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This book provides a design and development perspective MPC for micro-grid control, emphasizing step-by-step conversion of a nonlinear MPC to linear MPC preserving critical aspects of nonlinear MPC. The book discusses centralized and decentralized MPC control algorithms for a generic modern-day micro-grid consisting of vital essential constituents. It starts with the nonlinear MPC formulation for micro-grids. It also moves towards the linear time-invariant and linear time-variant approximations of the MPC for micro-grid control. The contents also discuss how the application of orthonormal special functions can improve computational complexity of MPC algorithms. It also highlights various auxiliary requirements like state estimator, disturbance compensator for robustness, selective harmonic eliminator for eliminating harmonics in the micro-grid, etc. These additional requirements are crucial for the successful online implementation of the MPC. In the end, the book shows how a well-designed MPC is superior in performance compared to the conventional micro-grid primary controllers discussed above. The key topics discussed in this book include – the detailed modeling of micro-grid components; operational modes in micro-grid and their control objectives; conventional micro-grid primary controllers; the importance of MPC as a micro-grid primary controller; understanding of MPC operation; nonlinear MPC formulation; linear approximations of MPC; application of special functions in the MPC formulation; and other online requirements for the MPC implementation. The examples in the book are available both from a calculation point of view and as MATLAB codes. This helps the students get acquainted with the subject first and then allows them to implement the subject they learn in software for further understanding and research.
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.
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.
This book provides a thorough understanding of the basic principles, synthesis, analysis, and control of virtual inertia systems. It uses the latest technical tools to mitigate power system stability and control problems under the presence of high distributed generators (DGs) and renewable energy sources (RESs) penetration. This book uses a simple virtual inertia control structure based on the frequency response model, complemented with various control methods and algorithms to achieve an adaptive virtual inertia control respect to the frequency stability and control issues. The chapters capture the important aspects in virtual inertia synthesis and control with the objective of solving the stability and control problems regarding the changes of system inertia caused by the integration of DGs/RESs. Different topics on the synthesis and application of virtual inertia are thoroughly covered with the description and analysis of numerous conventional and modern control methods for enhancing the full spectrum of power system stability and control. Filled with illustrative examples, this book gives the necessary fundamentals and insight into practical aspects. This book stimulates further research and offers practical solutions to real-world power system stability and control problems with respect to the system inertia variation triggered by the integration of RESs/DGs. It will be of use to engineers, academic researchers, and university students interested in power systems dynamics, analysis, stability and control.
"This reference book covers the latest innovations and trends within smart grid and microgrid development, detailing benefits, challenges, and opportunities, that will help readers to fully understand the current opportunities that smart grids and microgrids present around the world"--
Microgrids are the most innovative area in the electric power industry today. Future microgrids could exist as energy-balanced cells within existing power distribution grids or stand-alone power networks within small communities. A definitive presentation on all aspects of microgrids, this text examines the operation of microgrids – their control concepts and advanced architectures including multi-microgrids. It takes a logical approach to overview the purpose and the technical aspects of microgrids, discussing the social, economic and environmental benefits to power system operation. The book also presents microgrid design and control issues, including protection and explaining how to implement centralized and decentralized control strategies. Key features: original, state-of-the-art research material written by internationally respected contributors unique case studies demonstrating success stories from real-world pilot sites from Europe, the Americas, Japan and China examines market and regulatory settings for microgrids, and provides evaluation results under standard test conditions a look to the future – technical solutions to maximize the value of distributed energy along with the principles and criteria for developing commercial and regulatory frameworks for microgrids Offering broad yet balanced coverage, this volume is an entry point to this very topical area of power delivery for electric power engineers familiar with medium and low voltage distribution systems, utility operators in microgrids, power systems researchers and academics. It is also a useful reference for system planners and operators, manufacturers and network operators, government regulators, and postgraduate power systems students. CONTRIBUTORS Thomas Degner Aris Dimeas Alfred Engler Nuno Gil Asier Gil de Muro Guillermo Jiménez-Estévez George Kariniotakis George Korres André Madureira Meiqin Mao Chris Marnay Jose Miguel Yarza Satoshi Morozumi Alexander Oudalov Frank van Overbeeke Rodrigo Palma Behnke Joao Abel Pecas Lopes Fernanda Resende John Romankiewicz Christine Schwaegerl Nikos Soultanis Liang Tao Antonis Tsikalakis
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. The authors also provide a modular simulator to be run in MATLAB®/Simulink®, for readers to create their own microgrids using the blocks supplied, 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.
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.
The energy landscape is shifting toward renewable energy sources to mitigate climate change and reduce dependence on fossil fuels. The integration of renewable energy sources into the power grid presents various challenges, including uncertainty and variability of renewable energy sources, grid stability, and management of energy storage. Power system operation and optimization play a crucial role in managing the energy supply-demand balance, reducing operational costs, and improving the reliability of the power system. This call for papers aims to bring together the latest research and practical applications related to power system operation and optimization in the context of high penetration of renewable energy sources. We welcome contributions from researchers and practitioners from a broad range of disciplines to shed light on the challenges and opportunities associated with renewable energy integration in power systems. The objective of this Research Topic is to explore the latest advances in power system operation and optimization with a focus on the high penetration of renewable energy sources. We invite potential authors to submit articles for publication on the Research Topic of Frontiers in Energy Research on Power System Operation and Optimization Considering the High Penetration of Renewable Energy.