Distributed Generation Allocation For Power Loss Minimization And Voltage Improvement Of Radial Distribution
Systems Using Genetic Algorithm

Abstract

Numerous advantages attained by integrating Distributed Generation (DG) in distribution systems. These advantages include decreasing power losses and improving voltage profiles. Such benefits can be achieved and enhanced if DGs are optimally sized and located in the systems. This theses presents a distribution generation (DG) allocation strategy to improve node voltage and power loss of radial distribution systems using genetic algorithm (GA). The objective is to minimize active power losses while keep the voltage profiles in the network within specified limit. This approach finds optimal DG active power and optimal OLTC position for tap changing transformer. Also uncertainty in load and generation are considered. Thus, in this work, the load demand at each node and the DG power generation at candidate nodes are considered as a possibilistic variable represented by two different triangular fuzzy number. The simulation results shows that reduction of power loss in distribution system is possible and all node voltages variation can be achieved within the required limit if DG are optimally placed in the system. Induction DG placement into the distribution system also give a better performance from capacitor bank placement. In modern load growth scenario uncertainty load and generation model shows that reduction of power loss in distribution system is possible and all node voltages variation can be achieved within the required limit without violating the thermal limit of the system.