Performance analysis of a grid-connected PV system in LV distribution network

Over the past decade, the growing demand of Grid-connected photo voltaic (GCPV) system has been increasing due to an extensive use of renewable energy technologies for sustainable power generation and distribution. High-penetrated GCPV systems enhance the operation of the network by improving the voltage levels and reducing the active power losses along the length of the feeder. This paper aims to investigate the voltage variations and Total Harmonic Distortion (THD) of a typical GCPV system modelled in Power system simulator, PSS SINCAL with the change of level of PV integrations in a Low Voltage (LV) distribution network. Five different case studies are considered to investigate the impact of PV integrations on LV nodes and the corresponding voltage variations and harmonics. In addition, this paper also explores and benchmarks the voltage improvement techniques by implementing On Load Tap Changer (OLTC) with respective to the main transformer and addition of Shunt Capacitor (SC) at appropriate node points in LV network,

Distributed generation capacity planning for distribution networks to minimize energy loss: an unbalanced multi-phase optimal power flow based approach

This chapter presents an unbalanced multi-phase optimal power flow (UMOPF) based planning approach to determine the optimum capacities of multiple distributed generation units in a distribution network. An adaptive weight particle swarm optimization algorithm is used to find the global optimum solution. To increase the efficiency of the proposed scheme, a co-simulation platform is developed. Since the proposed method is mainly based on the cost optimization, variations in loads and uncertainties within DG units are also taken into account to perform the analysis. An IEEE 123 node distribution system is used as a test distribution network which is unbalanced and multi-phase in nature, for the validation of the proposed scheme. The superiority of the proposed method is investigated through the comparisons of the results obtained that of a Genetic Algorithm based OPF method. This analysis also shows that the DG capacity planning considering annual load and generation uncertainties outperform the traditional well practised peak-load planning.