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Author: José Augustín Candanedo Ibarra
Publisher:
ISBN:
Category :
Languages : en
Pages : 286
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Book Description
This thesis investigates the development of predictive control strategies for optimally or near-optimally designed solar homes. Optimal design refers to the integration of renewable energy technologies (mainly active and passive solar) with a high-quality building envelope as well as efficiency and conservation measures to achieve substantial reductions in energy consumption and peak demand. Effective implementation of these technologies requires an integrated design approach, which considers their interactions with the building and its services. Furthermore, control strategies must be an essential part of the integrated design of a building to improve energy performance and ensure occupant comfort. In optimally designed solar homes, control strategies should incorporate the collection, storage and delivery of solar energy. Weather forecasts along with an understanding of the building's thermal dynamics (e.g., time delays due to thermal mass) enable predicting and managing loads and solar energy availability. Design and operation strategies of a case study, the Alstonvale House, are presented. Features of this house include passive solar design, a building-integrated photovoltaic/thermal (BIPV/T) system coupled with a solar-assisted heat pump, a thermal energy storage tank and a radiant floor heating system in a thermally massive concrete slab. Design and control approaches developed for the Alstonvale House provided the basis for generalized control strategies applicable to optimally designed solar homes. Simplified building models, which can be derived from more detailed models or on-site measurements, can facilitate the implementation of predictive control techniques. In this investigation, model-based predictive control was applied to a radiant floor heating system and the position of roller blinds in a room with high solar gains. Predictive control can also be applied to optimize the operation of renewable energy systems. In this study, forecasts of heating loads and solar radiation were used in a dynamic programming algorithm to select a near-optimal set-point trajectory for an energy storage tank heated with a heat pump assisted by a BIPV/T system.
Author: José Augustín Candanedo Ibarra
Publisher:
ISBN:
Category :
Languages : en
Pages : 286
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Book Description
This thesis investigates the development of predictive control strategies for optimally or near-optimally designed solar homes. Optimal design refers to the integration of renewable energy technologies (mainly active and passive solar) with a high-quality building envelope as well as efficiency and conservation measures to achieve substantial reductions in energy consumption and peak demand. Effective implementation of these technologies requires an integrated design approach, which considers their interactions with the building and its services. Furthermore, control strategies must be an essential part of the integrated design of a building to improve energy performance and ensure occupant comfort. In optimally designed solar homes, control strategies should incorporate the collection, storage and delivery of solar energy. Weather forecasts along with an understanding of the building's thermal dynamics (e.g., time delays due to thermal mass) enable predicting and managing loads and solar energy availability. Design and operation strategies of a case study, the Alstonvale House, are presented. Features of this house include passive solar design, a building-integrated photovoltaic/thermal (BIPV/T) system coupled with a solar-assisted heat pump, a thermal energy storage tank and a radiant floor heating system in a thermally massive concrete slab. Design and control approaches developed for the Alstonvale House provided the basis for generalized control strategies applicable to optimally designed solar homes. Simplified building models, which can be derived from more detailed models or on-site measurements, can facilitate the implementation of predictive control techniques. In this investigation, model-based predictive control was applied to a radiant floor heating system and the position of roller blinds in a room with high solar gains. Predictive control can also be applied to optimize the operation of renewable energy systems. In this study, forecasts of heating loads and solar radiation were used in a dynamic programming algorithm to select a near-optimal set-point trajectory for an energy storage tank heated with a heat pump assisted by a BIPV/T system.
Author: Andreas Athienitis
Publisher: John Wiley & Sons
ISBN: 3433604630
Category : Technology & Engineering
Languages : en
Pages : 396
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Book Description
Building energy design is currently going through a period of major changes. One key factor of this is the adoption of net-zero energy as a long term goal for new buildings in most developed countries. To achieve this goal a lot of research is needed to accumulate knowledge and to utilize it in practical applications. In this book, accomplished international experts present advanced modeling techniques as well as in-depth case studies in order to aid designers in optimally using simulation tools for net-zero energy building design. The strategies and technologies discussed in this book are, however, also applicable for the design of energy-plus buildings. This book was facilitated by International Energy Agency's Solar Heating and Cooling (SHC) Programs and the Energy in Buildings and Communities (EBC) Programs through the joint SHC Task 40/EBC Annex 52: Towards Net Zero Energy Solar Buildings R&D collaboration. After presenting the fundamental concepts, design strategies, and technologies required to achieve net-zero energy in buildings, the book discusses different design processes and tools to support the design of net-zero energy buildings (NZEBs). A substantial chapter reports on four diverse NZEBs that have been operating for at least two years. These case studies are extremely high quality because they all have high resolution measured data and the authors were intimately involved in all of them from conception to operating. By comparing the projections made using the respective design tools with the actual performance data, successful (and unsuccessful) design techniques and processes, design and simulation tools, and technologies are identified. Written by both academics and practitioners (building designers) and by North Americans as well as Europeans, this book provides a very broad perspective. It includes a detailed description of design processes and a list of appropriate tools for each design phase, plus methods for parametric analysis and mathematical optimization. It is a guideline for building designers that draws from both the profound theoretical background and the vast practical experience of the authors.
