Stochastic demand side management in smart grid system

Abstract

Two-way communication of smart grid allows customer to see their energy consumption in demand side, and makes the energy supplier informed to manage economic dispatch based on load demand variability. Statistical analysis of demand-side management gives us the fitness of hourly load demand with proposed probability density functions. We proposed Lognormal, Gamma and Weibull probability density function for estimating the load demand variability at Banaras Hindu University (BHU) campus. We have collected the hourly load demand data of BHU campus for a year from the Electricity & Water Supply Service Center, BHU. The fitness of data with theoretical probability density function has been analysed with three goodness-of-fit tests named Kolmogorov-Smirnov, Anderson-Darling, and Cramer-von Mises tests. Modern R programming language software has been used for the computational work and graphical analysis. With this, we can manage optimal power flow between demand and supply to increase the system reliability. Copyright © 2019 Inderscience Enterprises Ltd.