Design And Development Of Model Predictive Primary Control Of Micro Grids
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Design and Development of Model Predictive Primary Control of Micro Grids
Author: Puvvula Vidyasagar
language: en
Publisher: Springer Nature
Release Date: 2023-01-01
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.
Model Predictive Control of Microgrids
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 of Microgrids
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.