Design of optimal hybrid power system to provide reliable supply to rural areas of Ethiopia using MATLAB and Homer

Abstract

Integrating different energy resources, like solar PV, wind, and hydro is used to ensure reliable power to the rural community loads. Hybrid power system offers sufficient power supply for the rural villages by providing alternative supply for intermittent nature of renewable energy resource. Hence, intermittency of renewable energy resources is a challenge to electrify the rural community in a sustainable manner with the above sources. Thus, efficient resources management is a reasonable choice for intermittent renewable energy resources. The majority of rural villages in Ethiopia are suffering from lack of electricity. This causes deforestation, travel for long distance to fetch water, and no good social services, like clinic and schools, sufficiently. Therefore, the objective of this study was to maximize reliability of power supply by renewable energy sources. Data on wind speed and solar radiation are obtained from the NASA surface meteorological agency. While hydro data are obtained from physical measurements. Different configuration options are considered by Homer software to find the optimal configuration of hybrid system. The optimal configuration system is selected and hybrid components are sized. The optimal hybrid system consists of solar PV, wind, and hydro to supply a community load with a share of 13%, 52%, and 35% respectively. The fuzzy logic controller is designed to manage the intermittent nature of energies. Hence, the demand and energy sources are unpredictable; intelligent control system is important to manage the system accordingly. The control system is designed in MATALAB software. The result obtained from resource combination shows demand and supply are balanced. From the Twelve probabilistic combinations of demand and energy sources, one of the combinations shows that when 7.5 kW is demanded, the power generated/output from hybrid system is 10 kW which is greater than demand. To satisfy 7.5 kW demand control system takes 4.25 kW, 2.75 kW, and 1.08 kW share from wind, hydro, and solar sources respectively. The fuzzy logic control system is designed, to monitor the resource availability and load demand. This controller was managing the demand and the available resources according to the rule.

Optimization of a hybrid renewable energy system for a rural community using PSO

“…Given an optimal HRES, the intermittency of the renewable energy sources remains to be a challenge in electrifying the rural community. Nebey introduced creating an efficient resource management system to solve the aforementioned problem, and conditionally manage the system's power demand and supply [8]. Ignat et al examined the use of PSO as the means for the effective energy management of an island microgrid that utilized various renewable energy sources.…”

Providing electricity access for unelectrified people in remote areas: demonstrated to a case study in Libya

“…Depending on the user's requirements, the user may compare several design options based on their technical and economic advantages as determined by the simulation results. HOMER can simulate both on-grid and off-grid micro power systems that serve electrical loads (Nebey, 2021). HOMER affects energy systems, visualizes cost-effective system designs, and performs sensitivity analysis.…”

Simulation and Analysis Approaches to Microgrid Systems Design: Emerging Trends and Sustainability Framework Application

“…Planning Dimension Software/Technique Technical and economic design, modelling and performance analysis of microgrid systems based on renewable and non-renewable resources and storage TE MILP [10]; HOMER/ANN-BP and LM [11]; optimal and sensitivity analysis [13]; HOMER/comparative analysis [14,15]; MANGO [16]; HOMER/integrated analysis [18]; modified non-dominated sorting GA [19]; MATLAB/MILP [20]; mixed integer MOO [22]; GA [23]; HOMER [24]; Monte Carlo simulation [25]; HOMER/PSO [26]; HOMER/TOPSIS [27]; HOMER/MATLAB [28]; GA [32]; HOMER/MATLAB [33]; HOMER/MATLAB/DSM [34]; HOHER RETScreen [35]; CPLEX [37], MATLAB/MPM-GAMS [40]; MOO [42] Technical, economic and environmental design, simulation and performance analysis of microgrid system with storage TEE MILP [10]; Eco-SIM [31]; RETScreen [36]; AHP-MCDM [38] Social, technical and economic design, modelling and analysis of microgrid systems STE GA, PSO and TLBO [12]; DIgSILENT PowerFactory, HOMER/integrated analysis [21] Technical design, modelling and performance analysis of microgrid systems T GA and Python optimal control problem [29]; MOO and MCDM [30]; fuzzy logic control strategy [39]; MATLAB Simulink/agent-based model [41]; MATLAB and HOMER [43], IoT-based approach [44] The study introduces a practical simulation framework for sustainable energy planning, which is based on the social-technical-economic-environmental-policy (STEEP) model. This model is comprehensive than the other models such as TE, ST, STE, TEE or T planning dimensions.…”