Optimal Planning of Electrical Appliance of Residential Units in a Smart Home Network Using Cloud Services

One of the important aspects realizing smart cities is developing homes/buildings and, from energy perspective, designing and implementing an efficient home area management system (HAEMS) vital. To be effective, HAEMS should include various electrical appliances as well local distributed/renewable resources storage systems, with whole a microgrid. However, collecting processing data associated these appliances/resources are challenging in terms required sensors/communication infrastructure computational burden. Thanks to internet-of-things cloud computing technologies, physical requirements for handling have been provided; however, they demand suitable optimization/management schemes. In this article, developed using services increase accuracy speed processing. A protocol proposed that provides optimal schedule day-ahead operation equipment residential homes under welfare indicators. The comprises three layers: (1) sensors generation/storage units, (2) fog nodes, (3) where information processed bilaterally hourly appliances/generation/storage units planned. neural network genetic algorithm (GA) used part program. predict amount workload corresponding users’ requests. Improving load factor economic efficiency considered objective function optimized GA. Numerical studies performed MATLAB platform results compared conventional method.