Energy requirements for heating and cooling of residential, commercial and industrial spaces constitute a major fraction of end use energy consumed. Centralized systems such as hydronic networks are becoming increasingly popular to meet those requirements. Energy efficient operation of such systems requires intelligent energy management strategies, which necessitates an understanding of the complex dynamical interactions among its components from a mathematical and physical perspective. In this work, concepts from linear graph theory are applied to model complex hydronic networks. Further, time-scale decomposition techniques have been employed to obtain a more succinct representation of the overall system dynamics. The proposed model is then used to design predictive control strategies which are compared with traditional feedback control schemes using a simulated chilled water system as a case study. The advantages and limitations associated with these methodologies has been demonstrated. The cornerstone of this work is the development of a novel, distributed predictive scheme which provides the best compromise in the multidimensional evaluation framework of 'regulation', `optimality', `reliability' and `computational complexity'.
Welcome to the world of HVAC hydronic systems, where the marriage of heating, ventilation, and air conditioning meets the elegance and efficiency of water-based heating and cooling solutions. This book is an exploration of the principles, design, and applications of hydronic systems in the context of HVAC. As the demand for energy-efficient and environmentally friendly solutions continues to grow, hydronic systems have emerged as a preferred choice for heating and cooling residential, commercial, and industrial spaces. These systems leverage the unique properties of water as a medium for transferring thermal energy, offering numerous advantages over traditional air-based HVAC systems. The aim of this book is to provide a comprehensive and accessible resource for understanding the fundamentals of hydronic systems, their components, and their integration into building infrastructure. Whether you are a seasoned HVAC professional seeking to expand your knowledge or a student entering the field, this book will serve as a valuable guide. In the chapters that follow, we will delve into the key principles underlying hydronic systems, exploring topics such as fluid dynamics, heat transfer, system components, control strategies, and system design considerations. We will discuss various types of hydronic heating and cooling systems, including radiant floor heating, chilled beam systems, and fan coil units, highlighting their unique features and applications. Additionally, we will examine the role of pumps, boilers, heat exchangers, valves, and other essential components in hydronic systems. We will explore the intricacies of system balancing, zoning, and control, emphasizing the importance of proper installation, operation, and maintenance practices to ensure optimal system performance and energy efficiency. Throughout this book, we will also address emerging trends and technologies in the field of HVAC hydronic systems, such as advanced control algorithms, renewable energy integration, and smart building automation. By staying informed about these developments, you will be equipped to navigate the evolving landscape of HVAC engineering. It is my hope that this book will serve as a source of inspiration, knowledge, and practical guidance for those involved in the design, installation, and operation of HVAC hydronic systems. By harnessing the power of water and embracing the principles outlined in these pages, we can create comfortable and sustainable indoor environments for generations to come. Remember, this book is a starting point—a foundation upon which you can build your understanding and expertise. So, let us embark on this journey together, exploring the world of HVAC hydronic systems and discovering the boundless possibilities they offer. Charles Nehme
Heating, ventilating and air-conditioning (HVAC) systems have been extensively used to provide desired indoor environment in buildings. It is well acknowledged that 25-35% of the total energy use is consumed by buildings, and space heating systems account for 50-60% of the building energy consumption. Furthermore, roughly half of the energy consumed goes to operation of heating systems. In the past few years the energy use has shown rapid growth. Therefore, it is necessary to design and operate HVAC systems to reduce energy consumption and improve occupant comfort. To improve energy efficiency, HVAC systems should be optimally controlled and operated. This study focuses on developing advanced control strategies and fault tolerant control (FTC) using information from fault detection and diagnosis (FDD) for hot water heating (HWH) systems. To begin with, HWH system dynamic models are developed based on mass, momentum and energy balance principles. Then, embedded intelligent control strategies: fuzzy logic control and fuzzy logic adaptive control are designed for the overall system to achieve better performance and energy efficiency. Moreover, in designing the advanced control strategies, the parameter uncertainty and noise from measurement and process are taken into account. The extended Kalman filter (EKF) technique is utilized to handle system uncertainty and measurement noise, and to improve system control performance. After that, a supervisory control strategy for the HWH system is designed and simulated to achieve optimal operation. Finally, model-based FDD methods were developed by using fuzzy logic to detect and isolate measurement and process faults occurring in HWH systems. The FDD information was employed to design model-based FTC systems for various faults and to extend the operating range under failure situations. The contributions of this study include the development of a large scale dynamic model of a HWH system for a high-rise building; design of fuzzy logic adaptive control strategies to improve energy efficiency of heating systems and design of model-based FTC systems by using FDD information.
