Read Books Online and Download eBooks, EPub, PDF, Mobi, Kindle, Text Full Free.
Model Predictive Optimal Control For Active And Passive Cold Thermal Energy Storage Of Multi Zone Buildings
Download Model Predictive Optimal Control For Active And Passive Cold Thermal Energy Storage Of Multi Zone Buildings full books in PDF, epub, and Kindle. Read online Model Predictive Optimal Control For Active And Passive Cold Thermal Energy Storage Of Multi Zone Buildings ebook anywhere anytime directly on your device. Fast Download speed and no annoying ads. We cannot guarantee that every ebooks is available!
Book Synopsis Model Predictive Optimal Control for Active and Passive Cold Thermal Energy Storage of Multi-zone Buildings by : Chang Liu
Download or read book Model Predictive Optimal Control for Active and Passive Cold Thermal Energy Storage of Multi-zone Buildings written by Chang Liu and published by . This book was released on 2012 with total page 91 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Predictive Optimal Control of Active and Passive Building Thermal Storage Inventory by : Moncef Krarti
Download or read book Predictive Optimal Control of Active and Passive Building Thermal Storage Inventory written by Moncef Krarti and published by . This book was released on 2005 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Cooling of commercial buildings contributes significantly to the peak demand placed on an electrical utility grid. Time-of-use electricity rates encourage shifting of electrical loads to off-peak periods at night and weekends. Buildings can respond to these pricing signals by shifting cooling-related thermal loads either by precooling the building's massive structure or the use of active thermal energy storage systems such as ice storage. While these two thermal batteries have been engaged separately in the past, this project investigated the merits of harnessing both storage media concurrently in the context of predictive optimal control. To pursue the analysis, modeling, and simulation research of Phase 1, two separate simulation environments were developed. Based on the new dynamic building simulation program EnergyPlus, a utility rate module, two thermal energy storage models were added. Also, a sequential optimization approach to the cost minimization problem using direct search, gradient-based, and dynamic programming methods was incorporated. The objective function was the total utility bill including the cost of reheat and a time-of-use electricity rate either with or without demand charges. An alternative simulation environment based on TRNSYS and Matlab was developed to allow for comparison and cross-validation with EnergyPlus. The initial evaluation of the theoretical potential of the combined optimal control assumed perfect weather prediction and match between the building model and the actual building counterpart. The analysis showed that the combined utilization leads to cost savings that is significantly greater than either storage but less than the sum of the individual savings. The findings reveal that the cooling-related on-peak electrical demand of commercial buildings can be considerably reduced. A subsequent analysis of the impact of forecasting uncertainty in the required short-term weather forecasts determined that it takes only very simple short-term prediction models to realize almost all of the theoretical potential of this control strategy. Further work evaluated the impact of modeling accuracy on the model-based closed-loop predictive optimal controller to minimize utility cost. The following guidelines have been derived: For an internal heat gain dominated commercial building, reasonable geometry simplifications are acceptable without a loss of cost savings potential. In fact, zoning simplification may improve optimizer performance and save computation time. The mass of the internal structure did not show a strong effect on the optimization. Building construction characteristics were found to impact building passive thermal storage capacity. It is thus advisable to make sure the construction material is well modeled. Zone temperature setpoint profiles and TES performance are strongly affected by mismatches in internal heat gains, especially when they are underestimated. Since they are a key factor in determining the building cooling load, efforts should be made to keep the internal gain mismatch as small as possible. Efficiencies of the building energy systems affect both zone temperature setpoints and active TES operation because of the coupling of the base chiller for building precooling and the icemaking TES chiller. Relative efficiencies of the base and TES chillers will determine the balance of operation of the two chillers. The impact of mismatch in this category may be significant. Next, a parametric analysis was conducted to assess the effects of building mass, utility rate, building location and season, thermal comfort, central plant capacities, and an economizer on the cost saving performance of optimal control for active and passive building thermal storage inventory. The key findings are: (1) Heavy-mass buildings, strong-incentive time-of-use electrical utility rates, and large on-peak cooling loads will likely lead to attractive savings resulting from optimal combined thermal storage control. (2) By using economizer to take advantage of the cool fresh air during the night, the building electrical cost can be reduced by using less mechanical cooling. (3) Larger base chiller and active thermal storage capacities have the potential of shifting more cooling loads to off-peak hours and thus higher savings can be achieved. (4) Optimal combined thermal storage control with a thermal comfort penalty included in the objective function can improve the thermal comfort levels of building occupants when compared to the non-optimized base case. Lab testing conducted in the Larson HVAC Laboratory during Phase 2 showed that the EnergyPlus-based simulation was a surprisingly accurate prediction of the experiment. Therefore, actual savings of building energy costs can be expected by applying optimal controls from simulation results.
