Data-Driven Demand Side Orchestration in a Smart Grid Environment

Abstract

The quest for meaningful living in the area of electricity usage seeks to optimize electricity usage and supply by controlling the shape of consumption via data-based energy management techniques. This leads to electricity market price forecasting for the market participants in the given present varying electric power supply with customers high energy demand. In this research, the smart meter data is concomitantly used to generate useful data for settling forces of demand and supply of electric power. The Bernoulli and Binomial distribution models are used in this paper to determine the activation benchmark function and the demand side classification threshold value. The results show that using smart meter data, maximum control, and energy management efficiency is possible given the limited available power resources and unstable renewable energy sources mainly in African nations.