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2023 | Book

Micro-grid Introduction and Overview Read chapter Read first chapter

Design and Development of Model Predictive Primary Control of Micro Grids

Simulation Examples in MATLAB

Authors: Puvvula Vidyasagar, K. Shanti Swarup

Publisher: Springer Nature Singapore

Book Series : Springer Tracts in Electrical and Electronics Engineering

Part of: Springer Professional "Wirtschaft+Technik" , Springer Professional "Technik"

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About this book

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.

Table of Contents

Frontmatter
Chapter 1. Micro-grid Introduction and Overview
Abstract
The chapter provides a detailed explanation about the reasons for the evolution of micro-grids. The conventional power system components, its architecture, and the challenges it poses in the modern-day power sector are discussed in Sect. 1.1. The concept of distributed generator (DG) and the typical components involved in a DG are explained in the Sect. 1.2. The role of DG in overcoming some of the challenges posed by the conventional power systems is explained in Sect. 1.3. However, a single DG always has its demerits when operated in either standalone or grid-connected modes. These demerits are discussed in Sect. 1.4. The concept of micro-grid, its definitions, and its ability to overcome the demerits of a single DG are discussed in Sect. 1.5. Section 1.6 provides a detailed explanation about different components involved in the modern-day micro-grid. The advantages, challenges, and operational modes of a micro-grid are explained in Sects. 1.7, 1.8, and 1.9, respectively.
Puvvula Vidyasagar, K. Shanti Swarup
Chapter 2. An Overview of Micro-grid Control
Abstract
The chapter provides a detailed overview of micro-grid control. The control objectives of a control system in the micro-grid are different for different operational modes. Section 2.1 provides an elaborate explanation of the control objectives of the micro-grid in both grid-connected and islanded modes. Section 2.2 explains different control architectures that are possibly employed to achieve the desired objectives. The section explains the underlying principles, pros, and cons of centralized architecture, decentralized architecture, and hierarchical architecture. Section 2.3 is completely dedicated to hierarchical architecture. The section explains the different control levels involved in the hierarchical architecture, the objectives of each control level, and the methodologies that can be used to achieve these objectives.
Puvvula Vidyasagar, K. Shanti Swarup
Chapter 3. Mathematical Modelling of a Micro-grid
Abstract
A generic modern-day micro-grid is of mixed nature. It should comprise both linear and nonlinear constituents in it. By this it means that the dynamical mathematical models of generators and loads should comprise both linear and nonlinear differential equations. It comprises rotating and non-rotating generators. This generally means presence of inertia in some generators like synchronous generators and induction generators, and the non-inertia generators like solar photovoltaic, battery energy storage systems, and fuel cell. It comprises rotating and non-rotating loads. This generally means presence of both static loads and rotating loads like induction motors and synchronous motors. It comprises both conventional synchronous generators and modern-day electronically interfaced generators like DGs with single inverter and DGs with back-to-back AC–DC–AC converters. It should contain buses that form or define the grid-connected mode, and a group of buses that can operate in the islanded mode in case grid-connected buses are disconnected from them. This chapter is all about detailed modelling of such a generic modern-day micro-grid which is the most important aspect for the design of the model predictive controller.
Puvvula Vidyasagar, K. Shanti Swarup
Chapter 4. Introduction to Model Predictive Control
Abstract and Brief Introduction to MPC
Model predictive control (MPC) is one of the advanced techniques in industrial control that is gaining more focus in the modern optimal control literature. So far, it has found a lot of real-time applications in many important industries and was successfully implemented as an online controller (Fernandez-Camacho and Bordons-Alba, Model predictive control in the process industry, Springer, London, 1995). This chapter provides a glimpse of its functioning styles and designs to the readers.
Puvvula Vidyasagar, K. Shanti Swarup
Chapter 5. LTI-MPC for the Micro-grid Control
Abstract
The micro-grid models in general are highly nonlinear. A centralized model predictive controller (MPC) for the primary control of micro-grids is a wonderful choice in terms of performance. However, the optimal control problem of a centralized MPC with a nonlinear model of the micro-grid is a non-convex nonlinear optimization problem. Solving such a problem online is very difficult with the rapid sampling rate requirements of the primary control level of a micro-grid. To deal with the non-convex nature of the optimal control problem, an MPC design that uses a linear time-invariant (LTI) approximation of the nonlinear micro-grid model is discussed in this chapter. The MPC design is referred to as linear time-invariant MPC (LTI-MPC). The optimal control problem of this LTI-MPC is a quadratic programming problem, which is convex with polynomial time complexity. The inspiration for the LTI-MPC is drawn from the references (Megias et al. in 1999 European control conference (ECC), pp 2707–2712, 1999; Blet et al. in IFAC Proc 35(1)L147–152, 2002; Ławryńczuk in Int J Appl Math Comput Sci 25(4):833–847, 2015; Vidyasagar and Swarup in 2016 National Power Systems Conference (NPSC), pp 1–6, 2016; Sagar and Swarup in 2016 IEEE International Conference on Power Electronics, Drives and Energy Systems (PEDES), pp 1–6, 2016) given at the end of the chapter.
