Minimizing Losses on Distribution System by PV and Compensating Capacitors

Document Type : Full-length article


1 Faculty of Energy and Environmental Engineering, The British University in Egypt, Cairo, Egypt

2 Faculty of Engineering, The British University in Egypt, Cairo, Egypt

3 Faculty of Engineering, British university in Egypt, Cairo, Egypt

4 Department of Electrical Engineering, Ain Shams University, Cairo, Egypt

5 Renewable Energy Engineering Dept., Faculty of Energy and Environmental Engineering, The British University in Egypt. Electrical Power and machine Dept., Faulty of Engineering, Ain Shams University.


Electric power has become an essential measure of the structure of modern society with most of today’s daily activity based on the proposition that the desired electric power constantly exists.
In The Electrical Distribution System (EDS), each component is essential to the process of distributing power from the site where it is generated then supplied to the customer who utilizes it. Distribution system plays an utmost role in providing the electrical energy from its generation point to the consumers’ end by the use of transmission system. Since the R/X -Where R is the Resistance and X denotes for the impedance- ratio in the distribution network is high, the losses in the distribution system is more. The DGs employed in this work is a mix of Photovoltaic panels (PVs) for active power compensation and capacitors for reactive power compensation. Location, range and type of capacitors used in the system manipulate the amount of compensation provided by the capacitors. To decide the location and size of the DGs, a load flow will be used and losses in the radial network are considered.
The backward-forward sweep load flow technique is used on the IEEE 69 bus standard network. Also, the Genetic algorithm, antlion technique and Cuckoo search algorithm (CS) are used as optimization techniques. The results are tested on the IEEE 69-bus standard test network to validate the proposed algorithms. The proposed algorithms showed enhanced results compared to the genetic algorithms.


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