performance enhancement of power distribution system with optimization strategy

Abstract

newline quotDistributed resources are usually connected close to the load Centre to supply active and reactive power to the power distribution system. Distribution generators technology mainly incorporate solar PV and wind turbines nowadays become trendy for mitigating greenhouse gases. Power system restructuring and technology advancement create more concentration towards DG as an alternative source of electric power connected near the load end to meet the growing demand. It not only helps to reduce the congestion of the existing transmission line but also saves revenue by establishing new infrastructure to meet rising demand. Generation of DG is not centrally planned and centrally dispatched at present, so that DG penetration in the grid poses new challenges and problems to the network operators as they can have a significant impact on the system and equipment operation in terms of reliability, power quality, distribution grid efficiency and safety for both customers and electricity suppliers. Placement of these distributed resources across the distribution network changes the line flows and modifies network performance parameters like network losses and voltage profile predominantly. DG and RPC deployment at load buses inject a partial active and reactive power, making the distribution system bidirectional and modified line flows need more detailed analysis to improve network performance parameters. The locations and size of these distributed resources have a strong influence on network losses and power quality. In this thesis, an attempt has been made to present strategies for allocating various distributed resources, including distributed generators and reactive power compensators, to enhance the distribution network performance and to present a strategy for optimal planning to manage available distributed generators to ensure a consistent distribution system performance on a real-time basis. The generation of these DGs depends upon environmental conditions that are hard to predict and make demand-side ma