Data Driven Building Thermal Modeling Using System Identification For Hybrid Systems
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Data-driven Building Thermal Modeling Using System Identification for Hybrid Systems
The building sector is a major energy consumer, therefore, a framework of actions has been decided on by countries worldwide to limit its impact. For implementing such actions, the availability of models providing an accurate description of the thermal behavior of buildings is essential. For this purpose, this thesis proposes the application of a new data-driven technique for modeling the thermal behavior of buildings based on a hybrid system approach. Hybrid systems exhibit both continuous and discrete dynamics. This choice is motivated by the fact that a building is a complex system characterized by nonlinear phenomena and the occurrence of different events. We use a PieceWise AutoRegressive eXogeneous inputs (PWARX) model for the identification of hybrid systems. It is a collection of sub-models where each sub-model is an ARX equation representing a certain configuration in the building characterized by its own dynamics. This thesis starts with a state-of-the-art on building thermal modeling. Then, the choice of a hybrid system approach is motivated by a mathematical interpretation based on the equations derived from an RC thermal circuit of a building zone. This is followed by a brief background about hybrid system identification and a detailed description of the PWARX methodology. For the prediction phase, it is shown how to use the Support Vector Machine (SVM) technique to classify new data to the right sub-model. Then, it is shown how to integrate these models in a hybrid control loop to estimate the gain in the energy performance for a building after insulation work. The performance of the proposed technique is validated using data collected from various test cases.
Data-driven Analytics for Sustainable Buildings and Cities
This book explores the interdisciplinary and transdisciplinary fields of energy systems, occupant behavior, thermal comfort, air quality and economic modelling across levels of building, communities and cities, through various data analytical approaches. It highlights the complex interplay of heating/cooling, ventilation and power systems in different processes, such as design, renovation and operation, for buildings, communities and cities. Methods from classical statistics, machine learning and artificial intelligence are applied into analyses for different building/urban components and systems. Knowledge from this book assists to accelerate sustainability of the society, which would contribute to a prospective improvement through data analysis in the liveability of both built and urban environment. This book targets a broad readership with specific experience and knowledge in data analysis, energy system, built environment and urban planning. As such, it appeals to researchers, graduate students, data scientists, engineers, consultants, urban scientists, investors and policymakers, with interests in energy flexibility, building/city resilience and climate neutrality.
Active Building Energy Systems
This book provides a comprehensive study on state-of-the-art developments in the control, operation, and market participation of active buildings (ABs). Active buildings can support the broader energy system by intelligent integration of renewable-based energy technologies for heating, cooling, electricity, and transport. This important reference analyzes the key features of modern control and operation techniques applied to these systems. Contributions from an international team of experts present practical methods with evidence and case studies from applications to real-world or simulated active buildings. Sample computer codes and analytical examples aid in the understanding of the presented methods. The book will support researchers working on the control and operation of buildings as an energy system, smart cities and smart grids, and microgrids, as well as researchers and developers from the building and energy engineering, economic, and operation research fields. Provides an in-depth review of building-level energy systems technologies; Covers codes, standards, and requirements for active building control systems; Includes sample computer code and analytical examples.