Dynamic Modeling and Control of a Hybrid Hydronic Heating System
Dynamic Modeling and Control of a Hybrid Hydronic Heating System

Author: YiTeng MA

Publisher:

Published: 2014

Total Pages: 115

ISBN-13:

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A dynamic model of a hybrid hydronic heating system has been developed. Simulations of the control strategies and the model-based energy analysis for the overall system have been presented in this thesis. The hybrid hydronic system is composed of a conventional natural gas fired boiler hot water heating and a ground source heat pump system. The overall system consists of several components such as a boiler, a heat exchanger, a ground loop heat pump, a ground loop heat exchanger, baseboard heaters, and radiant floor hydraulic piping systems. The system model was described by nonlinear differential equations, which were programmed and solved using MATLAB. Two control strategies for improving the overall system performance were explored: (i) a conventional PI control, and (ii) an adaptive gain control. The simulation results subject to set-point changes showed that the performance of the adaptive controller is better than the fixed gain PI controller in disturbance rejection and stability. Energy simulations under three different operating strategies were conducted: (i) a conventional fixed set-point PI control, (ii) an outdoor air temperature reset control, and (iii) an optimal set-point PI control. It was shown that the outdoor temperature reset strategy can save 4.5% and 19.9% energy under cold day and mild day conditions compared to the conventional fixed set-point PI control strategy. In addition, the iv implementation of the optimal PI control strategy result in higher energy savings 6.6% and 22% as compared to the base case under cold and mild day conditions, respectively.

Dynamic Modeling and Control of Hybrid Ground Source Heat Pump Systems
Dynamic Modeling and Control of Hybrid Ground Source Heat Pump Systems

Author: Chang Chen

Publisher:

Published: 2008

Total Pages: 0

ISBN-13:

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Ground source heat pump (GSHP) systems are one of the fastest growing applications of renewable energy in the world with annual increases of 10% over the past decade. GSHPs are potentially more efficient than conventional air-to-air heat pumps as they use the relatively constant temperature of the geothermal energy to provide heating or cooling to conditioned rooms at desired temperature and relative humidity. More importantly, GSHP systems can in fact achieve significant energy savings year round, compared to conventional HVAC systems. A hybrid ground source heat pump (HGSHP) system is designed in this study to heat and cool an office building all the year round. Dynamic models of each component of the heat pump system are developed for simulations of heat transfer between each component of the HGSHP system and for control strategy design and analysis. A detailed multiple-load aggregation algorithm (MLAA) is adapted from the literature to precisely account for and calculate the transient heat conduction in vertical ground heat exchangers with different yearly, monthly, and daily pulses of heat. Feedback PI controllers for heat pump units and On/Off controllers for boiler and cooling tower are designed and utilized to match anticipated building loads and to analyze transient response characteristics of such outputs as water flow rate and air flow rate of heat pumps, return water temperature and supply air temperature of heat pumps, water temperatures of ground loops and heat exchangers, water temperature of boiler or cooling tower, and fuel flow rate of boiler. Control strategies for the HGSHP system in both heating and cooling modes of operation are also introduced to study the system responses. With the usage of On/Off controllers and well-tuned PI controllers, as well as optimal control strategies for heating and cooling operations, the HGSHP system is expected to give better operating performance and efficiency. As a result, noticeable energy savings can be achieved in both heating and cooling modes of operation.

Dynamic Modeling, Intelligent Control and Diagnostics of Hot Water Heating Systems
Dynamic Modeling, Intelligent Control and Diagnostics of Hot Water Heating Systems

Author: Lianzhong Li

Publisher:

Published: 2008

Total Pages: 0

ISBN-13:

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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.

Dynamic Modeling and Model-free Real-time Optimization for Cold Climate Heat Pump Systems
Dynamic Modeling and Model-free Real-time Optimization for Cold Climate Heat Pump Systems

Author: Wenyi Wang

Publisher:

Published: 2019

Total Pages:

ISBN-13:

