Optimal Scheduling of a Microgrid Using Multiobjective Biogeography-Based Optimization Model and Algorithm with Adaptive Migration

Aiming at the important research topic of optimal scheduling in the microgrid field, the general model for multiobjective dynamic optimal scheduling of a microgrid is established with the objective of minimizing economic and environmental costs. On this basis, the model is organically integrated wit...

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Vydáno v:Mathematical problems in engineering Ročník 2020; číslo 2020; s. 1 - 15
Hlavní autoři: Li, Bo, Xia, Nan, Wang, Jue
Médium: Journal Article
Jazyk:angličtina
Vydáno: Cairo, Egypt Hindawi Publishing Corporation 2020
Hindawi
John Wiley & Sons, Inc
Témata:
Adaptive algorithms
Batteries
Biogeography
Constraint modelling
Consumption
Distributed generation
Economic models
Efficiency
Energy management
Evolutionary algorithms
Fuel cells
Genetic algorithms
Linear programming
Mathematical models
Multiple objective analysis
Natural gas
Operating costs
Optimization algorithms
Optimization models
Pareto optimization
Power supply
Scheduling
System effectiveness
Turbines
Wind power
ISSN:1024-123X, 1563-5147
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Shrnutí:Aiming at the important research topic of optimal scheduling in the microgrid field, the general model for multiobjective dynamic optimal scheduling of a microgrid is established with the objective of minimizing economic and environmental costs. On this basis, the model is organically integrated with constraint handling technology, multiobjective optimization, and biogeography-based optimization algorithm, and then a constrained multiobjective evolutionary model suitable for biogeography-based optimization is further established. The corresponding constraint handling mechanism, the determination method of habitat suitability index, and migration strategy are improved, and the convergence performance and the distribution uniformity of Pareto frontier for multiobjective evolutionary algorithm are effectively enhanced. Applied to the optimal scheduling of typical microgrid systems, the effectiveness of the proposed model and method is verified.
Bibliografie:ObjectType-Article-1
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ISSN:1024-123X
1563-5147
DOI:10.1155/2020/7120352