The adoption of power supply systems powered by renewable energy sources is growing these days as a result of the problems associated with economic, environmental and depletion of conventional energy sources. The main issue with the renewable energy power supply system is to determine the optimal, reliable, and feasible configuration and the corresponding components of the system. Even though Ethiopia is endowed with abundant renewable energy resources, the electrification rate of the country is very low, and there is no general framework that is used for the development of a renewablebased off-grid power supply system for rural electrification. Therefore, the main aim of this study is to develop a general framework for the optimal size of a renewable-based off-grid power supply system for rural communities. The power generated from the photovoltaic module is directly related to the magnitude of total incident solar radiation on the surface of the solar module. In this dissertation, generic models were developed that determine the seasonal and annual optimal tilt angle of the Photovoltaic module at any location in Ethiopia without using meteorological data. Both isotropic and anisotropic diffused solar radiation models were used to estimate monthly, seasonal, and annual optimal tilt angles. The monthly average daily global horizontal solar radiation for a total of 44 cities -32 for developing the models and 12 for testing were obtained from the National Aeronautical and Space Administration database, and algorithms were developed and implemented using MATLAB and R programming software to obtain optimum tilt angle and regression models. The study showed that the developed model accurately estimates the optimal tilt angle with the minimum statistical validation errors. It is also found that 5.1% to 6.3% (isotropic) and 5.7% to 6.3% (anisotropic models) solar radiation energy is lost when using the yearly average fixed optimal tilt angle as compared with the monthly optimal tilt angle. The developed optimal tilt angle models were validated by comparing them with previously published works, PVGIS, and PVWatt online software. The electricity demand is highly stochastic and unpredictable. A good load model is one of the main inputs for the design of an economical and reliable renewable-based rural electrification system for rural communities and demand management systems. This study presents a generic methodology for determining a rural community’s energy consumption load profile, which is used to determine the most cost-effective size of the renewable-based off-grid power supply system for rural electrification purposes. To determine the load profile parameters, such as the types of appliances used, their functioning times, functioning windows, and expected minimum and maximum cycle time, a field survey was conducted in four rural electrified Ethiopian villages. Since the survey findings will not fully explain the stochastic nature of the load profile, the load parameters are randomly generated, and a bottom-up approach is used to estimate the rural community’s energy usage. A MATLAB program is developed and implemented to obtain the load profiles of different customer groups. The results of this study are assessed per the multi-tier criterion and verified using the use of the well-known software HOMER Pro and LoadProGen. The zebra optimization algorithm (ZOA), a recently developed meta-heuristic optimization algorithm, has been used to perform the techno-economic performance analysis and optimal sizing of the renewable-based off-grid power supply system for rural Ethiopian villages. The optimal sizing of the off-grid power supply system is performed to supply synthetically developed load demand that comprises 1243 households, various commercial loads, public institutions, and small industrial loads on Dek Island, which is one of the largest islands in Ethiopia, on Lake Tana. Using the proposed optimal tilt angle model, the maximum solar radiation on the PV module’s surface is determined, leading to the determination of the PV output power. All the off-grid power supply system components are modeled, the objective function is formulated, and the optimization and techno-economic analysis are performed based on the minimum total annual cost of the off-grid system. Three off-grid power supply systems, such as PV-BAT, PV-WTBAT, and WT-BAT, are proposed to evaluate the optimal configuration for the study site at various losses of power supply probabilities (LPSP). The study’s findings showed that the photovoltaic-battery (PV-BAT) system, with an optimal size of 3483.161 kW of PV, 3668 units of storage batteries (11,444.160 kWh), and 2082 kW of converter at 0.044030% LPSP, is the best configuration for electrifying the rural communities of the study site with the minimum annual total cost of 621,736.056 USD and 0.227063 $/kWh COE. It results in a 3.3% annual total cost reduction and a 1.3% unmet load (kWh/year) improvement as compared to the PV-WT-BAT system. The performance of the proposed ZOA in obtaining the optimal size of the renewable-based power supply system for rural communities is evaluated by comparing it with a well-known gray wolf optimization (GWO) and HOMER Pro software, and it was found that the proposed algorithm is relatively best in finding the optimal size of the power supply system at the minimum cost. The standard deviation for ZOA and GWO, respectively, in determining the optimal configuration value for 25 runs is 14.295 and 36.360 for the PV-BAT configuration, indicating that ZOA is more reliable than GWO in determining the optimal size. Furthermore, ZOA yields a 16.76% reduction in the total net present cost when compared to the HOMER software results.