Predictive Controller Based EMS and Techno-Economics of an Electrical-Thermal Community MG

The growing population in cities around the globe creates concerns for issues related to rapid urbanization and changing climatic conditions. To accommodate this large-scale dweller, the concepts of smart buildings and community based sustainable living were started. These two considers application of renewable energy sources (RESs), viz., solar photovoltaic (PV), wind turbines as well as electric vehicles (EVs) to the maximum extent with a backup diesel generator (DG). Most hours of a day is spent by a person staying inside a building (be it residential or workplace), emphasizing the need of creating energy efficient and comfortable living spaces as community buildings. These smart infrastructures consists of various loads like lighting, pumps and motors, cooling and heating, as well as security. Integration of different RESs along with the dedicated loads within community microgrids (CMGs) forms system of systems (SoSs) architecture. This paper presents application of model predictive control for establishing an isolated CMG with optimal sizing of components, and energy management system applying both technical as well as economic aspects. It is verified by including multiple testing and actual operational conditions like time-varying energy output and load changes, storage capacity of batteries, load scheduling coordinated EVs, and minimum fuel consumption.