Abstract:
The distribution system is an important part of the total electrical supply system, as it provides
the final link between a utility’s transmission systems and its customers. It typically has tie and
sectionalizing switches whose states determine the topological configuration of the network. The
system configuration affects the efficiency with which the power supplied by the distribution
system is transferred to the load. Based on the configuration selected and other factors, it is
estimated that distribution systems cause a loss of about 5–13% of the total power generated.
Hence power companies are interested in finding the most efficient configuration, the one which
minimizes the real power loss of their three-phase distribution systems. Therefore, power
distribution system need to be reconfigured to minimize distribution losses.
There are various techniques which have been used for network reconfiguration. But because of
the large dimension and the complexity of the problem, no efficient method has been achieved.
One promising solution is the use of artificial intelligence algorithms. In this thesis, genetic
algorithm is used to automate a 21 buses system of Jimma University Main Campus distribution
system. Genetic algorithm based MATLAB codes are developed to select the optimum switch
combination out of the possible candidates and to calculate the load flow analysis for each
combination iteratively. The final optimum scheme is tested on power world simulator software.
Simulation results have shown that by introducing tie line switches and sectional switches, the
loss in Jimma University Power distribution system can be reduced by 24.3 % and a better
system performance can also be achieved