Improving energy efficiency in the Heating Ventilation and Air conditioning (HVAC) systems in buildings is critical to achieve the energy reduction in the building sector, which consumes 41% of all primary energy produced in the United States, and was responsible for nearly half of U.S. CO2 emissions. Based on a report by the New Building Institute (NBI), when HVAC systems are used, about half of the zero net energy (ZNE) buildings report using a radiant cooling/heating system, often in conjunction with ground source heat pumps. Radiant systems differ from air systems in the main heat transfer mechanism used to remove heat from a space, and in their control characteristics when responding to changes in control signals and room thermal conditions. This dissertation investigates three related design and control topics: cooling load calculations, cooling capacity estimation, and control for the heavyweight radiant systems. These three issues are fundamental to the development of accurate design/modeling tools, relevant performance testing methods, and ultimately the realization of the potential energy benefits of radiant systems. Cooling load calculations are a crucial step in designing any HVAC system. In the current standards, cooling load is defined and calculated independent of HVAC system type. In this dissertation, I present research evidence that sensible zone cooling loads for radiant systems are different from cooling loads for traditional air systems. Energy simulations, in EnergyPlus, and laboratory experiments were conducted to investigate the heat transfer dynamics in spaces conditioned by radiant and air systems. The results show that the magnitude of the cooling load difference between the two systems ranges from 7-85%, and radiant systems remove heat faster than air systems. For the experimental tested conditions, 75-82% of total heat gain was removed by radiant system during the period when the heater (simulating the heat gain) was on, while for air system, 61-63% were removed. From a heat transfer perspective, the differences are mainly because the chilled surfaces directly remove part of the radiant heat gains from a zone, thereby bypassing the time-delay effect caused by the interaction of radiant heat gain with non-active thermal mass in air systems. The major conclusions based on these findings are: 1) there are important limitations in the definition of cooling load for a mixing air system described in Chapter 18 of ASHRAE Handbook of Fundamentals when applied to radiant systems; 2) due to the obvious mismatch between how radiant heat transfer is handled in traditional cooling load calculation methods compared to its central role in radiant cooling systems, this dissertation provides improvements for the current cooling load calculation method based on the Heat Balance procedure. The Radiant Time Series method is not appropriate for radiant system applications. The findings also directly apply to the selection of space heat transfer modeling algorithms that are part of all energy modeling software. Cooling capacity estimation is another critical step in a design project. The above mentioned findings and a review of the existing methods indicates that current radiant system cooling capacity estimation methods fail to take into account incident shortwave radiation generated by solar and lighting in the calculation process. This causes a significant underestimation (up to 150% for some instances) of floor cooling capacity when solar load is dominant. Building performance simulations were conducted to verify this hypothesis and quantify the impacts of solar for different design scenarios. A new simplified method was proposed to improve the predictability of the method described in ISO 11855 when solar radiation is present. The dissertation also compares the energy and comfort benefits of the model-based predictive control (MPC) method with a fine-tuned heuristic control method when applied to a heavyweight embedded surface system. A first order dynamic model of a radiant slab system was developed for implementation in model predictive controllers. A calibrated EnergyPlus model of a typical office building in California was used as a testbed for the comparison. The results indicated that MPC is able to reduce the cooling tower energy consumption by 55% and pumping power consumption by 26%, while maintaining equivalent or even better thermal comfort conditions. In summary, the dissertation work has: (1) provided clear evidence that the fundamental heat transfer mechanisms differ between radiant and air systems. These findings have important implications for the development of accurate and reliable design and energy simulation tools; (2) developed practical design methods and guidance to aid practicing engineers who are designing radiant systems; and (3) outlined future research and design tools need to advance the state-of-knowledge and design and operating guidelines for radiant systems.
