Modular statistical system for an integrated environmental control

¹ Student Research Group Intelligent Integration of Innovations at Faculty of Electrical and Computing Engineering, Cracow University of Technology, Poland
² Associated Professor, D. Sc. Eng., Department of Automatic Control and Information Technology, Faculty of Electrical and Computing Engineering, Cracow University of Technology, Poland
³ Associated Professor, D. Sc. Eng., Department of Traction and Traffic Control, Faculty of Electrical and Computing Engineering, Cracow University of Technology, Poland

^* Corresponding author: a.romanska@pk.edu.pl

Abstract

In this paper series, we will examine the relation between the smart grid and the next generation of buildings. The new objective is now to design buildings so that the energy exchange takes place in time suitable for both sides. The building takes energy from the grid and give it back at different time because in the next generation of buildings they are equipped in advanced control system that controls energy storage for several hours and the new or retrofitted building can eliminate energy peaks and valleys for itself and assist the smart grid in equalization of the load. The control systems include monitoring and modeling of energy use and indoor environment to arrive to a weather-based prediction, Therefore, in part 1 of the paper series we address collecting, processing and analysis of the measurement data that can be done by the new modular statistical software alone or in conjunction with a dedicated neural network. We want to minimize energy use and maximize the thermal comfort of the occupants. Using the modular structure of the database, data transformation technologies and other existing tools, the modular statistical software (MSS) has been created to process large amounts of data as input to the decision-making algorithm. This is to enable buildings automated control (BAC) to take over the control of heating/cooling, ventilation, illumination and other performance aspects that relate to sustainability of built environment.