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| Author | : Ana Ionesi |
| Publisher | : |
| Total Pages | : 142 |
| Release | : 2019 |
| Genre | : |
| ISBN | : |
| Author | : Eric Burger |
| Publisher | : |
| Total Pages | : 183 |
| Release | : 2017 |
| Genre | : |
| ISBN | : |
This dissertation presents techniques for the numerical modeling and control of building systems, with an emphasis on thermostatically controlled loads. The primary objective of this work is to address technical challenges related to the management of energy use in commercial and residential buildings. This work is motivated by the need to enhance the performance of building systems and by the potential for aggregated loads to perform load following and regulation ancillary services, thereby enabling the further adoption of intermittent renewable energy generation technologies. To increase the generalizability of the techniques, an emphasis is placed on recursive and adaptive methods which minimize the need for customization to specific buildings and applications. The techniques presented in this dissertation can be divided into two general categories: modeling and control. Modeling techniques encompass the processing of data streams from sensors and the training of numerical models. These models enable us to predict the energy use of a building and of sub-systems, such as a heating, ventilation, and air conditioning (HVAC) unit. Specifically, we first present an ensemble learning method for the short-term forecasting of total electricity demand in buildings. As the deployment of intermittent renewable energy resources continues to rise, the generation of accurate building-level electricity demand forecasts will be valuable to both grid operators and building energy management systems. Second, we present a recursive parameter estimation technique for identifying a thermostatically controlled load (TCL) model that is non-linear in the parameters. For TCLs to perform demand response services in real-time markets, online methods for parameter estimation are needed. Third, we develop a piecewise linear thermal model of a residential building and train the model using data collected from a custom-built thermostat. This model is capable of approximating unmodeled dynamics within a building by learning from sensor data. Control techniques encompass the application of optimal control theory, model predictive control, and convex distributed optimization to TCLs. First, we present the alternative control trajectory (ACT) representation, a novel method for the approximate optimization of non-convex discrete systems. This approach enables the optimal control of a population of non-convex agents using distributed convex optimization techniques. Second, we present a distributed convex optimization algorithm for the control of a TCL population. Experimental results demonstrate the application of this algorithm to the problem of renewable energy generation following. This dissertation contributes to the development of intelligent energy management systems for buildings by presenting a suite of novel and adaptable modeling and control techniques. Applications focus on optimizing the performance of building operations and on facilitating the integration of renewable energy resources.
| Author | : Jan L.M. Hensen |
| Publisher | : Routledge |
| Total Pages | : 772 |
| Release | : 2019-04-24 |
| Genre | : Architecture |
| ISBN | : 0429688547 |
When used appropriately, building performance simulation has the potential to reduce the environmental impact of the built environment, to improve indoor quality and productivity, as well as to facilitate future innovation and technological progress in construction. Since publication of the first edition of Building Performance Simulation for Design and Operation, the discussion has shifted from a focus on software features to a new agenda, which centres on the effectiveness of building performance simulation in building life cycle processes. This new edition provides a unique and comprehensive overview of building performance simulation for the complete building life cycle from conception to demolition, and from a single building to district level. It contains new chapters on building information modelling, occupant behaviour modelling, urban physics modelling, urban building energy modelling and renewable energy systems modelling. This new edition keeps the same chapter structure throughout including learning objectives, chapter summaries and assignments. Moreover, the book: • Provides unique insights into the techniques of building performance modelling and simulation and their application to performance-based design and operation of buildings and the systems which service them. • Provides readers with the essential concepts of computational support of performance-based design and operation. • Provides examples of how to use building simulation techniques for practical design, management and operation, their limitations and future direction. It is primarily intended for building and systems designers and operators, and postgraduate architectural, environmental or mechanical engineering students.
| Author | : Zhaojun Wang |
| Publisher | : Springer Nature |
| Total Pages | : 931 |
| Release | : 2020-03-19 |
| Genre | : Technology & Engineering |
| ISBN | : 9811395241 |
This book presents selected papers from the 11th International Symposium on Heating, Ventilation and Air Conditioning (ISHVAC 2019), with a focus on HVAC techniques for improving indoor environment quality and the energy efficiency of heating and cooling systems. Presenting inspiration for implementing more efficient and safer HVAC systems, the book is a valuable resource for academic researchers, engineers in industry, and government regulators.