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Air source heat pump (ASHP) has been a well-received technology to provide space and/or water heating for building and industrial applications, while its efficiency and heating capacity can be severely limited when operated in cold climate. Various modifications have been proposed for cold-climate operation of ASHP over the single-stage refrigeration cycle, such as vapor injection techniques and cascade configuration. However, there has been a lack of effective control strategies for such systems to maintain the optimal energy efficiency for operations across different combinations of ambient and load conditions. Previous work has paid great efforts in model based strategies, anchored on deriving system models with simulation and experimental testing. Such approaches can be prohibitively expensive due to the inherent nonlinear nature of refrigeration systems and unmeasurable equipment degradation. This dissertation investigates on model-free control strategies for real-time efficiency optimization for several configurations of cold-climate ASHP, by use of Extremum Seeking Control (ESC). By utilizing periodic dither inputs for online gradient estimation, ESC bears significant robustness against process variation and external disturbance, which has proved to be more advantageous in handling the challenging applications like heating, ventilation and air conditioning (HVAC) systems. Three types of ASHP configurations are studied in this dissertation: the internal heat exchanger vapor injection, flash-tank vapor injection, and cascade configuration. For both vapor injection ASHP configurations, the intermediate pressure setpoint is optimized by standard ESC and Newton-based ESC based on the feedback of the total power consumption, with the constant heating load considered. For the cascade ASHP, multivariable ESC is designed to handle two operational scenarios: minimizing the total power for fixed heating capacity and maximizing the coefficient of performance (COP) for variable heating capacity. For the power based ESC, the manipulated inputs include the intermediate temperature, high temperature cycle superheat and low temperature cycle superheat; while for the COP based ESC, the high- and low-temperature cycle compressor speeds and evaporator fan mass flow rate are adopted as inputs. The proposed ESC strategies are evaluated with Modelica based dynamic simulation models of the three system configurations. Simulations have been conducted under both fixed and realistic ambient temperature profiles. The simulation results show good steady-state and transient performance of real-time efficiency optimization with the proposed strategies, in terms of tracking unknown and dynamic optimum settings.

Dynamic Modeling and Optimal Operation of District Heating Systems
Dynamic Modeling and Optimal Operation of District Heating Systems

Author: Lianzhong Li

Publisher:

Published: 2003

Total Pages: 0

ISBN-13:

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District Heating Systems (DHS) are widely utilized for space heating in residential and commercial buildings. They offer economic benefits to consumers in terms of lower heating costs. The energy efficiency of DHS can be further improved by optimally controlling the operating parameters of the system. With this as a motivation, dynamic modeling and optimal operation strategies of DHS are explored in this thesis. Two typical District Heating Systems namely Direct District Heating System (DDHS) and Indirect District Heating System (IDHS) are considered. Using typical system configurations the components of the DHS were sized. Dynamic models of the designed DHSS useful for control analysis were developed. Open loop tests subject to constant inputs and loads were conducted to evaluate the time response characteristics of DHS. A methodology for computing optimal operating parameters of DHS is presented. These optimal parameters so computed are used as set points for PID controllers. The DHS by virtue of its long distribution network is subject to large transportation time delays. To compensate such time delays, a PID controller augmented with a Smith Predictor is developed. The designed controller is used to simulate closed loop operation of DHS under variable load conditions. Results show that the optimal set point strategy can save 10%-15% energy compared to conventional control strategies.

Modeling and Control of Hydronic Building HVAC Systems
Modeling and Control of Hydronic Building HVAC Systems

Author: Vikas Chandan

Publisher:

Published: 2010

Total Pages:

ISBN-13:

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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'.

Modeling and Control in Air-conditioning Systems
Modeling and Control in Air-conditioning Systems

Author: Ye Yao

Publisher: Springer

Published: 2016-10-01

Total Pages: 496

ISBN-13: 3662533138

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This book investigates the latest modeling and control technologies in the context of air-conditioning systems. Firstly, it introduces the state-space method for developing dynamic models of all components in a central air-conditioning system. The models are primarily nonlinear and based on the fundamental principle of energy and mass conservation, and are transformed into state-space form through linearization. The book goes on to describe and discuss the state-space models with the help of graph theory and the structure-matrix theory. Subsequently, virtual sensor calibration and virtual sensing methods (which are very useful for real system control) are illustrated together with a case study. Model-based predictive control and state-space feedback control are applied to air-conditioning systems to yield better local control, while the air-side synergic control scheme and a global optimization strategy based on the decomposition-coordination method are developed so as to achieve energy conservation in the central air-conditioning system. Lastly, control strategies for VAV systems including total air volume control and trim & response static pressure control are investigated in practice.