Tuning of PID Controllers within Building Energy Systems
Aachen / E.ON Energy Research Center, RWTH Aachen University (2017, 2018) [Book, Dissertation / PhD Thesis]
Page(s): 1 Online-Ressource (xviii, 162 Seiten) : Illustrationen, Diagramme
Within this thesis, an extended PID auto-tuning algorithm for HVAC systems and building energy systems using the advances in computational power in recent years that is easily applicable to all state-of-the-art building energy management systems and building automation and control systems through the use of cloud-based services and standardized communication protocols is developed and demonstrated.The algorithm is derived based on a review of theory and related work. A simulation study investigates the main characteristics of the proposed algorithm. Its real-life demonstration takes place in a multifunctional office building during full operation. Conducted in order to enable this research, the thesis presents the extension of the demonstration building’s building automation and control system. On the one hand, the system is equipped with an extensive monitoring system; on the other hand, it is extended with an interface system that turns it towards a system that is able to interact with an IP-connected, thus cloud-like, server infrastructure.The major contributions of this thesis are an innovative PID tuning algorithm, its general configuration suggestions for application within different types of control loops and its demonstration. Its applicability is proved and demonstrated within a simulaton study and real-life experiments. The results for a classical real-life building automation systemand different classically PID-controlled loops show an amelioration of the tuned systems’ control performance in 68% of the algorithm’s applications. The application of the algorithm leads to control quality improvements of up to 90 %,accounting for both, simulation and field study, following the integral time-weighted absolute error criterion, ITEA and in comparison to a state-of-the-art adaptive auto-tuning method. Additionally, in order to investigate the applicability of alternative control infrastructures as they might occur in future cloud-based building control systems, such control infrastructures are implemented and tuned with the proposed algorithm. Their tuning is far less successful, indicating that data resolution and transmission times are important and should be regarded in future applications. Moreover, a technical structure for cloud-based services towards building operation optimization is proposed and demonstrated with PID control loop tuning as the use case. Finally yet importantly, a real-life demonstration bench for advanced control research as well as a simulation framework for the same purpose are developed.
Fütterer, Johannes Peter