Paper Title :Multi-objective Optimization Integrating Artificial Neural Networks: Design and Performance Analysis of a Solar-Powered System for Simultaneous Production of Hydrogen, Electricity, and Heat

Author :Lina Wang

Article Citation :Lina Wang , (2024 ) " Multi-objective Optimization Integrating Artificial Neural Networks: Design and Performance Analysis of a Solar-Powered System for Simultaneous Production of Hydrogen, Electricity, and Heat " , International Journal of Advances in Science, Engineering and Technology(IJASEAT) , pp. 76-79, Volume-12,Issue-4

Abstract : This study presents a novel approach integrating multi-objective optimization techniques withArtificial Neural Networks (ANNs) to design and analyze the performance of a solar-powered system aimed atsimultaneously generating hydrogen, electricity, and heat. The proposed methodology leverages the capability ofANNs to model complex relationships within the system and employs Grey-wolf optimization to achieveoptimal operation. Results demonstrate the effectiveness of the integrated approach, with the ANN achieving high accuracy (0.99997) and the TOPSIS was utilized to select the optimal solution. Moreover, sensitivity analyses highlight the significance of all parameters in influencing system behavior. Keywords - ANN; Multi-Objective Optimization; Grey-Wolf; Solar Energy; Hydrogen Production

Type : Research paper

Published : Volume-12,Issue-4

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