Book Synopsis Predictive Optimal Control of Active and Passive Building Thermal Storage Inventory by :
Download or read book Predictive Optimal Control of Active and Passive Building Thermal Storage Inventory written by and published by . This book was released on 2003 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Experimental Analysis of Model-based Predictive Optimal Control for Active and Passive Building Thermal Storage Inventory by : Doreen E. Kalz
Download or read book Experimental Analysis of Model-based Predictive Optimal Control for Active and Passive Building Thermal Storage Inventory written by Doreen E. Kalz and published by . This book was released on 2003 with total page 172 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Thermal Energy Storage with Phase Change Materials by : Mohammed Farid
Download or read book Thermal Energy Storage with Phase Change Materials written by Mohammed Farid and published by CRC Press. This book was released on 2021-07-26 with total page 560 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book focuses on latent heat storage, which is one of the most efficient ways of storing thermal energy. Unlike the sensible heat storage method, the latent heat storage method provides much higher storage density with a smaller difference between storing and releasing temperatures. Thermal Energy Storage with Phase Change Materials is structured into four chapters that cover many aspects of thermal energy storage and their practical applications. Chapter 1 reviews selection, performance, and applications of phase change materials. Chapter 2 investigates mathematical analyses of phase change processes. Chapters 3 and 4 present passive and active applications for energy saving, peak load shifting, and price-based control heating using phase change materials. These chapters explore the hot topic of energy saving in an overarching way, and so they are relevant to all courses. This book is an ideal research reference for students at the postgraduate level. It also serves as a useful reference for electrical, mechanical, and chemical engineers and students throughout their work. FEATURES Explains the technical principles of thermal energy storage, including materials and applications in different classifications Provides fundamental calculations of heat transfer with phase change Discusses the benefits and limitations of different types of phase change materials (PCM) in both micro- and macroencapsulations Reviews the mechanisms and applications of available thermal energy storage systems Introduces innovative solutions in hot and cold storage applications
Book Synopsis Optimal Control of Building Mass Thermal Energy Storage Systems by : Buss Andrew Price
Download or read book Optimal Control of Building Mass Thermal Energy Storage Systems written by Buss Andrew Price and published by . This book was released on 1995 with total page 276 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Future Urban Energy System for Buildings by : Xingxing Zhang
Download or read book Future Urban Energy System for Buildings written by Xingxing Zhang and published by Springer Nature. This book was released on 2023-05-13 with total page 485 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book investigates three main characteristics of future urban energy system for buildings, including flexibility, resilience and optimization. It explores the energy flexibility by considering renewable energy integration with buildings, sector coupling, and energy trading in the local energy market. Energy resilience is addressed from aspects of future climate change, pandemic crisis, and operational uncertainties. Approaches for system design, dynamic pricing and advanced control are discussed for the optimization of urban energy system. Knowledge from this book contributes to the effective means in future urban energy paradigm to closely integrate multiple energy systems (i.e., distribution, mobility, production and storage) with different energy carriers (i.e., heat, electricity) in an optimal manner for energy use. It would facilitate the envision of next-generation urban energy systems, towards sustainability, resilience and prosperity. This book targets at a broad readership with specific experience and knowledge in energy system, transport, built environment and urban planning. As such, it will appeal to researchers, graduate students, engineers, consultants, urban scientists, investors and policymakers, with interests in energy flexibility, building/city resilience and climate neutrality.
