Modelling and optimizing of Battery Energy Storage System (BESS) through an intelligent Building Management System (BMS)
The goal of decarbonizing our energy, calls for the integration of more renewable energy in our energy system. On-site energy generation is becoming more and more the norm for the Dutch buildings. The stochastic nature of renewable energy sources and the limitations of the grid, forces designers to look into demand side management and optimization of energy consumption. To optimize the consumption of the buildings, predicting their energy demand beforehand is valuable.
General project problem description
The project is in collaboration with Kropman one of the largest building services company in the Netherlands, focusing on renewable installations and building performance management. Kropman has been one of the leading forces in the Dutch construction industry towards energy transition and has created a living lab to develop, test, validate and implement new technologies and processes.
The living lab includes, on site energy generation with PVs and energy storage through a Battery Energy Storage System (BESS). An intelligent Building Management System (BMS) is in place to monitors and control different components of the system. Forecasting algorithms are already available to predict the building consumption accurately for the next day, the BESS should therefore be controlled accordingly through the BMS.
The student will be responsible for designing, developing and implementing the BESS models to be optimized in python. The focus of the project is partly the practical implementation of the algorithm to control the BESS. The outcome should be able to be used by Kropman immediately.
