Abstrato

Artificial Neural Network Approach for Load Forecasting in Demand Side Management

S.Devi, N.Ayswarya

To meet the fast growing demand of energy, smart techniques need to be adopted that are in compliance with the environment and energy conservation. In this paper, an autonomous demand-side energy management to encourage users to willingly modify their electricity consumption without compromising with service quality and customer satisfaction using load forecasting. The projected distributed demand side energy management (DSM) strategy gives each consumer an option to simply apply its best response strategy to current electric Load and tariff in the power distribution system. Using NN and ACO technique on load prediction, it is obtained that an area-load based pricing method is beneficial for both electric utility and consumer. Simulation results shows that the proposed approach can maximize load factor and reduce total energy cost as well as user’s daily electricity charges.