Optimal Control Strategy for a Marine Current Farm Integrated with a Hybrid PV System/Offshore Wind/Battery Energy Storage System

Optimal Control Strategy for a Marine Current Farm Integrated with a Hybrid PV System/Offshore Wind/Battery Energy Storage System



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This paper suggests an automated control technique constructed on the Multi-Objective Particle Swarm Optimization to enhance the operation of a wind farm, a marine power plant and a photovoltaic array with a battery energy storing system. due to changes in PV / wind / tide, and to boost the efficiency of offshore wind farms and marine power stations connected to the battery-powered storage system, with a view to smoothing power production, the aim of projected automatic control strategy is to minimize power fluctuations and voltage variations. The battery energy storage network was used with an optimized demand response strategy based on the real-time pricing model to improve stability and power efficiency, reduce the power fluctuations and variations in bus voltage and address renewable energy generation instability. The multi-objective particle swarm optimization-based energy management programming model would be used to minimize running costs, pollutant emissions, increase the demand response benefits of micro grid operators and, at the same time, meet the load demand constraints from customers of all sorts, such as domestic, commercial and industrial users.

Keywords: Battery Energy Storage System, Renewable Energy integration, Multi-Objective Particle Swarm Optimization, Marine Current Farm, PV system, Offshore Wind Farm
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[1]
Elgammal, A. and Jagessar, M. 2020. Optimal Control Strategy for a Marine Current Farm Integrated with a Hybrid PV System/Offshore Wind/Battery Energy Storage System. European Journal of Electrical Engineering and Computer Science. 4, 4 (Aug. 2020). DOI:https://doi.org/10.24018/ejece.2020.4.4.238.

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 Adel Elgammal
 Google Scholar |   EJECE Journal
 Miguel Jagessar
 Google Scholar |   EJECE Journal