Modeling Power Electronics and Interfacing Energy Conversion Systems

M. Godoy Simoes, Felix A. Farret

• Publisher: Wiley-IEEE Press
• Year: 2016
• ISBN:
  9781119058472
• Edition: 1
• Topic: Technology & Engineering
• Subtopic: Power Resources
• Index: Technology & Engineering

Discusses the application of mathematical and engineering tools for modeling, simulation and control oriented for energy systems, power electronics and renewable energy

This book builds on the background knowledge of electrical circuits, control of dc/dc converters and inverters, energy conversion and power electronics. The book shows readers how to apply computational methods for multi-domain simulation of energy systems and power electronics engineering problems. Each chapter has a brief introduction on the theoretical background, a description of the problems to be solved, and objectives to be achieved. Block diagrams, electrical circuits, mathematical analysis or computer code are covered. Each chapter concludes with discussions on what should be learned, suggestions for further studies and even some experimental work.

• Discusses the mathematical formulation of system equations for energy systems and power electronics aiming state-space and circuit oriented simulations
• Studies the interactions between MATLAB and Simulink models and functions with real-world implementation using microprocessors and microcontrollers
• Presents numerical integration techniques, transfer-function modeling, harmonic analysis and power quality performance assessment
• Examines existing software such as, MATLAB/Simulink, Power Systems Toolbox and PSIM to simulate power electronic circuits including the use of renewable energy sources such as wind and solar sources

The simulation files are available for readers who register with the Google Group: [e-mail]. After your registration you will receive information in how to access the simulation files, the Google Group can also be used to communicate with other registered readers of this book.

1
INTRODUCTION TO ELECTRICAL ENGINEERING SIMULATION

Theoretical modeling‐based analysis is a process where a model is set up based on laws of nature and logic, using mostly mathematics, physics, and engineering—initially with simplified assumptions about their processes and aiming at finding an input/output model. The following basic procedures and formulations are usually used in supporting a theoretical or an experimental model:

1. Balance equations, for stored masses, energies, and impulses
2. Physical–chemical constitutive equations
3. Phenomenological equations of irreversible processes (thermal conductivity, diffusion, chemical reaction)
4. Entropy balance equations, if several irreversible processes are interrelated
5. Connection equations, describing the interconnection of process elements

Using such formulation principles, a system can be understood in terms of their ordinary differential equations, or their algebraic equations, and then a physical device or a computer simulation or an emulation can be devised in order to obey such equations. The physical system is initialized with their proper initial values, and their development over time mimics the differential equations.

Integrators and function generation can accomplish simulation of an ordinary differential equation (ODE). It has been discussed by Ragazzini in 1947 that the continuous functions of several variables could be approximated by a combination of scalar products, scalar functions, and their time derivatives. We have to find first suitable state variables, i.e. variables that account for energy storage. Typically those variables appear differentiated in the ordinary differential equations.

Several computer‐based simulations depend on the principles of analog computing, where a differential equation such as Equation 1.1 must be represented in terms of fundamental operations such as integration, addition, multiplication, and function generation. The old analog computer circuitry required scaling of variables, but in a modern computer, floating‐point numbers represents the variables and scaling is not required. Higher precision, flexibility for modifications, better stability, reporting facilities, and lower costs are the main advantages of the digital processing. The analog computing may have an advantage for high‐speed online data processing, for example, a voltage across a resistor has immediate response. A function such as the one represented by Equation 1.1 requires several interconnections to represent the required calculations.

(1.1)

Numerical solution techniques and algorithms to solve differential equation are essential and used in digital computers. There are many ways to find approximate numerical solutions to ordinary differential equations such as the one represented by Equation 1.1. The methods are based on replacing the differential equations by a difference equation. Euler’s method is based on the approximation of the derivative by a first‐order difference, but there are more efficient techniques such as Runge–Kutta and multistep methods. These methods were well known when digital simulators emerged in the 1960s, but several contributions made them better and more stable when solving difference approximations, for example, the automatic step length adjustment was a very important contribution. A more mathematical‐oriented model for dynamical systems can be based on differential–algebraic equations (DAEs), that is, a mixture of diffe...