In the modern grid era, solar photovoltaic (PV) microgrid systems are suitable for electrifying areas without access to electricity and mitigating power reliability. However, obtaining accurate solar cell parameters, generating maximum power point tracking, and optimizing energy production are significant challenges. Therefore, this dissertation focuses on modeling an AC-coupled, semi-autonomous PV microgrid system to reduce planning costs and increase efficiency. As a result, the following are the main contributions of this study: Modeling of a single-diode parameter extraction of PV cell models using the Newton-Raphson method in conjunction with the particle swarm optimization (PSO) algorithm, which accurately estimates the roots of the nonlinear characteristic equation. Another input is the simulation of a new modified particle swarm optimization (MPSO)-based maximum power point tracking. The proposed modeling is an improved version of the standard PSO algorithm that addresses the limitations, such as random number assignment of acceleration factors and constant weights. The proposed maximum power point method is more adaptable and straightforward than perturb and observe (P&O), the cuckoo search algorithm, and standard PSO. This dissertation also investigates the techno-economic potential of a predominantly renewable electricity-based microgrid serving residential real estate buildings in Ethiopia, the fastest-growing sector of the economy. The modeling of energy management techniques provides the energy share of microgrid components with load response. Indeed, the results indicate that the proposed system is the most cost-effective, environmentally friendly, and reliable. In addition, these findings can help to develop rules for residential complexes and industrial villages to generate their own electricity needs, distribute their existing grid energy share to other underserved areas, and reduce the issue of power outages. All findings were obtained via simulation using HOMER, ETAP, and MATLAB/Simulink software. Thus, the system could be a benchmark for new roof-mounted solar-based technology for residential complexes in developing nations, creating a healthy and competitive energy industry, and optimizing energy asset efficiency. Keywords: Energy management, Maximum power point tracking, PV cell parameter extraction, Reliability, and Microgrid.