Optimal Allocation of Distributed Generation Using Hybrid Grey Wolf Optimizer
Optimal allocation of distributed generation units is essential to ensure power loss minimization, while meeting the real and reactive power demands in a distribution network. This paper proposes a solution to this non-convex, discrete problem by using the hybrid grey wolf optimizer, a new metaheuri...
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| Veröffentlicht in: | IEEE access 2017, Vol.5, p.14807-14818 |
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| creator | Sanjay, R. Jayabarathi, T. Raghunathan, T. Ramesh, V. Mithulananthan, Nadarajah |
| description | Optimal allocation of distributed generation units is essential to ensure power loss minimization, while meeting the real and reactive power demands in a distribution network. This paper proposes a solution to this non-convex, discrete problem by using the hybrid grey wolf optimizer, a new metaheuristic algorithm. This algorithm is applied to IEEE 33-, IEEE 69-, and Indian 85-bus radial distribution systems to minimize the power loss. The results show that there is a considerable reduction in the power loss and an enhancement of the voltage profile of the buses across the network. Comparisons show that the proposed method outperforms all other metaheuristic methods, and matches the best results by other methods, including exhaustive search, suggesting that the solution obtained is a global optimum. Furthermore, unlike for most other metaheuristic methods, this is achieved with no tuning of the algorithm on the part of the user, except for the specification of the population size. |
| doi_str_mv | 10.1109/ACCESS.2017.2726586 |
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This paper proposes a solution to this non-convex, discrete problem by using the hybrid grey wolf optimizer, a new metaheuristic algorithm. This algorithm is applied to IEEE 33-, IEEE 69-, and Indian 85-bus radial distribution systems to minimize the power loss. The results show that there is a considerable reduction in the power loss and an enhancement of the voltage profile of the buses across the network. Comparisons show that the proposed method outperforms all other metaheuristic methods, and matches the best results by other methods, including exhaustive search, suggesting that the solution obtained is a global optimum. 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This paper proposes a solution to this non-convex, discrete problem by using the hybrid grey wolf optimizer, a new metaheuristic algorithm. This algorithm is applied to IEEE 33-, IEEE 69-, and Indian 85-bus radial distribution systems to minimize the power loss. The results show that there is a considerable reduction in the power loss and an enhancement of the voltage profile of the buses across the network. Comparisons show that the proposed method outperforms all other metaheuristic methods, and matches the best results by other methods, including exhaustive search, suggesting that the solution obtained is a global optimum. Furthermore, unlike for most other metaheuristic methods, this is achieved with no tuning of the algorithm on the part of the user, except for the specification of the population size.</description><subject>Algorithms</subject><subject>Distributed generation</subject><subject>Distributed generation (DG)</subject><subject>Distributed power generation</subject><subject>Electric power distribution</subject><subject>Heuristic methods</subject><subject>Hybrid power systems</subject><subject>loss minimization</subject><subject>metaheuristic algorithm</subject><subject>optimal DG location</subject><subject>optimal DG size</subject><subject>Optimization</subject><subject>Particle swarm optimization</subject><subject>Radial distribution</subject><subject>radial distribution system</subject><subject>Reactive power</subject><subject>Resource management</subject><subject>Tuning</subject><subject>Xenon</subject><issn>2169-3536</issn><issn>2169-3536</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2017</creationdate><recordtype>article</recordtype><sourceid>ESBDL</sourceid><sourceid>RIE</sourceid><sourceid>DOA</sourceid><recordid>eNpNUU1rwkAQDaWFivUXeAn0HLsf2a-jWKuCxYOVHpfNZiIradZu4sH--q6mSOcyw5t5b2Z4STLGaIIxUi_T2Wy-3U4IwmJCBOFM8rtkQDBXGWWU3_-rH5NR2x5QDBkhJgbJ--bYuS9Tp9O69tZ0zjepr9JX13bBFacOynQBDYS-s2tds0-X5yK4iAc4p5--rtKrhvuB8JQ8VKZuYfSXh8nubf4xW2brzWI1m64zmyPZZQWnlHOEmZLE2IJIwKxgVU6RBaEwNhJbIEIqQYUxhlslUU5KbiTihKGcDpNVr1t6c9DHED8IZ-2N01fAh702oXO2Bq0IxiB5QYiockBlIcpSivi8lNYIAVHrudc6Bv99grbTB38KTTxfk5wxlTMhaZyi_ZQNvm0DVLetGOmLDbq3QV9s0H82RNa4ZzkAuDGEuhyA6C-DwYGh</recordid><startdate>2017</startdate><enddate>2017</enddate><creator>Sanjay, R.</creator><creator>Jayabarathi, T.</creator><creator>Raghunathan, T.</creator><creator>Ramesh, V.</creator><creator>Mithulananthan, Nadarajah</creator><general>IEEE</general><general>The Institute of Electrical and Electronics Engineers, Inc. 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This paper proposes a solution to this non-convex, discrete problem by using the hybrid grey wolf optimizer, a new metaheuristic algorithm. This algorithm is applied to IEEE 33-, IEEE 69-, and Indian 85-bus radial distribution systems to minimize the power loss. The results show that there is a considerable reduction in the power loss and an enhancement of the voltage profile of the buses across the network. Comparisons show that the proposed method outperforms all other metaheuristic methods, and matches the best results by other methods, including exhaustive search, suggesting that the solution obtained is a global optimum. 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| subjects | Algorithms Distributed generation Distributed generation (DG) Distributed power generation Electric power distribution Heuristic methods Hybrid power systems loss minimization metaheuristic algorithm optimal DG location optimal DG size Optimization Particle swarm optimization Radial distribution radial distribution system Reactive power Resource management Tuning Xenon |
| title | Optimal Allocation of Distributed Generation Using Hybrid Grey Wolf Optimizer |
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