Author: Carlos Bordons
Publisher: Springer Nature
ISBN: 3030245705
Category : Technology & Engineering
Languages : en
Pages : 266
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Book Description
The book shows how the operation of renewable-energy microgrids can be facilitated by the use of model predictive control (MPC). It gives readers a wide overview of control methods for microgrid operation at all levels, ranging from quality of service, to integration in the electricity market. MPC-based solutions are provided for the main control issues related to energy management and optimal operation of microgrids. The authors present MPC techniques for case studies that include different renewable sources – mainly photovoltaic and wind – as well as hybrid storage using batteries, hydrogen and supercapacitors. Experimental results for a pilot-scale microgrid are also presented, as well as simulations of scheduling in the electricity market and integration of electric and hybrid vehicles into the microgrid. in order to replicate the examples provided in the book and to develop and validate control algorithms on existing or projected microgrids. Model Predictive Control of Microgrids will interest researchers and practitioners, enabling them to keep abreast of a rapidly developing field. The text will also help to guide graduate students through processes from the conception and initial design of a microgrid through its implementation to the optimization of microgrid management. Advances in Industrial Control reports and encourages the transfer of technology in control engineering. The rapid development of control technology has an impact on all areas of the control discipline. The series offers an opportunity for researchers to present an extended exposition of new work in all aspects of industrial control.
Author: Stéphane Vannitsem
Publisher: Elsevier
ISBN: 012812248X
Category : Science
Languages : en
Pages : 364
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Book Description
Statistical Postprocessing of Ensemble Forecasts brings together chapters contributed by international subject-matter experts describing the current state of the art in the statistical postprocessing of ensemble forecasts. The book illustrates the use of these methods in several important applications including weather, hydrological and climate forecasts, and renewable energy forecasting. After an introductory section on ensemble forecasts and prediction systems, the second section of the book is devoted to exposition of the methods available for statistical postprocessing of ensemble forecasts: univariate and multivariate ensemble postprocessing are first reviewed by Wilks (Chapters 3), then Schefzik and Möller (Chapter 4), and the more specialized perspective necessary for postprocessing forecasts for extremes is presented by Friederichs, Wahl, and Buschow (Chapter 5). The second section concludes with a discussion of forecast verification methods devised specifically for evaluation of ensemble forecasts (Chapter 6 by Thorarinsdottir and Schuhen). The third section of this book is devoted to applications of ensemble postprocessing. Practical aspects of ensemble postprocessing are first detailed in Chapter 7 (Hamill), including an extended and illustrative case study. Chapters 8 (Hemri), 9 (Pinson and Messner), and 10 (Van Schaeybroeck and Vannitsem) discuss ensemble postprocessing specifically for hydrological applications, postprocessing in support of renewable energy applications, and postprocessing of long-range forecasts from months to decades. Finally, Chapter 11 (Messner) provides a guide to the ensemble-postprocessing software available in the R programming language, which should greatly help readers implement many of the ideas presented in this book. Edited by three experts with strong and complementary expertise in statistical postprocessing of ensemble forecasts, this book assesses the new and rapidly developing field of ensemble forecast postprocessing as an extension of the use of statistical corrections to traditional deterministic forecasts. Statistical Postprocessing of Ensemble Forecasts is an essential resource for researchers, operational practitioners, and students in weather, seasonal, and climate forecasting, as well as users of such forecasts in fields involving renewable energy, conventional energy, hydrology, environmental engineering, and agriculture. - Consolidates, for the first time, the methodologies and applications of ensemble forecasts in one succinct place - Provides real-world examples of methods used to formulate forecasts - Presents the tools needed to make the best use of multiple model forecasts in a timely and efficient manner
Author: Eduardo F. Camacho
Publisher: Springer Science & Business Media
ISBN: 1447130081
Category : Technology & Engineering
Languages : en
Pages : 250
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Book Description
Model Predictive Control is an important technique used in the process control industries. It has developed considerably in the last few years, because it is the most general way of posing the process control problem in the time domain. The Model Predictive Control formulation integrates optimal control, stochastic control, control of processes with dead time, multivariable control and future references. The finite control horizon makes it possible to handle constraints and non linear processes in general which are frequently found in industry. Focusing on implementation issues for Model Predictive Controllers in industry, it fills the gap between the empirical way practitioners use control algorithms and the sometimes abstractly formulated techniques developed by researchers. The text is firmly based on material from lectures given to senior undergraduate and graduate students and articles written by the authors.
