RECONFIGURATION OF RADIAL DISTRIBUTION NETWORK WITH DISTRIBUTED GENERATION

Abstract

Power companies are interested in finding the most efficient configuration for minimization of real power losses and load balancing among distribution feeders to save the energy and enhance the operational performance of distribution system. Power distribution systems have tie and sectionalizing switches whose states determine the configuration of the network. Reconfiguration of distribution network is achieved through operation of these switches of distribution network. The network reconfiguration problem is usually formulated as a single objective optimization problem with equality and inequality constraints. The network reconfiguration is a complex, combinatorial and non-linear optimization problem. As a result, more efficient approaches are required to handle this combinatorial problem. In recent years, the use of distributed generation (DG) has increased due to the problems of global warming and exhaustion of fossil fuels. DGs are set up in the vicinity of the customer, with the advantage that this decreases transmission/distribution losses. The flow of electric power is uniflow from an upstream to a downstream system in the conventional electric power system. Thus, voltage control of an electric power system postulates the condition of the flow of electric power as uniflow. However, the DG connected to the downstream power system may produce backward flow which is not assumed in conventional systems. In this thesis, therefore, a genetic algorithm (GA) based technique has been proposed for the reconfiguration of electrical distribution networks with DG to minimize the power losses of the system. Constraints on bus voltage magnitudes, line loadings and radial topology of the network have also been taken into consideration. The proposed algorithm is coded using MATLAB. The proposed method has been tested on a 33-bus IEEE distribution system to check its effectiveness and validity. The obtained results reveal that the proposed method is promising in distribution system reconfiguration. This work is to provide a basis for power companies to use it in the reconfiguration of the distribution networks to reduce the operational costs and to enhance the performance of their networks.