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Optimization of Renewable Energy Sources in a Microgrid Using Artificial Fish Swarm Algorithm
Shanti K. Swarup, Kumar K.P, , Swarup K.S.
Published in Elsevier Ltd
2016
Volume: 90
   
Pages: 107 - 113
Abstract
Advances in microgrid enabling technologies and utilization of Renewable Energy Sources are prompting more and more number of smaller investors to invest in Renewable energy generation and distribution at microgrid level. The increased competition requires the energy producers to offer energy at minimum possible cost to gain the confidence of consumers, which needs efficient methods to schedule the energy generation among the available Renewable Energy Sources. Optimal scheduling of generation is one of the methods used to reduce the cost of generation. Out of many types of algorithms used effectively to solve the problem, evolutionary program techniques are proven and time tested to be one of the best solutions. A stochastic based search algorithm, called Artificial Fish Swarm Algorithm is used in this article to solve the problem of optimal scheduling of energy generation among the available Renewable Energy Sources. The effectiveness of the algorithm is validated by implementing to schedule generation in a microgrid scenario. The results are validated by comparing to an already tested Additive Increase Multiplicative Decrease algorithm. © 2016 The Authors.
About the journal
JournalData powered by TypesetEnergy Procedia
PublisherData powered by TypesetElsevier Ltd
ISSN18766102
Open AccessYes
Concepts (17)
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    Congestion control (communication)
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    Costs
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    Evolutionary algorithms
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    Natural resources
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    Optimization
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    Scheduling
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    Software testing
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    Stochastic systems
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    ADDITIVE INCREASE MULTIPLICATIVE DECREASE
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    ARTIFICIAL FISH SWARM ALGORITHMS
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    Enabling technologies
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    ENERGY GENERATIONS
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    GENERATION SCHEDULLING
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    RENEWABLE ENERGY GENERATION
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    Renewable energy source
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    SCHEDULE GENERATION
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    Renewable energy resources