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Reliability analysis of the distribution network due to the integration of distributed generations

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Reliability analysis is critical to power system design and planning, ensuring that electrical networks operate efficiently under defined conditions over a specified period. The growing integration of Distributed Generation (DG) units, driven by advancements in renewable energy technologies such as solar photovoltaic (PV) and wind energy systems, has significantly impacted power distribution networks. DG units, which are small-scale power generation sources, can be connected at distribution substations or dispersed throughout the network. Their implementation influences voltage profiles and reduces power losses, but their increasing penetration levels also affect overall system operation. This study evaluates the reliability of a distribution network with and without DG integration. A numerical model is developed to analyse the impact of DG integration on network performance. The IEEE 30-bus system is the test network, incorporating solar PV and wind energy conversion systems as DG sources. Numeral Simulations are conducted, implemented on the MATLAB/Simulink software. The Newton-Raphson method is employed for load flow analysis, determining the network's voltage magnitudes and phase angles. Additionally, the Particle Swarm Optimization (PSO) algorithm is utilised to determine the optimal placement of DGs, aiming to minimise power losses, reduce operational costs, and improve voltage stability under various conditions. A reliability assessment is performed using Monte Carlo simulation, which calculates key reliability indices to evaluate system performance. The results confirm that the location and capacity of DG units significantly influence network reliability. The study establishes that integrating optimally placed DGs enhances power system reliability by improving voltage stability and reducing power losses. These findings highlight the potential benefits of renewable energy-based DGs in strengthening distribution networks and ensuring a more stable and resilient power supply.

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A dissertation submitted in fulfilment of the requirements for the Master of Engineering: Power Engineering, Durban University of Technology, Durban, South Africa, 2025.

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https://doi.org/10.51415/10321/6382