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Multi-objective evolutionary optimization with genetic algorithm for the design of off-grid PV-wind-battery-diesel system

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Abstract

With the increasing hazard to the environment and progressions in renewable energy technologies, hybrid renewable energy systems can meet the energy demand. Total dependability can be attained by adding battery banks to hybrid systems. This paper aims to optimally design a multi-source grid isolated hybrid generation system for future smart cities in the state of Tamil Nadu, India. This off-grid power generation consists of wind turbine generators, photovoltaic panels, inverters, diesel generators, and batteries. The design intents at minimizing Net Present Cost, Unmet Load, and CO2 emissions which are conventionally contradictory to each other. This paper analyzes the optimal off-grid combination of components and control strategies, utilizing improved Hybrid Optimization using the Genetic Algorithm. The results obtained portrays that a mix of hybrid renewable energy generators at off-grid locations without diesel generators can be a cost-effective choice of new smart cities, and it is sustainable, environmentally viable, and techno-economically feasible. Subvention is imperative to take on the large-scale system due to the high capital cost.

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Abbreviations

\(N_{{{\text{gen}}\_{\text{main}}}}\) :

Number of main algorithm generations

\(N_{{{\text{gen}}_{\text{main}}\_\hbox{max} }}\) :

Maximum number of generations of the main algorithm

\(N_{{{\text{gen}}_{ \sec }}}\) :

Number of generations of the secondary algorithm

\(N_{{{\text{gen}}_{ \sec }\_\hbox{max} }}\) :

Maximum number of secondary algorithm generations

\(N_{\text{non\,dom}}\) :

Tally of non-dominated solutions

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Acknowledgements

We gratefully acknowledge PSNA College of Engineering and Technology, Dindigul, Tamil Nadu, India and Vellore Institute of Technology-Vellore, Tamil Nadu, India for the support provided. We are indebted to Prof. Dr. Rodolfo Dufo-López, Electrical Engineering Department, University of Zaragoza, Spain, who provided insight and expertise that greatly assisted the research.

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Authors and Affiliations

  1. Department of Electrical and Electronics Engineering, PSNA College of Engineering and Technology, Dindigul, Tamil Nadu, India

    Rajendran Joseph Rathish & Krishnan Mahadevan

  2. Department of Manufacturing Engineering, School of Mechanical Engineering, Vellore Institute of Technology, Vellore, Tamil Nadu, India

    Senthil Kumaran Selvaraj

  3. Department of Electronics and Communication Engineering, PSNA College of Engineering and Technology, Dindigul, Tamil Nadu, India

    Jayapalan Booma

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  1. Rajendran Joseph Rathish
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  2. Krishnan Mahadevan
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Correspondence to Rajendran Joseph Rathish.

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Rathish, R.J., Mahadevan, K., Selvaraj, S.K. et al. Multi-objective evolutionary optimization with genetic algorithm for the design of off-grid PV-wind-battery-diesel system. Soft Comput 25, 3175–3194 (2021). https://doi.org/10.1007/s00500-020-05372-y

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