Book Synopsis Using Occupant Feedback in Model Predictive Control for Indoor Thermal Comfort and Energy Optimization by : Xiao Chen
Download or read book Using Occupant Feedback in Model Predictive Control for Indoor Thermal Comfort and Energy Optimization written by Xiao Chen and published by . This book was released on 2015 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Buildings are our society's biggest energy users. Reducing building energy consumption and creating a better indoor thermal environment have becoming a more and more important topic among policy makers, building scientists/engineers, and the masses. To achieve this target, great efforts have been made in several aspects including but not limited to using better thermal insulation materials, integrating renewable power sources, developing intelligent buildings, and creating better and more efficient building climate control systems.With the ever increasing computation power, advancements in building modeling and simulation, and accurate weather forecast, model predictive control (MPC) reveals its power as one of the best control methods in building climate control to save energy and maintain high level of indoor comfort. Although many researchers have investigated extensively on how to use building's active or passive thermal storage along with accurate weather forecast and occupants' schedule prediction to reduce energy consumption or shift loads, not much research has been done on how a better thermal comfort model used in MPC would help reducing energy usage and improve comfort level. Furthermore, unlike lighting control in which occupants have plenty of opportunities to adjust lights and blinds so that visual comfort can be improved, centralized and automated building thermal control systems take away users' ability to intervene the control system directly. In this dissertation, we study occupant augmented MPC control design in which feedback information from occupants is used to adaptively update the prediction given by a data-driven dynamic thermal sensation model. It is demonstrated both in simulation and chamber experiment that including users directly in the feedback loop of MPC control design provides opportunity to significantly save energy and still maintain thermal comfort. We propose a data-driven state-space dynamic thermal sensation (DTS) model based on data collected in a chamber experiment. The developed model takes air temperature as input, and the occupant actual mean thermal sensation vote as an output. To account for cases in which indoor environmental or occupant associated conditions deviate from the nominal condition conducted in the chamber experiment, a time-varying offset parameter in the model is adaptively estimated by an extended Kalman filter using feedback information from occupants.We develop two different MPC controls based on the proposed DTS model: a certainty equivalence MPC and a chance constrained MPC. By using this thermal comfort model in the MPC design, users are included directly in the feedback loop. We compare the DTS model based MPC with predicted mean vote (PMV) model based MPC. Simulation results demonstrate that an MPC based on occupant feedback can be expected to produce better energy and thermal comfort outcomes than an MPC based on PMV model. The proposed chance-constrained MPC is designed to allow specifying the probability of violation of thermal comfort constraint, so that a balance between energy saving and thermal comfort can be achieved.The DTS model based MPC is evaluated in chamber experiment. A hierarchical control strategy is used. On the high level, MPC calculates optimal supply air temperature of the chamber's HVAC system. On the low level, the actual supply air temperature of the HVAC system is controlled by the chiller and heater using PI control to achieve the optimal level set by the high level. Results from experiments show that the DTS-based MPC with occupant feedback provides the opportunity to reduce energy consumption significantly while maintain occupant thermal comfort.
