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The Future of Rural Power
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Our research, as developed in this book, focuses on finding the optimal design and size for a hybrid renewable energy system. This system aims to be a successful and ideal solution for providing electrical power to remote rural areas, whether mountainous or desert. By utilizing photovoltaic systems and wind turbines, the two most important and efficient alternative energy sources, the hybrid system is poised to effectively address the energy needs of these regions. The assembly of these hybrid components in electrical systems requires optimization in design and sizing to minimize the total cost while meeting the energy demands of the loads. Therefore, the main objective of this work is to develop a new and efficient methodology for the optimal design of renewable hybrid systems that ensures low cost and reasonable project lifetime. To achieve this, we used two new algorithms, SOS (Symbiotic Organisms Search) and SFS (Stochastic Fractal Search), to determine the optimal size of the system components, taking into account all economic and technical constraints. Through this approach, we integrated a robust energy management strategy into the hybrid system design.
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Our research, as developed in this book, focuses on finding the optimal design and size for a hybrid renewable energy system. This system aims to be a successful and ideal solution for providing electrical power to remote rural areas, whether mountainous or desert. By utilizing photovoltaic systems and wind turbines, the two most important and efficient alternative energy sources, the hybrid system is poised to effectively address the energy needs of these regions. The assembly of these hybrid components in electrical systems requires optimization in design and sizing to minimize the total cost while meeting the energy demands of the loads. Therefore, the main objective of this work is to develop a new and efficient methodology for the optimal design of renewable hybrid systems that ensures low cost and reasonable project lifetime. To achieve this, we used two new algorithms, SOS (Symbiotic Organisms Search) and SFS (Stochastic Fractal Search), to determine the optimal size of the system components, taking into account all economic and technical constraints. Through this approach, we integrated a robust energy management strategy into the hybrid system design.
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