Enhancing on-grid renewable energy systems: Optimal configuration and diverse design strategies

Guodao Zhang, Haijun Zhou, Yisu Ge, Sharafzher M. Magabled, Mohamed Abbas, Xiaotian Pan, Joffin Jose Ponnore, Hamd Asilza, Jian Liu and Yanhong Yang

Renewable Energy, 2024, vol. 235, issue C

Abstract: This study explores the optimization of hybrid renewable energy systems in smart grids, incorporating configurations involving multiple sources such as solar photovoltaic, wind, and combined PV/wind systems with advanced battery storage strategies. The goal is to develop optimal sizing and energy management solutions that not only reduce the grid use factor but also enhance the sustainability and reliability of energy systems through innovative energy-saving methods and carbon-neutral approaches. Utilizing a novel methodology that integrates particle swarm optimization, long short-term memory, and genetic algorithms, this research identifies the most effective mix of renewable energy capacities alongside versatile energy storage solutions, to align energy production with consumption efficiently. The study demonstrates significant environmental benefits, crucial for sustainable management aimed at achieving carbon neutrality, including reducing CO2 emissions by 122.29 tons per year and maintaining a notably low levelized cost of energy at $0.0417/kWh. The model proves accurate in forecasting renewable energy generation, emphasizing its potential as a sustainable and cost-effective alternative to traditional energy sources. These findings underscore the critical importance of integrating optimal hybrid renewable systems that incorporate strategic energy storage, innovative optimization for energy savings, and robust measures towards achieving carbon neutrality, thus enhancing both energy sustainability and economic feasibility.

Keywords: Hybrid renewable energy systems; Smart grids; Solar photovoltaic (PV); Solar PV with batteries; PV/Wind; PSO-LSTM-GA hybrid (search for similar items in EconPapers)
Date: 2024
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Persistent link: https://EconPapers.repec.org/RePEc:eee:renene:v:235:y:2024:i:c:s0960148124011716

DOI: 10.1016/j.renene.2024.121103

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