ADVANCED OPTIMIZATION TECHNIQUES AND HYBRID MICROGRID DESIGN FOR SOLAR ENERGY INTEGRATION AND MPPT ENHANCEMENT USING MODIFIED FIREFLY ALGORITHM

Abstract

Present-day, microgrid systems, particularly systems engaging photovoltaic (PV) technologies, are gaining increasing attention as they offer promising solutions for a resilient and sustainable power demand worldwide. Saudi Arabia, with its enormous solar resources, is great positioned to embrace renewable energy alternatives. However, the southern region, particularly Najran Provenience, remains unutilized despite its significant solar potential. This thesis comprehensively investigates the design and sizing of microgrids of this area following enhancing system reliability and optimizing performance using the professional capabilities for the scientific research. The first study examines a grid-connected hybrid microgrid for the Najran Secondary Industrial Institute (NSII) utilizing the Hybrid Optimization of Multiple Energy Resources (HOMER) software. The system integrates PV, battery storage system (BSS), diesel generator (DG) and grid. In this study, the system’s reliability was assessed using the Loss of Power Supply Probability (LPSP). The LPSP was maintained at zero, indicating no unmet load for all scenarios. The design of the grid-connected balances the technological, economic and environmental considerations, insuring the system’s resilience and cost-effectiveness. The second study shifts the focus to an off-grid system. The off-grid solar-powered microgrid interduces a novel approach for sizing the microgrid using a Modified Firefly Algorithm (MFA). This modified algorithm enhances the convergence speed and solution quality which is a significant improvement over the traditional firefly algorithm (FA). The system’s reliability was evaluated under two scenarios, with LPSP values of 0.01 and 0.1. This innovative MFA demonstrated superior performance in optimizing the sizing of the system’s components, particularly in scenarios where reliability is critical. The third study focuses on the impact of partial shading conditions (PSC) on photovoltaic systems and the effectiveness of maximum power point tracking (MPPT) algorithms. A comparative analysis was conducted to evaluate the performance of four MPPT techniques: Perturb and Observe (P&O), Particle Swarm Optimization (PSO), FA, and MFA. The results demonstrate that MFA consistently outperforms the other algorithms in tracking the maximum power point (MPP) under PSCs. Additionally, the study investigates the influence of varying load resistance on the efficiency of MPPT tracking, revealing that MFA exhibits higher adaptability and stability across different conditions. The research findings highlight the importance of employing advanced MPPT techniques to enhance PV system efficiency under challenging environmental conditions. Together, these studies enrich the deployment of renewable energy systems in Saudi Arabia’s southern regions by highlighting the potential of the advance and novel techniques in designing the methodologies of these microgrid. This research, by addressing both grid-connected and off- grid, contributes to the Saudi Arabia’s immense efforts to diversify its energy sources under Vision 2030.