| Author | : Can Cui |
| Publisher | : |
| Total Pages | : 152 |
| Release | : 2016 |
| Genre | : Building |
| ISBN | : |
Buildings consume nearly 50% of the total energy in the United States, which drives the need to develop high-fidelity models for building energy systems. Extensive methods and techniques have been developed, studied, and applied to building energy simulation and forecasting, while most of work have focused on developing dedicated modeling approach for generic buildings. In this study, an integrated computationally efficient and high-fidelity building energy modeling framework is proposed, with the concentration on developing a generalized modeling approach for various types of buildings. First, a number of data-driven simulation models are reviewed and assessed on various types of computationally expensive simulation problems. Motivated by the conclusion that no model outperforms others if amortized over diverse problems, a meta-learning based recommendation system for data-driven simulation modeling is proposed. To test the feasibility of the proposed framework on the building energy system, an extended application of the recommendation system for short-term building energy forecasting is deployed on various buildings. Finally, Kalman filter-based data fusion technique is incorporated into the building recommendation system for on-line energy forecasting. Data fusion enables model calibration to update the state estimation in real-time, which filters out the noise and renders more accurate energy forecast. The framework is composed of two modules: off-line model recommendation module and on-line model calibration module. Specifically, the off-line model recommendation module includes 6 widely used data-driven simulation models, which are ranked by meta-learning recommendation system for off-line energy modeling on a given building scenario. Only a selective set of building physical and operational characteristic features is needed to complete the recommendation task. The on-line calibration module effectively addresses system uncertainties, where data fusion on off-line model is applied based on system identification and Kalman filtering methods. The developed data-driven modeling framework is validated on various genres of buildings, and the experimental results demonstrate desired performance on building energy forecasting in terms of accuracy and computational efficiency. The framework could be easily implemented into building energy model predictive control (MPC), demand response (DR) analysis and real-time operation decision support systems.
| Author | : Rodrigues, João M.F. |
| Publisher | : IGI Global |
| Total Pages | : 459 |
| Release | : 2020-02-28 |
| Genre | : Computers |
| ISBN | : 1799821145 |
Smart systems when connected to artificial intelligence (AI) are still closely associated with some popular misconceptions that cause the general public to either have unrealistic fears about AI or to expect too much about how it will change our workplace and life in general. It is important to show that such fears are unfounded, and that new trends, technologies, and smart systems will be able to improve the way we live, benefiting society without replacing humans in their core activities. Smart Systems Design, Applications, and Challenges provides emerging research that presents state-of-the-art technologies and available systems in the domains of smart systems and AI and explains solutions from an augmented intelligence perspective, showing that these technologies can be used to benefit, instead of replace, humans by augmenting the information and actions of their daily lives. The book addresses all smart systems that incorporate functions of sensing, actuation, and control in order to describe and analyze a situation and make decisions based on the available data in a predictive or adaptive manner. Highlighting a broad range of topics such as business intelligence, cloud computing, and autonomous vehicles, this book is ideally designed for engineers, investigators, IT professionals, researchers, developers, data analysts, professors, and students.
| Author | : Ravinesh Deo |
| Publisher | : Elsevier |
| Total Pages | : 552 |
| Release | : 2020-10-14 |
| Genre | : Science |
| ISBN | : 0128177721 |
Predictive Modeling for Energy Management and Power Systems Engineering introduces readers to the cutting-edge use of big data and large computational infrastructures in energy demand estimation and power management systems. The book supports engineers and scientists who seek to become familiar with advanced optimization techniques for power systems designs, optimization techniques and algorithms for consumer power management, and potential applications of machine learning and artificial intelligence in this field. The book provides modeling theory in an easy-to-read format, verified with on-site models and case studies for specific geographic regions and complex consumer markets. Presents advanced optimization techniques to improve existing energy demand system Provides data-analytic models and their practical relevance in proven case studies Explores novel developments in machine-learning and artificial intelligence applied in energy management Provides modeling theory in an easy-to-read format
| Author | : Chris Underwood |
| Publisher | : John Wiley & Sons |
| Total Pages | : 312 |
| Release | : 2008-04-15 |
| Genre | : Technology & Engineering |
| ISBN | : 1405153008 |
Climate change mitigation and sustainable practices are now at the top of political and technical agendas. Environmental system modelling provides a way of appraising options and this book will make a significant contribution to the uptake of such systems. It provides knowledge of the principles involved in modelling systems, builds confidence amongst designers and offers a broad perspective of the potential of these new technologies. The aim of the book is to provide an understanding of the concepts and principles behind predictive modelling methods; review progress in the development of the modelling software available; and explore modelling in building design through international case studies based on real design problems.
