Open AccessA Novel Residential Energy Management System Based on Sequential Whale Optimization Algorithm and Fuzzy Logic
Author(s) -
S. Nethravathi,
Venkatakirthiga Murali
Publication year - 2021
Publication title -
distributed generation and alternative energy journal
Language(s) - English
Resource type - Journals
eISSN - 2156-3306
pISSN - 2156-6550
DOI - 10.13052/dgaej2156-3306.3739
Subject(s) - computer science , smart grid , fuzzy logic , demand management , electricity , energy management , demand side , energy management system , operations research , scheduling (production processes) , environmental economics , operations management , economics , energy (signal processing) , engineering , artificial intelligence , statistics , mathematics , electrical engineering , macroeconomics
Demand side management has become inevitable in today’s smart gridenvironment to balance electricity supply and demand. Many methodolo-gies/algorithms have been developed for realizing and implementing thistechnique at different levels of distribution systems. Advanced meteringinfrastructure and the latest communication technologies have empow-ered residential consumers to participate in the demand side managementschemes. After careful investigations and analyses, the authors of this paperhave made a decisive effort to propose a novel sequential strategy for devel-oping an energy management system for scheduling loads of residentialconsumers. The proposed work aims at a fuzzy logic and an evolutionaryalgorithm-based approach of demand side management that considers theusers’ preference of operating time of the appliances at the residence of theirchoice, which has not been addressed earlier. This approach reduces the peakdemand and cuts the cost of electricity per billing period for a consumer. This study also encourages the consumers to install solar rooftop PV systemsby indicating the cost benets reaped over a more extended period. Theproposed framework is implemented in MATLAB, and the case studies provethe effectiveness of using this algorithm from the consumers’ perspective