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Planning and optimization of the renewable-energy-based micro-grid for rural electrification
Author(s)
Mojela, Nteka Maletsie
Date Issued
2026
Type
doctoral thesis
Publisher
Cape Peninsula University of Technology
Abstract
Microgrid systems are a sustainable, technically feasible alternative to grid extension, and for off-grid, energy-impoverished communities, rural electrification serves as an equity-in-energy access reduction effort and a means to evolve supply reliability to ensure greater renewable penetration. This dissertation evaluates planning, modelling, and optimization for microgridbased rural electrification as a reliable, cost-effective approach compared to traditional grid extension methods. Through an expansive review of contemporary literature, the increasingly feasible and applicable advancements support microgrids within modern power systems as a means of reducing operational costs, minimizing technical losses, and accommodating shifting energy needs. The microgrid set up for this dissertation is constructed on realistic operational definitions, empirically established cost functions, and anticipated technical considerations for distributed energy resources, solar systems, wind turbines, and battery storage. The general goal of the study is to present operational cost functions for each energy component, using relevant cost-of-operations realities to better inform microgrid-based rural electrification planning. Thus, this dissertation develops a microgrid-based rural electrification approach and assesses the impacts of various established optimization methodologies within a renewabledriven microgrid context. Furthermore, new methodologies emerge; one offers an innovative Dynamic Arithmetic Optimization Algorithm, assessed for microgrid energy management using expected information gain from MATLAB simulations for empirical validation. Scheduling alternative approaches emerge through the development and subsequent validation of Linear Programming and Grey Wolf Optimization. The Dynamic Arithmetic Optimization Algorithm (DAOA) is employed to minimize the microgrid’s total operating cost by intelligently coordinating renewable power generation, battery charging and discharging, and interaction. Its dynamic arithmetic operators enable the algorithm to respond flexibly to fluctuating resource availability, resulting in more adaptive search patterns than classical AOA and other metaheuristics. Through this implementation, the study evaluates DAOA's performance relative to LP and GWO, providing insights into the algorithm’s dispatch behaviour, cost efficiency, and suitability for renewable-energy-based microgrid applications. By comparing DAOA, LP, and GWO under the same system configurations and constraints, the study provides a clear assessment of each method’s costeffectiveness, stability, and suitability for microgrid management. The case studies presented are implemented and simulated in MATLAB using the DAOA-based optimization framework. According to the simulation results, a fully integrated microgrid yielded the lowest cost of $5,467.56, demonstrating the economic benefits of integrating diverse renewable energy resources with energy storage. The moderate cost for the wind-grid configuration is $6148.10. The highest cost is recorded for the PV-battery configuration at $15411.41, due to solar intermittency and storage capacity limitations. Therefore, the study verifies the efficacy of the DAOA technique for solving microgrid dispatch problems and indicates that resource diversification is a key enabler of cost-efficient, flexible microgrid operation. Dynamic Arithmetic Optimization Algorithms, Linear Programming, and Grey Wolf Optimization are assessed against each other under varying load requirements and renewable generation profiles to better understand their performance. Ultimately, all three algorithms performed successfully, resulting in reduced overall energy costs, improved reliability, and enhanced renewable penetration. Therefore, the results of this dissertation support the microgrid-based rural electrification approach as a feasible, economically viable means of transforming rural access to electrical power.
Additional information
Thesis (DEng (Electrical Engineering))--Cape Peninsula University of Technology, 2026
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