Book Synopsis Thermal Energy Storage Analyses and Designs by : Pei-Wen Li
Download or read book Thermal Energy Storage Analyses and Designs written by Pei-Wen Li and published by Academic Press. This book was released on 2017-06-06 with total page 236 pages. Available in PDF, EPUB and Kindle. Book excerpt: Thermal Energy Storage Analyses and Designs considers the significance of thermal energy storage systems over other systems designed to handle large quantities of energy, comparing storage technologies and emphasizing the importance, advantages, practicalities, and operation of thermal energy storage for large quantities of energy production. Including chapters on thermal storage system configuration, operation, and delivery processes, in particular the flow distribution, flow arrangement, and control for the thermal charge and discharge processes for single or multiple thermal storage containers, the book is a useful reference for engineers who design, install, or maintain storage systems. - Includes computer code for thermal storage analysis, including code flow charts - Contains a database of material properties relevant to storage - Provides example cases of input and output data for the code
Book Synopsis Model Predictive Control of Electric Building Energy and Heating Systems by : Sayani Seal
Download or read book Model Predictive Control of Electric Building Energy and Heating Systems written by Sayani Seal and published by . This book was released on 2020 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: "The residential building sector is a major consumer of electricity. In cold countries like Canada, heating systems contribute to a large share of the total building energy demand. Smart and efficient solutions to reduce building energy consumption are continually being explored through multi-disciplinary fields of research. This thesis focuses on the development and analysis of a central model predictive control (MPC) strategy for both comfort as well as energy management. In this work, the building simulations are done using a well-established simulation software TRNSYS (Transient System Simulation Tool) and the controllers are designed and simulated in MATLAB using standard computation routines. The thesis is conceptually divided into two parts. A simulation-based analytical study of two typical Canadian residential heating systems, namely electric baseboard heaters (BB) and hydronic radiant floor heating (RFH) systems is presented in the first part. The study focuses on the modelling and characterization of the RFH and BB heating systems, highlighting the differences between their respective heating dynamics and related effects on their performance. A closed-loop MPC is designed and implemented for indoor temperature control. Various control scenarios are simulated to study the individual and cooperative performances of the two heating systems. Two novel MPC schemes are proposed to design a collaborative heating system using RFH and BB. These cooperative control schemes, namely the Sequential and Simultaneous approaches, have the identical goal of improving the performance of the slow-reacting RFH in maintaining the indoor operative temperature within predefined bounds while reducing the energy cost. In the Sequential approach, separate MPCs successively perform the optimizations for the RFH and BB whereas for the Simultaneous approach a single MPC optimizes the two heating systems. The MPC optimization also considers a thermal energy storage unit, incorporated as a part of the RFH system, for optimal energy usage based on variable Time-of-Use rate.The HVAC system constitutes an integral part of the building energy management system. In the second part of the thesis, a novel centralized MPC based building energy management system (BEMS) is proposed. The new residential setup used here is equipped with a photovoltaic (PV) solar system and a battery storage unit. An air-to-air multi-split heat pump (HP) is used as the primary heating system. The electric baseboard (BB) unit in each zone is used as a secondary system. The MPC is simultaneously responsible for controlling the heating inputs of the HP and BB units for comfort management, as well as for the control of energy flow between the PV, the home-battery and the bidirectional grid system. Variable Time-of-Use (ToU) rates are considered for the energy cost calculation and Feed-in-Tariff (FiT) is considered for selling energy to the grid. The MPC strategy is further modified to incorporate an electric vehicle (EV). The EV is considered as an intermittently available extended battery storage unit. Uncertainties related to the EV availability schedule, home-work-home trip discharges and state of charge (SOC) of the battery are considered. A Monte Carlo based uncertainty analysis is presented to estimate the reliability of MPC performance against the disturbances introduced into the system. Performance of the MPC is studied considering EV to home (V2H) communication, in an example simulation scenario"--
Book Synopsis Comfort Control in Buildings by : María del Mar Castilla
Download or read book Comfort Control in Buildings written by María del Mar Castilla and published by Springer. This book was released on 2014-06-30 with total page 257 pages. Available in PDF, EPUB and Kindle. Book excerpt: The aim of this book is to research comfort control inside buildings, and how this can be achieved through low energy consumption. It presents a comprehensive exploration of the design, development and implementation of several advanced control systems that maintain users' comfort (thermal and indoor air quality) whilst minimizing energy consumption. The book includes a detailed account of the latest cutting edge developments in this area, and presents several control systems based on Model Predictive Control approaches. Real-life examples are provided, and the book is supplemented by illustrations, tables, all of which facilitate understanding of the text. Energy consumption in buildings (residential and non-residential) represents almost the half of the total world energy consumption, and they are also responsible for approximately 35% of CO2 emissions. For these reasons, the reduction of energy consumption associated with the construction and use of buildings, and the increase of energy efficiency in their climatic refurbishment are frequently studied topics in academia and industry. As the productivity of users is directly related to their comfort, a middle ground needs to be found between comfort of users and energy efficiency. In order to achieve this, it is necessary to develop innovation and technology which can provide comfortable environments with minimum energy consumption. This book is intended for researchers interested in control engineering, energy and bioclimatic buildings, and for architects and process control engineers. It is also accessible to postgraduate students embarking on a career in this area, particularly those studying architecture.