Puvvula Vidyasagar, K. Shanti Swarup
Chapter 6. LTV-MPC with Extended “TAIL”
Abstract
MPC with LTI approximation of the nonlinear model of the micro-grid is fairly simple and easy to implement. However, the LTI model is generally inaccurate and closely approximates the nonlinear model only in the small neighbourhood of the operating point around which the linearization is performed. The LTI model deviates from the original nonlinear model with an increase in the prediction horizon length Np. Hence the LTI-MPC is limited to small prediction horizons. When a load disturbance or source intermittency occurs in the micro-grid, LTI-MPC indeed controls the micro-grid and moves it towards the new steady-state. However, it leads to large oscillatory transient response and large settling times due to the highly inaccurate prediction. Due to the receding horizon principle, control inputs that correspond to the present sample are chosen from the optimal control trajectories generated at each sample. The rest of the trajectories (“tail”) are neglected. This is a waste of information that is optimal in some sense. A linear time-variant MPC (LTV-MPC) with an extended “tail” for the primary control of micro-grids is discussed in this chapter to tackle the difficulties mentioned above. The inspiration for the LTV-MPC is drawn from Kouvaritakis et al. (Int J Control 72:919–928, 1999) given at the end of the chapter. Puvvula et al. (IET Renew Power Gener 14:2221–2231, 2020) gives a detailed insight into different aspects of the LTV-MPC which forms the crux of this chapter.
Puvvula Vidyasagar, K. Shanti Swarup
Chapter 7. Special Functions in the MPC Formulation
Abstract
In the LTI-MPC and LTV-MPC formulations discussed in the previous chapters, the number of optimal variables that are to be evaluated at each sampling instant increases with an increase in the length of the control horizon Nc and the number of control inputs nip in the micro-grid model. Orthonormal special functions are employed for approximating the original pulse operator-based control trajectories within the control horizon. The approximation aims to decrease the number of decision variables (optimal variables) in the optimal control problem without compromising the controller's performance. Two kinds of special functions, namely Laguerre functions and two-parameter Kautz functions, are employed in this chapter.
Puvvula Vidyasagar, K. Shanti Swarup
Chapter 8. Auxiliary Requirements for Real-Time Implementation
Abstract
So far the book discussed the theoretical aspects of the MPC formulations for the micro-grid control at the primary control level. However, it is necessary to discuss some of the important requirements, referred to as the auxiliary requirements for the effective online implementation of the MPC formulations. The requirements comprise:
  • Scalability
  • Harmonics
  • State estimation
  • Choice of a particular MPC formulation
    • Based on computational complexity
    • Based on the performance comparison
  • Robustness.
This chapter puts more focus on the choice among the MPC formulations and the incorporation of the robust features into the MPC formulations. The other three requirements, namely scalability, harmonics, and state estimation are briefly discussed in this chapter.
Puvvula Vidyasagar, K. Shanti Swarup
Chapter 9. Conclusion and Future Scope
Abstract
The foundation of this book fundamentally lies in the fact that in a hierarchical control of the micro-grid, an advanced controller called MPC is superior in performance compared to the conventional micro-gird controllers. The superiority of the MPC at the secondary control level was already a thoroughly discussed topic in the micro-grid literature. But its application at the primary control level of a micro-grid is still a point of discussion. The MPC at the micro-grid primary level is decentralized in nature and restricted only to the linear models of the micro-grid constituents. The major implementation issue with the MPC at the primary control level of a micro-grid arises from the nonlinearity of the micro-grid model and the necessity for a centralized MPC architecture that facilitates the use of large prediction and control horizons. This book focused on the MPC formulations for centralized primary control of the micro-grids with nonlinear models.
Puvvula Vidyasagar, K. Shanti Swarup
Metadata
Title
Design and Development of Model Predictive Primary Control of Micro Grids
Authors
Puvvula Vidyasagar
K. Shanti Swarup
Copyright Year
2023
Publisher
Springer Nature Singapore
Electronic ISBN
978-981-19-5852-6
Print ISBN
978-981-19-5851-9
DOI
https://doi.org/10.1007/978-981-19-5852-6