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General Introduction With the growing demand for electrical power driven by population growth, industrial development, and economic expansion, the need for reliable power supply has become increasingly crucial.The research aims to provide valuable insights into the interplay between DG penetration levels, DG types, and system reliability, ultimately contributing to the development of more resilient and efficient distribution networks.The study will consider different types of DG units, including those injecting real power (e.g., photovoltaic, battery, fuel cell) and those injecting both real and reactive power (e.g., synchronous generators, wind power).By employing meta-heuristic optimization techniques, such as Particle Swarm Optimization (PSO) and Gravitational Search Algorithm (GSA), the optimal sizing and siting of DG units will be determined while considering various operational constraints and objectives, including power loss minimization and voltage profile improvement.This thesis aims to investigate the optimal allocation of multiple DG units in radial distribution systems and analyze their impact on system reliability indicators, such as Total Energy Not Supplied (TENS), Average Energy Not Supplied (AENS), and Average System Interruption Duration Index (ASIDI).
General Introduction
With the growing demand for electrical power driven by population growth, industrial development, and economic expansion, the need for reliable power supply has become increasingly crucial. Radial distribution systems are one of the most common network configurations used to deliver electricity from substations to customers. However, these systems are susceptible to power interruptions due to component failures, adversely affecting system reliability and causing substantial economic losses for utilities and consumers a like.
Traditional approaches to mitigate outages in radial networks involve network reconfiguration and the replacement of failed components using tie and sectionalizing switches. However, these methods have limitations, and the integration of distributed generation (DG) units has emerged as a promising solution to enhance system reliability and provide alternative power sources.
Distributed generation refers to small-scale electricity generation units located close to load centers, often utilizing renewable energy sources or combined heat and power systems. The optimal penetration of DG units in radial distribution systems can offer numerous advantages, including improved voltage profiles, reduced power losses, and increased system reliability. However, improper integration of DG units may adversely impact the system's operation and stability.
This thesis aims to investigate the optimal allocation of multiple DG units in radial distribution systems and analyze their impact on system reliability indicators, such as Total Energy Not Supplied (TENS), Average Energy Not Supplied (AENS), and Average System Interruption Duration Index (ASIDI). The study will consider different types of DG units, including those injecting real power (e.g., photovoltaic, battery, fuel cell) and those injecting both real and reactive power (e.g., synchronous generators, wind power).By employing meta-heuristic optimization techniques, such as Particle Swarm Optimization (PSO) and Gravitational Search Algorithm (GSA), the optimal sizing and siting of DG units will be determined while considering various operational constraints and objectives, including power loss minimization and voltage profile improvement.
The research aims to provide valuable insights into the interplay between DG penetration levels, DG types, and system reliability, ultimately contributing to the development of more resilient and efficient distribution networks. The findings of this study will be of significant interest to utility companies, policymakers, and researchers working towards the integration of distributed generation and the enhancement of power system reliability.
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