Book Synopsis Thermal Energy Storage for Sustainable Energy Consumption by : Halime Ö. Paksoy
Download or read book Thermal Energy Storage for Sustainable Energy Consumption written by Halime Ö. Paksoy and published by Springer Science & Business Media. This book was released on 2007-03-16 with total page 440 pages. Available in PDF, EPUB and Kindle. Book excerpt: Çukurova University, Turkey in collaboration with Ljubljana University, Slovenia and the International Energy Agency Implementing Agreement on Energy Conservation Through Energy Storage (IEA ECES IA) organized a NATO Advanced Study Institute on Thermal Energy Storage for Sustainable Energy Consumption – Fundamentals, Case Studies and Design (NATO ASI TESSEC), in Cesme, Izmir, Turkey in June, 2005. This book contains manuscripts based on the lectures included in the scientific programme of the NATO ASI TESSEC.
Book Synopsis Advances in Thermal Energy Storage Systems by : Luisa F. Cabeza
Download or read book Advances in Thermal Energy Storage Systems written by Luisa F. Cabeza and published by Elsevier. This book was released on 2014-10-31 with total page 623 pages. Available in PDF, EPUB and Kindle. Book excerpt: Thermal energy storage (TES) technologies store thermal energy (both heat and cold) for later use as required, rather than at the time of production. They are therefore important counterparts to various intermittent renewable energy generation methods and also provide a way of valorising waste process heat and reducing the energy demand of buildings. This book provides an authoritative overview of this key area. Part one reviews sensible heat storage technologies. Part two covers latent and thermochemical heat storage respectively. The final section addresses applications in heating and energy systems. - Reviews sensible heat storage technologies, including the use of water, molten salts, concrete and boreholes - Describes latent heat storage systems and thermochemical heat storage - Includes information on the monitoring and control of thermal energy storage systems, and considers their applications in residential buildings, power plants and industry
Book Synopsis Evaluation of Optimal Control for Ice-based Thermal Energy Storage Systems by : Dagfinn Bell
Download or read book Evaluation of Optimal Control for Ice-based Thermal Energy Storage Systems written by Dagfinn Bell and published by . This book was released on 1998 with total page 474 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Intelligent Control System Design for Energy Conservation in Commercial Buildings by : Hao Huang
Download or read book Intelligent Control System Design for Energy Conservation in Commercial Buildings written by Hao Huang and published by . This book was released on 2016 with total page 221 pages. Available in PDF, EPUB and Kindle. Book excerpt: This thesis focuses on the development of model predictive control (MPC) strategies for reducing energy consumption in air-conditioned buildings. It is well known that the building sector is responsible for 40 per cent of the world's energy usage and 33 per cent of all greenhouse emissions. As a result of global environmental issues and decreasing energy resources, there is strong motivation to develop more efficient control strategies for Heating, Ventilation, and Air Conditioning (HVAC) systems in buildings. The existing HVAC control strategies are not energy or cost efficient, which results in energy waste, high on-peak electricity demand and poor thermal comfort in buildings. Previous works have shown that MPC can be utilised as a supervisory controller to achieve energy saving while maintaining the indoor thermal comfort in buildings. However, most of the past studies were focused on small residential buildings or mid-size commercial buildings. It is highly desired to improve the existing MPC strategies to make them more reliable and applicable for large commercial buildings. This thesis extends the previous works by addressing the following challenges when dealing with the large buildings. Firstly, HVAC plants and the thermal dynamics of buildings are inherently nonlinear. Accurate modelling of these components is difficult due to the limited number of