The paper establishes a method of optimization of voltage profiles and power minimization in the 11kV Emene Injection substation distribution network which belongs to Enugu Electricity Distribution Company (EEDC). The system to be studied is 30 bus radial feeder whose model is created with empirical load flow data recorded at the substation. A first Newton-Raphson type of load flow analysis showed that certain buses (especially buses 9, 11, 12 and 13) experienced a violation of voltage, making reactive power compensation on the system mandatory, as well as system reinforcement. In order to mitigate such problems, a Genetic Algorithm (GA) was used to size and to determine optimal locations of the Distributed Generation (DG) units in the network. The objective of the GA-based optimization was a reduction in the losses; therefore, this scheme concentrated on the power factor and the voltage deviation profit as its fitness measure. The MATLAB/Simulink was utilized to simulate the optimized DG schemes. It was found that there were significant improvements in the voltage profiles at buses which were earlier faulty and the voltages were reduced to within the acceptable range of 0.95-1.05 p.u. These reasons include the reduced power losses, improved voltage stability and the system performance due to integration of DG. The novelty of work approves the power of evolutionary methods in smart optimization of a power distribution network and provides applicable information on the enhancement of power quality in the same kind of power systems which are under development.
Ikenna Chuddy Mbamalu (Tue,) studied this question.
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