Predicting solar power potential via an enhanced ANN through the evolution of cub to predator (ECP) optimization technique

Nasab, Morteza Azimi; Zand, Mohammad; Miri, Mohsen; Sanjeevikumar, P.; Guerrero, Josep M.; Saket, R. K.; Khan, Bassem

doi:10.1007/s00202-024-02302-1

Electr Eng

2024

DOI: 10.1007/s00202-024-02302-1

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Predicting solar power potential via an enhanced ANN through the evolution of cub to predator (ECP) optimization technique

Morteza Azimi Nasab,

Mohammad Zand,

Mohsen Miri

et al.

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2024

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Cited by 2 publications

References 34 publications

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Artificial intelligence modeling for power system planning

Knežević,

Žarković

2024

Electr Eng

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Artificial intelligence modeling for power system planning

Knežević,

Žarković

2024

Electr Eng

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Development of wind and solar systems for power charging: An application of an electric vehicle to grid systems

Soomro,

Shaikh,

Baloch

et al. 2024

AIMSE

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<abstract> <p>In response to escalating environmental concerns driven by greenhouse gas emissions, Pakistan, amid accelerated climate change and deteriorating air quality, struggles with power crisis. Our purpose of this research was to develop a pivotal strategy to address the power crisis and provide clean transportation facilities by involving power transitioning from fossil fuel vehicles to electric vehicles (EVs). We aimed to establish EV charging stations powered by renewable sources like solar and wind energy using grid to vehicle (V2G) mechanism. Utilizing MATLAB Simulink, an optimal electric vehicle charging system with a Level 2 fast charging mechanism was designed, aiming to significantly reduce greenhouse gas emissions from both the transportation and energy sectors. This framework aligned with global trends in climate change mitigation, providing developing countries like Pakistan with a practical solution. The results indicated a 10-kW, AC power output at 240 V coupled with an ideal 50 kWh EV battery rating, which was achieved for EV charging. The output parameters, including current voltage and power output of solar PV, micro wind, and battery levels, were used before and after the incorporation of a boost converter. Consequently, the application of a boost converter and proportional integral (PI) controller resulted in low overshoot and steady state output parameters of the proposed system. Also, the battery backup helped to optimize the power output for load driven EVs.</p> </abstract>

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Predicting solar power potential via an enhanced ANN through the evolution of cub to predator (ECP) optimization technique

Cited by 2 publications

References 34 publications

Artificial intelligence modeling for power system planning

Artificial intelligence modeling for power system planning

Development of wind and solar systems for power charging: An application of an electric vehicle to grid systems

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