Optimal allocation of microgrid using a differential multi-agent multi-objective evolution algorithm
The optimal configuration and allocation of a microgrid are one of the key issues to guarantee the economic and reliable working of a microgrid. This is a multi-objective optimisation problem within which the economic index and the load power shortage rate index should be considered when optimising...
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| Published in: | Applied mathematics and nonlinear sciences Vol. 6; no. 2; pp. 111 - 124 |
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| Main Authors: | , , , , |
| Format: | Journal Article |
| Language: | English |
| Published: |
Beirut
Sciendo
01.07.2021
De Gruyter Brill Sp. z o.o., Paradigm Publishing Services |
| Subjects: | |
| ISSN: | 2444-8656, 2444-8656 |
| Online Access: | Get full text |
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| Summary: | The optimal configuration and allocation of a microgrid are one of the key issues to guarantee the economic and reliable working of a microgrid. This is a multi-objective optimisation problem within which the economic index and the load power shortage rate index should be considered when optimising the configuration. In this article, a differential multi-agent multi-objective evolutionary algorithm (DMAMOEA) was designed to optimise the capacity configuration of a microgrid system, which includes three kinds of equipment: wind turbine, photovoltaic equipment and battery. The final optimisation results were compared with the Non-dominated Sorting Genetic Algorithm II (NSGA-II) algorithm. Simulation results showed the effectiveness of the algorithm. At the end of this article, the representative solutions in the calculation results are compared and explained and the environmental benefits are analysed, which show the effectiveness of the implementation of the microgrid system. |
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| Bibliography: | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14 |
| ISSN: | 2444-8656 2444-8656 |
| DOI: | 10.2478/amns.2021.1.00034 |