الفهرس | Only 14 pages are availabe for public view |
Abstract In isolated rural regions it is difficult to provide energy to improve the living environment of the people. Finding economical and practical solutions poses significant challenges. An Integrated Renewable Energy System (IRES) can effectively utilize locally available renewable resources to satisfy the diversity of energy and other requirements. The purpose of this study is to design an IRES to “energize” rural areas for varying energy sources and demands. The first part of this thesis presents a comparative study between the gridconnected and the off-grid IRES to match the power requirement of a remote village in rural Egypt. Five scenarios have been suggested to resolve the village energy issue. These include PV/Biomass/Battery IRES, PV/Wind/Battery IRES, Wind/Biomass/Battery IRES, PV/Wind/Biomass/Battery IRES and a gridconnected IRES. The scope of this study is to identify the best feasible selection/option. An optimization model in terms of four parameters has also been applied. These parameters include the Loss of Power Supply Probability (LPSP), the Renewable Energy Fraction (REF), the Waste Energy Fraction (WEF) and economic feasibility. All calculations employed the MATLAB software with the ultimate objective converging to an optimal solution for the sizing problem. The selection of the optimum system was based on maximizing the REF, minimizing the system Total Net Present Cost (TNPC), and the WEF for a specific LPSP. The outcomes of the simulation show that the optimal configuration is obtained for a grid-connected IRES comprising of two biomass power systems, one wind turbine, and two Nickel Iron battery with a REF of 50.05% and a LCOE of 0.0122 $/kWh. The second part of this thesis focuses on developing a grid-connected IRES in such a way to provide uninterrupted energy supply to a village connected to an unreliable grid with a random outage. The grid availability is modeled in this study randomly with the percentage of 100%, 90%, and 80% of total yearly grid operation respectively. The system adopts meta-heuristic optimization using six different optimization techniques to achieve the optimum sizing of the system. In this case, the meta-heuristic algorithm with the best performance and minimal execution time will be directly selected. The optimization techniques included the Particle Swarm Optimization (PSO), the Flower Pollination Algorithm (FPA), the Harmony Search (HS) algorithm, the Artificial Bee Colony (ABC) Algorithm, the Fire-fly Algorithm (FA) and Hybrid Fire-Fly/Harmony Search Algorithm (HFA/HS). The simulation results show that the Hybrid Fire-Fly/Harmony Search Algorithm has the minimum execution time and best performance among the other algorithms. Three different battery technologies, including Flooded lead-acid (FLA), Lithium Ferro Phosphate (LFP) and Nickel Iron (Ni-Fe) have been considered in this study. Our study suggests that the Nickel Iron battery worth consideration in renewable applications. |