On Efficient Modeling, Simulation and Control of District Energy Systems

Abstract: Sustainable energy systems rely on a wide range of energy sources, where an integral part is to use the available energy as efficiently as possible. District energy systems are considered a key factor as an efficient way of distributing heat and cold within urban areas and facilitating the utilization of renewable energy sources and heat recovery from, e.g., industrial plants and data centers.To achieve high-performing control and an increased understanding of the district energy system, a dynamic model of the process can be used. However, a city-scale, automatically generated, and updated model that can be used for the whole lifecycle of the plant remains a challenging problem. Large-scale physics-based models are sometimes used for planning and validation, but using the models for optimization and control, long-term simulation, or running a high number of simulation scenarios can be computationally prohibitive. In the thesis, the physics of the district energy grid is presented along with modeling, simulation, and control methods with the goal of increasing the computational efficiency and flexibility of the methods. The grid is described using graph theoretical concepts and a linear parameter-varying state-space model representation, along with an introduction to reduced-order models, heat load prediction, Gaussian process models, and feedback control for district energy systems. The main contribution of the thesis is the seven papers. Experiences, challenges, and possible methods to address the presented problems are given in the first paper of the thesis. In the second paper a method for the prediction of heat load for buildings is presented, followed by a machine learning-based method of modeling the thermal dynamics in a district heating pipe. Next, a method for reduced order modeling of district energy grids using graph theoretical methods and spectral clustering is presented in two papers. The sixth paper suggests an integrated approach to spatial and energy planning using an optimization-based tool, and the final paper presents a method for decentralized temperature control in district heating networks using dead time compensation.Based on the work in the thesis, conclusions and suggestions for future research direction are given. 

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