sensors that are usually installed and the paucity of prior knowledge of the system. There is a need to develop models that are capable of effectively handling the nonlinearity to achieve better modelling accuracy. Secondly, in large commercial buildings with adjacent large open spaces, the effects of thermal coupling between differently controlled spaces play a crucial role. This significance of the interaction between zones has seldom been discussed before and requires more thorough investigation. Thirdly, although load shifting function of MPC have been proven to be effective in achieving cost savings in buildings with a considerable thermal mass, it is demanding to investigate the application value of these strategies in lightweight commercial buildings. Finally, given the presence of uncertainties, these models may not be able to predict the indoor temperature accurately, which may lead to poor control performance and even instability in operation of the MPC strategy. The existing robust control approaches are generally too conservative, and may not be suitable for use in real-world buildings. In this study, the advantages of neural networks (NNs) will be exploited to address the challenges outlined above. NNs are known as universal approximators, meaning that they can model any continuous functions with any desired degree of accuracy. In particular, the NNs will be used to conduct modelling work, generate control rule, and improve the performance of classical MPC. The major contributions of this thesis are presented in four chapters, with each based on an individual scientific paper. Paper-1 presents a systematic modelling method for air handling units (AHUs) and thermal zone using a recursive NN (RNN). As the major novelty, a cascade NN structure is developed, which enables the thermal dynamics modelling of both interior zones and perimeter zones within investigated building. This approach allows accurate prediction of both supply air temperature and zone temperature prediction, making it suitable for predictive control design. Continuing with the first paper, Paper-2 introduces a multi-input, multi-output (MIMO) model, which effectively models the convective heat exchange between open spaces within multi-zone commercial buildings. The proposed model allows closed-loop prediction for several adjacent zones simultaneously by considering their thermal interaction. A NN-based optimal start-stop control method is also developed in this paper to demonstrate the energy saving potential enabled by using the proposed predictive model. The NN models provide accurate prediction results, but they are in general difficult to optimise under an MPC framework. Paper-3 presents a hybrid MPC (HMPC), which combines the classic MPC with an inverse NN model. With the HMPC, the classical MPC based on linearised building model optimises the supplied cooling energy. The inverse NN model compensates the nonlinearity associated with the AHU process and generates more accurate control inputs. Simulations and experiments demonstrate the feasibility of the proposed method in achieving energy and cost reductions while maintaining good indoor thermal comfort in the investigated large commercial building. The MPC formulation in Paper-3 does not take the system uncertainty into account. In reality, however, the modelled building energy systems are always affected by uncertainties, so that the modelling errors become inevitable which cause control performance degradation to the MPC. Paper-4 considers the application of a robust MPC (RMPC) to handle the system uncertainty within buildings. In particular, an uncertainty estimator is developed based on the previously presented RNN model to provide uncertainty bound to the conventional closed-loop min-max RMPC. The newly developed bound estimator reduces the conservatism of the RMPC and achieves improved control performance. In conclusion, the research work presented in this thesis has made important contributions to the research of intelligent model predictive control for air-conditioning systems in commercial buildings. The methodologies developed in this thesis can be utilised for other buildings or for the control of other dynamic systems.
