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Computers play an important role in the analyzing and designing of modern DC-DC power converters. This book shows how the widely used analysis techniques of averaging and linearization can be applied to DC-DC converters with the aid of computers. Obtained dynamical equations may then be used for control design.

This book presents physics-based models of bipolar power semiconductor devices and their implementation in MATLAB and Simulink. The devices are subdivided into different regions, and the operation in each region, along with the interactions at the interfaces which are analyzed using basic semiconductor physics equations that govern their behavior. The Fourier series solution is used to solve the ambipolar diffusion equation in the lightly doped drift region of the devices. In addition to the external electrical characteristics, internal physical and electrical information, such as the junction voltages and the carrier distribution in different regions of the device, can be obtained using the models.

This book presents the reader, whether an electrical engineering student in power electronics or a design engineer, a selection of power converter control problems and their basic digital solutions, based on the most widespread digital control techniques. The presentation is primarily focused on different applications of the same power converter topology, the half-bridge voltage source inverter, considered both in its single- and three-phase implementation. This is chosen as the test case because, besides being simple and well known, it allows the discussion of a significant spectrum of the most frequently encountered digital control applications in power electronics, from digital pulse width modulation (DPWM) and space vector modulation (SVM), to inverter output current and voltage control, ending with the relatively more complex VSI applications related to the so called smart-grid scenario. This book aims to serve two purposes: (1) to give a basic, introductory knowledge of the digital control techniques applied to power converters; and (2) to raise the interest for discrete time control theory, stimulating new developments in its application to switching power converters.

Wind power penetration is rapidly increasing in today's energy generation industry. In particular, the doubly-fed induction generator (DFIG) has become a very popular option in wind farms, due to its cost advantage compared with fully rated converter-based systems. Wind farms are frequently located in remote areas, far from the bulk of electric power users, and require long transmission lines to connect to the grid. Series capacitive compensation of DFIG-based wind farm is an economical way to increase the power transfer capability of the transmission line connecting the wind farm to the grid. For example, a study performed by ABB reveals that increasing the power transfer capability of an existing transmission line from 1300 MW to 2000 MW using series compensation is 90% less expensive than building a new transmission line. However, a factor hindering the extensive use of series capacitive compensation is the potential risk of subsynchronous resonance (SSR). The SSR is a condition where the wind farm exchanges energy with the electric network, to which it is connected, at one or more natural frequencies of the electric or mechanical part of the combined system, comprising the wind farm and the network, and the frequency of the exchanged energy is below the fundamental frequency of the system. This oscillatory phenomenon may cause severe damage in the wind farm, if not prevented. Therefore, this book studies the SSR phenomenon in a capacitive series compensated wind farm. A DFIG-based wind farm, which is connected to a series compensated transmission line, is considered as a case study. The book consists of two main parts:Small-signal modeling of DFIG for SSR analysis: This part presents a step-by-step tutorial on modal analysis of a DFIG-based series compensated wind farm using Matlab/Simulink. The model of the system includes wind turbine aerodynamics, a 6th order induction generator, a 2nd order two-mass shaft system, a 4th order series compensated transmission line, a 4th order rotor-side converter (RSC) controller and a 4th order grid-side converter (GSC) controller, and a 1st order DC-link model. The relevant modes are identified using participation factor analysis. Definition of the SSR in DFIG-based wind farms: This part mainly focuses on the identification and definition of the main types of SSR that occur in DFIG wind farms, namely: (1) induction generator effect (SSIGE), (2) torsional interactions (SSTI), and (3) control interactions (SSCI).

DC-DC converters have many applications in the modern world. They provide the required power to the communication backbones, they are used in digital devices like laptops and cell phones, and they have widespread applications in electric cars, to just name a few.DC-DC converters require negative feedback to provide a suitable output voltage or current for the load. Obtaining a stable output voltage or current in presence of disturbances such as: input voltage changes and/or output load changes seems impossible without some form of control.This book tries to train the art of controller design for DC-DC converters. Chapter 1 introduces the DC-DC converters briefly. It is assumed that the reader has the basic knowledge of DC-DC converter (i.e., a basic course in power electronics).The reader learns the disadvantages of open loop control in Chapter 2. Simulation of DC-DC converters with the aid of Simulink is discussed in this chapter as well. Extracting the dynamic models of DC-DC converters is studied in Chapter 3. We show how MATLAB and a software named KUCA can be used to do the cumbersome and error-prone process of modeling automatically. Obtaining the transfer functions using PSIM is studied as well.These days, softwares are an integral part of engineering sciences. Control engineering is not an exception by any means. Keeping this in mind, we design the controllers using MATLAB in Chapter 4.Finally, references are provided at the end of each chapter to suggest more information for an interested reader. The intended audiencies for this book are practice engineers and academians.