This important new book bridges the gap between works on classical control and process control, and those dealing with HVAC control at a more elementary level, which generally adopt a qualitative and descriptive control. Both advanced level students and specialist practitioners will welcome the in-depth analytical treatment of the subject presented in this volume. Of particular significance are the current developments in adaptive control, robust control, artificial neural networks and fuzzy logic systems, all of which are given a thorough analytical treatment in the book. First book to provide an analytical treatment of subject Covers all new developments in HVAC control systems Looks at systems both in the UK and abroad
Energy and cost-efficient management of a building's thermal properties requires heating, ventilation and air conditioning (HVAC) systems controllers to be working at optimal settings. However, many HVAC systems employ nonlinear time variances to deal with issues that affect the system's optimal operation. The present work considers an HVAC system at Memorial University's S. J. Carew Building which has been mathematically modeled using a state space multi-input and multi-output system (MIMO) approach for analyses and control system design. An IDA-ICE (Indoor Climate and Energy) simulation program has been applied for modeling the building, note that the four-story Carew Building includes an air-handling unit (AHU) on every floor. Compared with real data for one year's (2016) power consumption, the simulated annual power consumption for the building shows good agreement. Based on that data, two scenarios are applied for building the system models. Scenario 1 considers the HVAC system as a single unit with energy consumption (kWh) as inputs and zonal temperature and CO2 concentrations as outputs. By employing the MATLAB system identification toolbox, a MIMO-based system forms the basis for a state space model. In the model for Scenario 1, there are eight main AHU inputs (hot water power usage and power usage) and eight main outputs (return airflow temperature and CO2 levels). The state feedback controller obtains good results for both responses rise time and stability. In Scenario 2, there are four AHUs in total. Each of this scenario's AHUs features three main inputs (hot water, internal-to-internal air flow, and external-to-internal air flow) and three main outputs (static air pressure, CO2 levels, and temperature). In the first AHU (AHU1), we apply state-of-the-art fuzzy logic controllers (FLCs) to control fan speeds, CO2 concentrations, and temperature in the building in accordance with the flow rates for air and hot water. This strategy represents a novel approach for adapting FLCs by modifying fuzzy rule using the Simulink. The modified system shows improved levels of thermal comfort. The final part of the work presents the design for a supervisor fuzzy logic controller (SFLC) that can be applied to the entire S. J. Carew Building HVAC control. This SFLC features 24 inputs and 12 outputs and employs a state-space model that considers each AHU as an individual system. The SFLC detailed design and system simulation results are presented in this thesis.
Readers of this book will be shown how, with the adoption of ubiquituous sensing, extensive data-gathering and forecasting, and building-embedded advanced actuation, intelligent building systems with the ability to respond to occupant preferences in a safe and energy-efficient manner are becoming a reality. The articles collected present a holistic perspective on the state of the art and current research directions in building automation, advanced sensing and control, including: model-based and model-free control design for temperature control; smart lighting systems; smart sensors and actuators (such as smart thermostats, lighting fixtures and HVAC equipment with embedded intelligence); and energy management, including consideration of grid connectivity and distributed intelligence. These articles are both educational for practitioners and graduate students interested in design and implementation, and foundational for researchers interested in understanding the state of the art and the challenges that must be overcome in realizing the potential benefits of smart building systems. This edited volume also includes case studies from implementation of these algorithms/sensing strategies in to-scale building systems. These demonstrate the benefits and pitfalls of using smart sensing and control for enhanced occupant comfort and energy efficiency.
Heating Ventilation and Air Conditioning by J. W. Mitchell and J. E. Braun provides foundational knowledge for the behavior and analysis of HVAC systems and related devices. The emphasis of this text is on the application of engineering principles that features tight integration of physical descriptions with a software program that allows performance to be directly calculated, with results that provide insight into actual behavior. Furthermore, the text offers more examples, end-of-chapter problems, and design projects that represent situations an engineer might face in practice and are selected to illustrate the complex and integrated nature of an HVAC system or piece of equipment.
