Real-life implementation of a linear model predictive control in a building energy system

Abstract

Recent legislation on the reduction of carbon dioxide emission encourages the improvement of building energy systems’ efficiency as well as minimizing the usage of primary energy resources and damaging impacts on the environment. This fact has attracted the attention of energy system engineers to the importance of developing control strategies to use energy resources more efficiently. Moreover, the development of new energy efficient components and complex energy concepts in last decades has heightened the need to design advanced control strategies to reach the full potential of the recently-developed complex energy systems even more. The objectives of the advanced control strategies that have been developed to be energy efficient are obtained from energy analysis. However, an energy analysis is unable to provide information on the quality of energy streams flowing through a system. In this study, exergy, which is the maximum available work that can be extracted from a system during a process that brings the system into equilibrium with its environment, is considered as the objective of the optimization. The main objective of this research is to develop an exergy-based control strategy for building energy systems and investigate its applicability in real life. The control strategy is supposed to regulate a building energy system in a way that the most exergy efficient operation of the system in question is achieved. To reach this goal, a Model Predictive Control (MPC) for building energy systems using the exergy principles is developed. Model predictive control, which uses a system model to predict the future states of the system, offers a promising solution to the need for more advanced control strategies for complex building energy systems. In order to keep the calculation times as short as possible, the approach of Mixed Integer Linear Programming (MILP) is used in the development of model predictive controller. To demonstrate the functionality of the linear model predictive controller, it is implemented in a building energy system. The use case of this research is the energy supply system of the E.ON Energy Research Center's main building in Aachen, Germany. During an experiment, the exergy-based mixed integer linear MPC made meaningful decisions and demonstrated that it is able to control the forward flow temperature of the energy system with only minor deviations from the specified set point range.