Management in Industrial Sectors using Neuro-Fuzzy Controller and Deep Learning

Abstract

Load forecasting plays a vital role in generation and distribution sectors in the power system. This helps to obtain optimum load scheduling which helps to predict future consumption to increase reliability in the system. The demand side management helps to optimize the consumption of energy based upon the priority of the consumers. The load forecasting helps to predict the usage of power through the priority scheduling of the loads which helps to minimize and maximize the operating cost. The optimization technique plays a versatile role in the load scheduling based on demand side management in the industrial sectors. The combination of advanced technologies with communication infrastructure makes the system more reliable and smarter. The demand side management is achieved through shifting the loads from peak hours to non-peak hours. Thus, to enhance the automatic scheduling of loads in the industrial sector is achieved by the neuro-fuzzy controller and deep learning techniques.