DC-DC converters require negative feedback to provide a suitable output voltage or current for the load. Obtaining a stable output voltage or current in the presence of disturbances like input voltage changes and/or output load changes seems impossible without some form of control.This book shows how simple controllers such as Proportional-Integral (PI) can turn into a robust controller by correct selection of its parameters. Kharitonov's theorem is an important tool toward this end.This book consist of two parts. The first part shows how one can obtain the interval plant model of a DC-DC converter. The second part introduces the Kharitonov's theorem. Kharitonov's theorem is an analysis tool rather than a design tool. Some case studies show how it can be used as a design tool.The prerequisite for reading this book is a first course on feedback control theory and power electronics.

Computers play an important role in the analyzing and designing of modern DC-DC power converters. This book shows how the widely used analysis techniques of averaging and linearization can be applied to DC-DC converters with the aid of computers. Obtained dynamical equations may then be used for control design.The book is composed of two chapters. Chapter 1 focuses on the extraction of control-to-output transfer function. A second-order converter (a buck converter) and a fourth-order converter (a Zeta converter) are studied as illustrative examples in this chapter. Both ready-to-use software packages, such as PLECS and MATLAB programming, are used throught this chapter.The input/output characteristics of DC-DC converters are the object of considerations in Chapter 2. Calculation of input/output impedance is done with the aid of MATLAB programming in this chapter. The buck, buck-boost, and boost converter are the most popular types of DC-DC converters and used as illustrative examples in this chapter.This book can be a good reference for researchers involved in DC-DC converters dynamics and control.

The efficiency of solar energy farms requires detailed analytics and information on each panel regarding voltage, current, temperature, and irradiance. Monitoring utility-scale solar arrays was shown to minimize the cost of maintenance and help optimize the performance of the photo-voltaic arrays under various conditions. We describe a project that includes development of machine learning and signal processing algorithms along with a solar array testbed for the purpose of PV monitoring and control. The 18kW PV array testbed consists of 104 panels fitted with smart monitoring devices. Each of these devices embeds sensors, wireless transceivers, and relays that enable continuous monitoring, fault detection, and real-time connection topology changes. The facility enables networked data exchanges via the use of wireless data sharing with servers, fusion and control centers, and mobile devices. We develop machine learning and neural network algorithms for fault classification. In addition, we use weather camera data for cloud movement prediction using kernel regression techniques which serves as the input that guides topology reconfiguration. Camera and satellite sensing of skyline features as well as parameter sensing at each panel provides information for fault detection and power output optimization using topology reconfiguration achieved using programmable actuators (relays) in the SMDs. More specifically, a custom neural network algorithm guides the selection among four standardized topologies. Accuracy in fault detection is demonstrate at the level of 90+% and topology optimization provides increase in power by as much as 16% under shading.

This book presents physics-based electro-thermal models of bipolar power semiconductor devices including their packages, and describes their implementation in MATLAB and Simulink. It is a continuation of our first book Modeling of Bipolar Power Semiconductor Devices. The device electrical models are developed by subdividing the devices into different regions and the operations in each region, along with the interactions at the interfaces, are analyzed using the basic semiconductor physics equations that govern device behavior. The Fourier series solution is used to solve the ambipolar diffusion equation in the lightly doped drift region of the devices. In addition to the external electrical characteristics, internal physical and electrical information, such as junction voltages and carrier distribution in different regions of the device, can be obtained using the models. The instantaneous dissipated power, calculated using the electrical device models, serves as input to the thermal model (RC network with constant and nonconstant thermal resistance and thermal heat capacity, or Fourier thermal model) of the entire module or package, which computes the junction temperature of the device. Once an updated junction temperature is calculated, the temperature-dependent semiconductor material parameters are re-calculated and used with the device electrical model in the next time-step of the simulation. The physics-based electro-thermal models can be used for optimizing device and package design and also for validating extracted parameters of the devices. The thermal model can be used alone for monitoring the junction temperature of a power semiconductor device, and the resulting simulation results used as an indicator of the health and reliability of the semiconductor power device.