Development of a low-tech MPC-algorithm for versatile applications in buildings with thermal activated components

Abstract

Buildings with thermal activated components enable short-term storage of heat and cold with a high level of comfort for the inhabitants. However, a challenge for temperature control is the inertia of the storage mass and the behaviour of conventional control systems during extreme weather events such as long heat periods. Predictive controllers, working with weather forecast data in combination with a simplified building model enable a prediction of the system behaviour in order to manage heating and cooling in an efficient way.Due to the fact, that existing model predictive controller (MPC) follow the principle of higher system intelligence, this work focuses on the most simple design for a MPC. The following scientific study describes the simple respectively low-tech MPC approach, the experimental setup & the simulation in Matlab/Simulink and the comparison with conventional controller solutions. Although the authors use the term low-tech MPC, the proposed solution can be seen as being at the lower bound to a MPC logic and in the classification as a “predictive optimization controller”.The developed algorithm processes solar radiation gains and outside temperature forecasts with building characteristics and calculates a predicted room temperature profile for 48 h into the future. By optimizing the room temperature in relation to the set temperature, a prognosis of the necessary energy demand is possible. The analysis and validation of the algorithm was carried out in a simulated building model with a thermal activated building component (e.g. ceiling/floor-heating). First results show that the developed algorithm is capable of meeting comfort parameters better than conventional controller strategies and therefore useful for various operations in buildings. Possible future extensions can focus on the ideal combination of heating/cooling demand and cost optimization via own PV energy production.