Multi-objective optimization of photovoltaic/wind/biomass/battery-based grid-integrated hybrid renewable energy system

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Abstract

The variable nature of the renewable energy resources (RES) complicates their modelling, operation, and integration to the grid. Therefore, it is difficult to choose optimal RES with a proper energy storage system (ESS) for the economic and reliable operation of the grid-integrated hybrid renewable energy system (HRES). There is a need to solve this optimal HRES problem using efficient algorithms due to the high cost and model complexity involved. In this study, optimal photovoltaic, wind, biomass, and battery-based grid-integrated HRES is proposed using a multi-objective artificial cooperative search algorithm (MOACS) to minimise annual life cycle costing and loss of power supply probability. ESS is chosen to provide a backup power supply for at least 30 min during peak load condition. A probabilistic approach is used to consider the time-varying nature of the RES and load while solving optimal HRES design problem by employing MOACS. A comparative analysis is provided at the end, which shows that MOACS can provide a better optimal design of HRES.

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APA

Pavankumar, Y., Kollu, R., & Debnath, S. (2021). Multi-objective optimization of photovoltaic/wind/biomass/battery-based grid-integrated hybrid renewable energy system. IET Renewable Power Generation, 15(7), 1528–1541. https://doi.org/10.1049/rpg2.12131

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