Author: Manuel Berenguel
Publisher: Springer Science & Business Media
ISBN: 1447109813
Category : Technology & Engineering
Languages : en
Pages : 287
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Book Description
The series Advances in Industrial Control aims to report and encourage technology transfer in control engineering. The rapid development of control technology impacts all areas of the control discipline. New theory, new controllers, actuators, sensors, new industrial processes, computer methods, new applications, new philosophies ... , new challenges. Much of this development work resides in industrial reports, feasibility study papers and the reports of advanced collaborative projects. The series offers an opportunity for researchers to present an extended exposition of such new work in all aspects of industrial control for wider and rapid dissemination. This volume by Professor Eduardo F. Camacho and his colleagues Manuel Berenguel and Francisco R. Rubio is an exemplar of what an Advances in Industrial Control monograph should be. In it the control of a thermal solar facility is used to study the performance obtainable from an interesting range of control algorithms. These methods range from the conventional PID controller, through to model-based predictive and robust optimal control methods and finishing with two fuzzy logic based control techniques. The scientific methodology applied is modelling, simulation and plant implementation. In the last chapter, a rigorous approach for a comparative study is described involving a careful selection of performance metrics. The text is rich in relevant up-to-date source material, and contains many thought-provoking comments. The presentation is well-balanced, impartial and very readable.
Author: Ardeshir Mahdavi
Publisher: CRC Press
ISBN: 1315736950
Category : Technology & Engineering
Languages : en
Pages : 960
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Book Description
In the last two decades, the biannual ECPPM (European Conference on Product and Process Modelling) conference series has provided a unique platform for the presentation and discussion of the most recent advances with regard to the ICT (Information and Communication Technology) applications in the AEC/FM (Architecture, Engineering, Construction and
Author: Nassim Khaled
Publisher: Butterworth-Heinemann
ISBN: 0128139196
Category : Technology & Engineering
Languages : en
Pages : 264
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Book Description
Practical Design and Application of Model Predictive Control is a self-learning resource on how to design, tune and deploy an MPC using MATLAB® and Simulink®. This reference is one of the most detailed publications on how to design and tune MPC controllers. Examples presented range from double-Mass spring system, ship heading and speed control, robustness analysis through Monte-Carlo simulations, photovoltaic optimal control, and energy management of power-split and air-handling control. Readers will also learn how to embed the designed MPC controller in a real-time platform such as Arduino®. The selected problems are nonlinear and challenging, and thus serve as an excellent experimental, dynamic system to show the reader the capability of MPC. The step-by-step solutions of the problems are thoroughly documented to allow the reader to easily replicate the results. Furthermore, the MATLAB® and Simulink® codes for the solutions are available for free download. Readers can connect with the authors through the dedicated website which includes additional free resources at www.practicalmpc.com. - Illustrates how to design, tune and deploy MPC for projects in a quick manner - Demonstrates a variety of applications that are solved using MATLAB® and Simulink® - Bridges the gap in providing a number of realistic problems with very hands-on training - Provides MATLAB® and Simulink® code solutions. This includes nonlinear plant models that the reader can use for other projects and research work - Presents application problems with solutions to help reinforce the information learned
Author: Jiefeng Hu
Publisher: Energy Engineering
ISBN: 9781839533976
Category : Technology & Engineering
Languages : en
Pages : 300
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Book Description
Model predictive control (MPC) is a method for controlling a process while satisfying a set of constraints. The use of MPC for controlling power systems has been gaining traction in recent years. This work presents the use of MPC for distributed renewable power generation in microgrids.
Author: J.A. Rossiter
Publisher: CRC Press
ISBN: 135198859X
Category : Technology & Engineering
Languages : en
Pages : 323
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Book Description
Model Predictive Control (MPC) has become a widely used methodology across all engineering disciplines, yet there are few books which study this approach. Until now, no book has addressed in detail all key issues in the field including apriori stability and robust stability results. Engineers and MPC researchers now have a volume that provides a complete overview of the theory and practice of MPC as it relates to process and control engineering. Model-Based Predictive Control, A Practical Approach, analyzes predictive control from its base mathematical foundation, but delivers the subject matter in a readable, intuitive style. The author writes in layman's terms, avoiding jargon and using a style that relies upon personal insight into practical applications. This detailed introduction to predictive control introduces basic MPC concepts and demonstrates how they are applied in the design and control of systems, experiments, and industrial processes. The text outlines how to model, provide robustness, handle constraints, ensure feasibility, and guarantee stability. It also details options in regard to algorithms, models, and complexity vs. performance issues.
