Efficient real-time optimal power management of large-scale building prosumers

As urbanization accelerates and energy demand increases, buildings continue to be a key contributor to overall energy consumption. Heating and cooling loads, along with the energy needed to produce hot water, contribute almost 60% of the total energy consumption of buildings. Therefore, the need for innovative technologies for smart building energy management systems is more urgent than ever. A method for real-time optimal power management of large-scale building prosumers comprising thermal-electrical loads, electrical loads and plug-in electric vehicles with low computation requirements is proposed in this paper. Thermal and electrical loads are considered flexible, and they are regulated in real time to ensure an economically optimal operation of the building prosumer. The primary goal of the suggested algorithm is to significantly reduce the daily operation cost of the building prosumer while satisfying a wide range of constraints. At the same time effort is paid on achieving power dispatch of the optimal power setpoint in real-time that ensures the highest possible flexibility of building thermal zones and determining the power set-point of the building prosumer and the hosted electric vehicles also in real-time using efficient artificial neural networks.