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

Multi‐objective optimization of photovoltaic/wind/biomass/battery‐based grid‐integrated hybrid renewable energy system
Multi‐objective optimization of photovoltaic/wind/biomass/battery‐based grid‐integrated hybrid renewable energy system
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.
1752-1416
1528-1541
Pavankumar, Yadala
5cd41b9c-57cc-4ac1-b36d-4143d5d1a81b
Kollu, Ravindra
b008947a-9d73-4f39-adb2-09406ea260fc
Debnath, Sudipta
78351e14-b824-4d90-8e9f-4c2f7bd51d89
Pavankumar, Yadala
5cd41b9c-57cc-4ac1-b36d-4143d5d1a81b
Kollu, Ravindra
b008947a-9d73-4f39-adb2-09406ea260fc
Debnath, Sudipta
78351e14-b824-4d90-8e9f-4c2f7bd51d89

Pavankumar, Yadala, Kollu, Ravindra and Debnath, Sudipta (2021) Multi‐objective optimization of photovoltaic/wind/biomass/battery‐based grid‐integrated hybrid renewable energy system. IET Renewable Power Generation, 15 (7), 1528-1541. (doi:10.1049/rpg2.12131).

Record type: Article

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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IET Renewable Power Gen - 2021 - Pavankumar - Multi‐objective optimization of photovoltaic wind biomass battery‐based - Version of Record
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More information

Accepted/In Press date: 21 January 2021
e-pub ahead of print date: 16 March 2021
Published date: 23 April 2021

Identifiers

Local EPrints ID: 499149
URI: http://eprints.soton.ac.uk/id/eprint/499149
ISSN: 1752-1416
PURE UUID: 4514fd6c-b019-47f7-a480-7cdb3d05e9e3
ORCID for Yadala Pavankumar: ORCID iD orcid.org/0000-0001-9211-8337

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Date deposited: 11 Mar 2025 17:30
Last modified: 22 Aug 2025 02:45

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Contributors

Author: Yadala Pavankumar ORCID iD
Author: Ravindra Kollu
Author: Sudipta Debnath

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