Model Centric Development of Genetic Algorithm Based Optimal Load Scheduler for Smart Home

Abstract

Information/Communication Technologies (ICT) and control has been focal research areas contributing in grid modernization. It enabled the concept of home energy automation solutions by providing control to home assets according to local renewable energy generation and storage systems, providing decentralized control for smart homes also termed as prosumers energy systems. To attain such controls, efficient Demand Side Management (DSM) and Demand Response (DR) approaches are required in energy prosumer units. This paper investigate these efficient approaches by deploying price based DSM as real time Genetic Algorithm based optimal load scheduler. It provides real time control to home appliances according to grid price, renewable energy generation and local energy storage. To develop optimal load scheduler Model Centric Development (MCD) approach is used and simulation environment is established using simulator coupling.