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Optimizing solar-photovoltaic-distributed energy resources in power networks using ai-based particle swarm optimization (pso) algorithm

• Authors Details :  
• Engr Okpo K. O.,  
• Prof Omorogiuwa E.

131 Views Original Article

This study was conducted to optimize the integration of solar-photovoltaic-distributed energy resources (SPVDERs) within the Nigerian power system networks using an AI-based Particle Swarm Optimization (PSO) Algorithm. By employing a mixed research method, primary and secondary data were gathered to calculate flow analysis, NR method's equations, PSO's position update model, particle swarm optimizer algorithm, and application modeling including Solar-PV DER modeling. The AI-based PSO algorithm design was developed for optimizing SPV-DER integration in Nigerian power system networks, and key parameters and variables that needed consideration were identified. The study also established how the performance of the AI-based PSO algorithm could be evaluated and compared with other optimization techniques for SPV-DER integration within Nigerian power system networks. The study's results showed that voltage limits were within acceptable ranges, and solar power contributions were estimated at 880.10MW with 46,718 panels needed. The study concluded and recommended that investing in AI-powered tools for efficient power distribution; monitoring and resource optimization for sustainable energy sources would optimize performance and unleash Nigeria's sustainable energy potential.

Article Subject Details

• Engineering
• Engineering management

Article Keywords Details

• AI-based
• Algorithm
• Particle Swarm Optimization (PSO)
• power system networks
• Solar-photovoltaic-distributed energy resources

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