| Author | : Moncef Krarti |
| Publisher | : CRC Press |
| Total Pages | : 658 |
| Release | : 2020-12-01 |
| Genre | : Science |
| ISBN | : 1000259676 |
Updated to include recent advances, this third edition presents strategies and analysis methods for conserving energy and reducing operating costs in residential and commercial buildings. The book explores the latest approaches to measuring and improving energy consumption levels, with calculation examples and Case Studies. It covers field testing, energy simulation, and retrofit analysis of existing buildings. It examines subsystems—such as lighting, heating, and cooling—and techniques needed for accurately evaluating them. Auditors, managers, and students of energy systems will find this book to be an invaluable resource for their work. Explores state-of-the-art techniques and technologies for reducing energy combustion in buildings. Presents the latest energy efficiency strategies and established methods for energy estimation. Provides calculation examples that outline the application of the methods described. Examines the major building subsystems: lighting, heating, and air-conditioning. Addresses large-scale retrofit analysis approaches for existing building stocks. Introduces the concept of energy productivity to account for the multiple benefits of energy efficiency for buildings. Includes Case Studies to give readers a realistic look at energy audits. Moncef Krarti has vast experience in designing, testing, and assessing innovative energy efficiency and renewable energy technologies applied to buildings. He graduated from the University of Colorado with both MS and PhD in Civil Engineering. Prof. Krarti directed several projects in designing energy-efficient buildings with integrated renewable energy systems. He has published over 3000 technical journals and handbook chapters in various fields related to energy efficiency, distribution generation, and demand-side management for the built environment. Moreover, he has published several books on building energy-efficient systems. Prof. Krarti is Fellow member to the American Society for Mechanical Engineers (ASME), the largest international professional society. He is the founding editor of the ASME Journal of Sustainable Buildings & Cities Equipment and Systems. Prof. Krarti has taught several different courses related to building energy systems for over 20 years in the United States and abroad. As a professor at the University of Colorado, Prof. Krarti has been managing the research activities of an energy management center at the school with an emphasis on testing and evaluating the performance of mechanical and electrical systems for residential and commercial buildings. He has also helped the development of similar energy efficiency centers in other countries, including Brazil, Mexico, and Tunisia. In addition, Prof. Krarti has extensive experience in promoting building energy technologies and policies overseas, including the establishment of energy research centers, the development of building energy codes, and the delivery of energy training programs in several countries.
| Author | : Frede Blaabjerg |
| Publisher | : MDPI |
| Total Pages | : 500 |
| Release | : 2019-06-24 |
| Genre | : Technology & Engineering |
| ISBN | : 3039210203 |
Power electronics technology is still an emerging technology, and it has found its way into many applications, from renewable energy generation (i.e., wind power and solar power) to electrical vehicles (EVs), biomedical devices, and small appliances, such as laptop chargers. In the near future, electrical energy will be provided and handled by power electronics and consumed through power electronics; this not only will intensify the role of power electronics technology in power conversion processes, but also implies that power systems are undergoing a paradigm shift, from centralized distribution to distributed generation. Today, more than 1000 GW of renewable energy generation sources (photovoltaic (PV) and wind) have been installed, all of which are handled by power electronics technology. The main aim of this book is to highlight and address recent breakthroughs in the range of emerging applications in power electronics and in harmonic and electromagnetic interference (EMI) issues at device and system levels as discussed in robust and reliable power electronics technologies, including fault prognosis and diagnosis technique stability of grid-connected converters and smart control of power electronics in devices, microgrids, and at system levels.
