Improved Genetic Algorithm for Distribution System Performance Analysis by Taking Advantage of Essential Spanning Trees
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 (...
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| Format: | Article |
| Language: | English |
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Wiley
2018-01-01
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| Series: | Journal of Engineering |
| Online Access: | http://dx.doi.org/10.1155/2018/1601239 |
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| author | Yanzhu Ji Zhuoqun Shi Robert M. O’Connell |
| author_facet | Yanzhu Ji Zhuoqun Shi Robert M. O’Connell |
| author_sort | Yanzhu Ji |
| collection | DOAJ |
| description | 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. |
| format | Article |
| id | doaj-art-ac3a2dd6959547e1b55df3fb1cdd8b55 |
| institution | Kabale University |
| issn | 2314-4904 2314-4912 |
| language | English |
| publishDate | 2018-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Journal of Engineering |
| spelling | doaj-art-ac3a2dd6959547e1b55df3fb1cdd8b552025-02-03T07:24:42ZengWileyJournal of Engineering2314-49042314-49122018-01-01201810.1155/2018/16012391601239Improved Genetic Algorithm for Distribution System Performance Analysis by Taking Advantage of Essential Spanning TreesYanzhu Ji0Zhuoqun Shi1Robert M. O’Connell2Department of Electrical Engineering and Computer Science, University of Missouri, Columbia, MO, USABlack & Veatch, Kansas City, MO, USADepartment of Electrical Engineering and Computer Science, University of Missouri, Columbia, MO, USAGrowing 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.http://dx.doi.org/10.1155/2018/1601239 |
| spellingShingle | Yanzhu Ji Zhuoqun Shi Robert M. O’Connell Improved Genetic Algorithm for Distribution System Performance Analysis by Taking Advantage of Essential Spanning Trees Journal of Engineering |
| title | Improved Genetic Algorithm for Distribution System Performance Analysis by Taking Advantage of Essential Spanning Trees |
| title_full | Improved Genetic Algorithm for Distribution System Performance Analysis by Taking Advantage of Essential Spanning Trees |
| title_fullStr | Improved Genetic Algorithm for Distribution System Performance Analysis by Taking Advantage of Essential Spanning Trees |
| title_full_unstemmed | Improved Genetic Algorithm for Distribution System Performance Analysis by Taking Advantage of Essential Spanning Trees |
| title_short | Improved Genetic Algorithm for Distribution System Performance Analysis by Taking Advantage of Essential Spanning Trees |
| title_sort | improved genetic algorithm for distribution system performance analysis by taking advantage of essential spanning trees |
| url | http://dx.doi.org/10.1155/2018/1601239 |
| work_keys_str_mv | AT yanzhuji improvedgeneticalgorithmfordistributionsystemperformanceanalysisbytakingadvantageofessentialspanningtrees AT zhuoqunshi improvedgeneticalgorithmfordistributionsystemperformanceanalysisbytakingadvantageofessentialspanningtrees AT robertmoconnell improvedgeneticalgorithmfordistributionsystemperformanceanalysisbytakingadvantageofessentialspanningtrees |