Book Synopsis Model Predictive Control for Energy Efficient Buildings by : Yudong Ma
Download or read book Model Predictive Control for Energy Efficient Buildings written by Yudong Ma and published by . This book was released on 2013 with total page 262 pages. Available in PDF, EPUB and Kindle. Book excerpt: The building sector consumes about 40% of energy used in the United States and is responsible for nearly 40% of greenhouse gas emissions. Energy reduction in this sector by means of cost-effective and scalable approaches will have an enormous economic, social, and environmental impact. Achieving substantial energy reduction in buildings may require to rethink the entire processes of design, construction, and operation of buildings. This thesis focuses on advanced control system design for energy efficient commercial buildings. Commercial buildings are plants that process air in order to provide comfort for their occupants. The components used are similar to those employed in the process industry: chillers, boilers, heat exchangers, pumps, and fans. The control design complexity resides in adapting to time-varying user loads as well as occupant requirements, and quickly responding to weather changes. Today this is easily achievable by over sizing the building components and using simple control strategies. Building controls design becomes challenging when predictions of weather, occupancy, re- newable energy availability, and energy price are used for feedback control. Green buildings are expected to maintain occupants comfort while minimizing energy consumption, being ro- bust to intermittency in the renewable energy generation and responsive to signals from the smart grid. Achieving all these features in a systematic and cost-effective way is challenging. The challenge is even greater when conventional systems are replaced by innovative heat- ing and cooling systems that use active storage of thermal energy with critical operational constraints. Model predictive control (MPC) is the only control methodology that can systematically take into account future predictions during the control design stage while satisfying the system operating constraints. This thesis focuses on the design and implementation of MPC for building cooling and heating systems. The objective is to develop a control methodology that can 1) reduce building energy consumption while maintaining indoor thermal comfort by using predictive knowledge of occupancy loads and weather information, (2) easily and systematically take into account the presence of storage devices, demand response signals from the grid, and occupants feedback, (3) be implemented on existing inexpensive and distributed building control platform in real-time, and (4) handle model uncertainties and prediction errors both at the design and implementation stage. The thesis is organized into six chapters. Chapter 1 motivates our research and reviews existing control approaches for building cooling and heating systems. Chapter 2 presents our approach to developing low-complexity control oriented models learned from historical data. Details on models for building components and spaces thermal response are provided. The thesis focuses on the dynamics of both the energy conversion and storage as well as energy distribution by means of heating ventilation and air conditioning (HVAC) systems. In Chapter 3, deterministic model predictive control problems are formulated for the en- ergy conversion systems and energy distribution systems to minimize the energy consumption while maintaining comfort requirement and operational constraints. Experimental and simu- lative results demonstrate the effectiveness of the MPC scheme, and reveal significant energy reduction without compromising indoor comfort requirement. As the size and complexity of buildings grow, the MPC problem quickly becomes com- putationally intractable to be solved in a centralized fashion. This limitation is addressed in Chapter 4. We propose a distributed algorithm to decompose the MPC problem into a set of small problems using dual decomposition and fast gradient projection. Simulation results show good performance and computational tractability of the resulting scheme. The MPC formulation in Chapter 3 and 4 assumes prefect knowledge of system model, load disturbance, and weather. However, the predictions in practice are different from actual realizations. In order to take into account the prediction uncertainties at control design stage, stochastic MPC (SMPC) is introduced in Chapter 5 to minimize expected costs and satisfy constraints with a given probability. In particular, the proposed novel SMPC method applies feedback linearization to handle system nonlinearity, propagates the state statistics of linear systems subject to finite-support (non Gaussian) disturbances, and solves the resulting optimization problem by using large-scale nonlinear optimization solvers.
Book Synopsis Heat Storage Systems for Buildings by : Ibrahim Dincer
Download or read book Heat Storage Systems for Buildings written by Ibrahim Dincer and published by Elsevier. This book was released on 2021-08-04 with total page 320 pages. Available in PDF, EPUB and Kindle. Book excerpt: Heat Storage Systems for Buildings provides a unique resource for researchers, scientists, engineers, students, sectoral professional and people who work in the area of heat storage systems and applications for buildings. This book will further provide theoretical and practical materials, systems, applications, case studies and examples about various potential options for buildings. The primary focus is on thermodynamic analyses, performance evaluation, lifecycle assessment, environmental impact assessment and sustainability development criteria. - Includes case studies and examples explain various potential options for buildings - Examines, in detail, the design of heat storage methods - Presents environmental impact assessment and sustainability development criteria - Contains a section on artificial intelligence techniques and estimation methods in heat storage
