OPTIMUM SIZING AND ALLOCATION OF PV SYSTEMS FOR IMPROVING THE PERFORMANCE OF ELECTRICAL NETWORK – CASE STUDY NEDCO
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Date
2024-09-30
Authors
Breik, Omar
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Publisher
An-Najah National University
Abstract
Distribution networks may be affected if distribution generation is integrated into an existing system without a comprehensive network analysis since electrical systems are not built to support power generation sources at the distribution level. There may be an impact on voltage levels, current flow and protection coordination. Hence, the importance of studying the optimal size and location of solar cells in electrical networks.
In this research, the Chaotic Bees Algorithm is used to determine the optimal size and location of solar photovoltaic (PV) systems for integration into electrical distribution networks. Considering that solar energy integration has become an essential energy source, PV deployment needs to be supported by strong standards and research to optimize its benefits.
The traditional Bee algorithm in most studies solves the problem of optimal PV placement and sizing by focusing on minimizing losses while improving voltage stability only on small systems and networks such as the IEEE test system of 33 or 69 busses. We modified the algorithm so that the modified form of the algorithm using chaotic mapping increases the search space and returns better results faster and handles larger networks.
Three scenarios were compared in order to determine how well the distribution network performed: without solar systems, with distributed solar systems on remote and weak buses, and with optimally placed solar systems through both the original and improved Bee algorithm. The improved algorithm proved its efficacy, as it was able to improve the network performance significantly and thus provide optimal solutions.
the algorithm was applied to a more significant part of the Nablus network, which included 247 connection points and 213 transformers, based on information from operational engineer we considering a load factor 0.4 and a power factor 0.95 of the transformers because we don’t have measured data in all the 213 transformers.
This study was done with the help of the Python programming language and Jupyter Notebook for the implementation of the algorithm and analysis of the network. The results confirm that the developed algorithm finds the optimal locations and sizes of PV systems to improve the efficiency and stability of the electrical network with higher quality and speed compared to the traditional algorithm.