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• Established a centralized diesel and solar PV system, which led to the reduction of the operational cost by 38.24% as well as CO 2 emission by 46.05%. • Provided a thorough technical assessment of the grid model as well as environmental implications, inclusive of measurable factors for decision purposes. • Conducted sensitivity studies to determine the optimum grid configuration that can meet varying loading levels and changing fuel costs. • Outlined improvements in the grid system that are in direct correlation with SDG 7, 9, 11, and 13, which emphasize sustainable energy practices. • Built a detailed 75-bus distribution network model in MATLAB/Simulink for accurate estimation of work performance within different situations and analysis of the proposed grid model's technical feasibility and environmental costs, providing clear metrics for decision-making. Electricity consumption expenses take a significant amount of an educational institution's budget. A major part of utility production in Pakistan depends on non-renewable sources of energy, which have a bad impact on the environment, while their production cost is very high. To mitigate these problems at an institutional level, Renewable Energy (RE) should be promoted; this research provides a detailed plan for improving the NUST grid structure for sustainable energy management by 2030. The study improves the location of RE sources, especially solar PV systems, and includes a central Diesel generator (DG) to replace dispersed generators. The research provides a new strategy for the development of the National University of Science and Technology (NUST) grid infrastructure to support sustainable energy management by 2030. It combines central utility-scale solar photovoltaic (PV) systems and distributed generation (DG) systems, unlike the current literature that largely consists of distributed renewable power systems. This research evaluates grid performance by creating a 75-bus distribution network model in MATLAB/Simulink and implementing variations to various scenarios to optimize operational costs at 38.24% and decrease CO 2 emissions by 46.05%. This, together with the use of the HOMER software for both cost and environmental analysis, avails a good model that other institutions experiencing similar characteristics in the power sector can emulate when in pursuit of the optimal, efficient integration of sustainable energy solutions.
Abbasi et al. (Tue,) studied this question.