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Comparative energy scheduling and efficiency analysis of 150kw hybrid micro-grids using ann-pso

• Authors Details :  
• Engr. O. B. Balogun,  
• Associate Prof. C. O. Omeje,  
• Engr. Dr. B. O. Ogbonna

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This study investigated the formulation, implementation, and performance implications of an artificial neural network–particle swarm optimization (ANN–PSO) based energy scheduling framework for a 150kW hybrid micro-grid. The analysis focused on two hybrid configurations, namely micro gas turbine–fuel cell (MGT–FC) and solar photovoltaic–battery storage system (PV–BSS), with emphasis on optimal dispatch behaviour and system efficiency under dynamic load and generation conditions. MATLAB was used to simulate ANN-based forecasting of hourly load and distributed energy resource outputs, which were subsequently optimized using PSO over multiple iterations to achieve balanced supply–demand scheduling. 4-in-1 visualization techniques were employed to capture convergence behaviour, transient response, dispatch stability, and efficiency dynamics across operating scenarios. Results showed that both hybrid systems achieved convergence within 20–24 PSO iterations, with scheduled power maintained within 50–120kW despite injected disturbances of ±20–30kW. The MGT–FC configuration demonstrated smoother dispatch profiles and faster fitness convergence, while the PV–BSS system exhibited greater variability due to intermittency, compensated by storage dispatch. Efficiency analysis revealed that optimal ANN–PSO scheduling sustained MGT–FC efficiency within 83–89%, whereas PV–BSS efficiency ranged between 41–72%, peaking during high-irradiance periods. Overall, the findings established that ANN–PSO-based scheduling enhanced operational stability and efficiency in both configurations, while highlighting the superior resilience of the MGT–FC hybrid under identical dynamic conditions. The study concluded that intelligent optimization provides a viable pathway for improving micro-grid performance in developing communities and industrial off-grid applications, where reliable and efficient decentralized power supply remains critical. It was therefore recommended among others that power system engineers and industrial energy planners in developing economies adopt ANN–PSO frameworks for real-time micro-grid dispatch to improve efficiency, resilience, and adaptability of decentralized energy systems serving communities and industrial loads.

Article Subject Details

• Allied Science
• Basic science
• Computer Science
• Interdisciplinary science
• Materials Science

Article Keywords Details

• ANN–PSO; MGT–FC; PV–BSS; Hybrid micro-grid; Energy scheduling

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