POSSIBILISTIC UNCERTAINTY ASSESSMENT IN THE PRESENCE OF OPTIMALLY INTEGRATED SOLAR PV-DG AND PROBABILISTIC LOAD MODEL IN DISTRIBUTION NETWORK

To integrate network load and line uncertainties in the radial distribution network (RDN), the probabilistic and possibilistic method has been applied. The load uncertainty is considered to vary as Gaussian distribution function whereas line uncertainty is varied at a fixed proportion. A voltage stability index is proposed to assign solar PV-DG optimally followed by application of PSO technique to determine the optimal power rating of DG. Standard IEEE 33- and 69-bus RDN are considered for the analysis. The impact of various uncertainties in the presence of optimally integrated solar PV-DG has been carried out on 69-bus network. The results obtained are superior to fuzzy-arithmetic algorithm. Faster convergence characteristic is obtained and analyzed at different degree of belongingness and realistic load models. The narrower interval width indicates that the observed results are numerically stable. To improve network performance, the technique takes into account long-term changes in the load profile during the planning stage. The significant drop in network power losses, upgraded bus voltage profile and noteworthy energy loss savings are observed due to the introduction of renewable DG. The results are also statistically verified