm (FNSGA), not only is effective in finding system configurations that are optimal with respect to voltages, currents, and losses, but also considered parametric study to determine minimum values of N and Gen. In this paper, the essential spanning tree concept is expanded to improve the computational efficiency of the algorithm. Results of the study show that for relatively small test systems, optimum system configurations are obtained using values of N and Gen that require very small CPU times. In larger systems, optimum values of N and Gen requiring reasonable CPU times can also be found, provided that certain carefully chosen branches are removed from the pool of possibilities when producing the initial population in the algorithm. By using essential trees, the efficiency of the calculation is improved.
Reference Key
ji2018journalimproved Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors ;Yanzhu Ji;Zhuoqun Shi;Robert M. O’Connell
Journal Plant foods for human nutrition (Dordrecht, Netherlands)
Year 2018
DOI
10.1155/2018/1601239
URL
http://dx.doi.org/10.1155/2018/1601239
Keywords
engineering (general) civil engineering (general)

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