Solar PV and Wind Energy Conversion Systems: An Introduction to Theory, Modeling with MATLAB/SIMULINK, and the Role of Soft Computing Techniques

by S. Sumathi, L. Ashok Kumar, P. Surekha

Overview

This textbook starts with a review of the principles of operation, modeling and control of common solar energy and wind-power generation systems before moving on to discuss grid compatibility, power quality issues and hybrid models of Solar PV and Wind Energy Conversion Systems (WECS). MATLAB/SIMULINK models of fuel cell technology and associated converters are discussed in detail. The impact of soft computing techniques such as neural networks, fuzzy logic and genetic algorithms in the context of solar and wind energy is explained with practical implementation using MATLAB/SIMULINK models.

This book is intended for final year undergraduate, post-graduate and research students interested in understanding the modeling and control of Solar PV and Wind Energy Conversion Systems based on MATLAB/SIMULINK.

- Each chapter includes “Learning Objectives” at the start, a “Summary” at the end and helpful Review Questions

- Includes MATLAB/SIMULINK models of different control strategies for power conditioning units in the context of Solar PV

- Presents soft computing techniques for Solar PV and WECS, as well as MATLAB/SIMULINK models, e.g. for wind turbine topologies and grid integration

- Covers hybrid solar PV and Wind Energy Conversion Systems with converters and MATLAB/SIMULINK models

- Reviews harmonic reduction in Solar PV and Wind Energy Conversion Systems in connection with power quality issues

- Covers fuel cells and converters with implementation using MATLAB/SIMULINK

Product Details

ISBN-13:	9783319149417
Publisher:	Springer-Verlag New York, LLC
Publication date:	04/08/2015
Series:	Green Energy and Technology
Sold by:	Barnes & Noble
Format:	eBook
File size:	24 MB
Note:	This product may take a few minutes to download.

About the Author

Dr.S. Sumathi has pursued her B.E. (Electronics and Communication Engineering), M.E. (Applied Electronics) and PhD (Data Mining). She has a teaching experience of 24 years. Currently she is an Associate Professor in the Department of Electrical and Electronics Engineering, PSG College of Technology, Coimbatore. She has published about 46 Technical papers in reputed National and International Journals and 52 papers in National and International Conferences. In addition, she has authored 5 books with leading publishers like Springer-Verlag and CRC press. She is a recipient of several awards from Institution of Engineers and ISTE. Her areas of specialization are Neural Networks, Fuzzy Systems and Genetic Algorithms, Pattern Recognition and Classification, Data Warehousing and Data Mining, Operating systems and Parallel Computing.

Dr. L. Ashok Kumar has completed his B.E. (EEE), ME (Electrical Machines) MBA (HRM) PhD (Wearable Electronics). He has both teaching and industrial experience of 17 years. At present he is working as a Professor in the Dept. of EEE, PSG College of Technology, Coimbatore. He has got 16 research projects from various Government funding agencies. He has published 72 Technical papers in reputed National and International Journal and presented 77 research articles in International and National Conferences. He is a recipient of many National and International Awards. He is a member of various National & International Technical bodies like ISTE, IETE, TSI, BMSI, ISSS, SESI, SSI CSI & TAI. His areas of specializations are Wearable Electronics, Power Electronics & Drives and Renewable Energy Systems.

Dr. P. Surekha completed her B.E. (Electrical and Electronics Engineering), M.E. (Control Systems) and Ph.D (Computational Intelligence). Her experience includes 10 years with a combination of teaching and industry. She is presently working in the Department of Electrical and Electronics Engineering, PES University, Bangalore. She has published 22 technical papers in International Journals and 16 papers in National and International conferences. Along with journals, to her credit, she has published 3 books with publishers like Springer-Verlag and CRC Press. Her areas of interest include Robotics, Virtual Instrumentation, Mobile Communication and Computational Intelligence.

Table of Contents

1.      INTRODUCTION

1.1.            What is Energy?

1.1.1.      The Energy Scenario

1.1.2.      Energy crisis – Global and Indian

1.2.            Energy Efficiency

1.2.1.      Efficient Energy Use

1.3.            Classification of Energy Sources

1.4.            Solar Photovoltaics

1.4.1.      Solar radiation

1.4.2.      Measurement of Solar Radiation

1.5.            Wind Energy

1.5.1.      Renewable Energy in the 12th Five-Year Plan [2012-2017]

1.5.2.      Barriers to achieving higher growth

1.6.            Benefits of Renewable Energy Sources

1.7.            Trends in Energy Consumption

1.7.1.      Annual Energy Consumption

1.7.2.      RES in INDIA

1.7.3.      National Policy Measures supporting Renewables

1.7.4.      Renewable Energy Law

1.7.5.      Generation Based Incentive

1.7.6.      Renewable Energy Certificate scheme

1.7.7.      National Clean Energy Fund

1.7.8.      Other initiatives: Renewable Regulatory Fund Mechanism

1.7.9.      Land allocation policy

1.7.10.  Grid Integration Issues

1.7.11.  Grid transmission planning process

1.7.12.  Interconnection standards

1.7.13.  Green Energy Corridor

1.7.14.  India Smart Grid Task Force

1.8.            Worldwide Potentials of Renewable Energy Sources

1.9.            Need for New Energy Technologies       

1.10.        Introduction to MATLAB and SIMULINK

1.11.        Introduction to Soft Computing

1.11.1.  Soft Computing techniques

1.11.2.  Applications of soft computing techniques in solar energy

1.11.3.  Applications of Soft computing techniques in wind energy

Summary

Review Questions

 

2.      APPLICATION OF MATLAB/SIMULINK IN SOLAR PV SYSTEMS

2.1.            Basics of Solar PV

2.2.            PV Module Performance Measurements

2.2.1.      Balance of system and applicable Standards

2.2.2.      Photovoltaic Systems Total Costs Overview

2.3.            Types of PV Systems

2.4.            MATLAB Model of Solar PV

2.4.1.      SIMULINK model of PV module

2.4.2.      SIMULINK model for PV Array

2.4.3.      SIMULINK model to find shading effect

2.5.            Charge Controller

2.5.1.      Batteries in PV Systems

2.5.2.      Battery Types and Classifications

2.5.3.      Battery Charging

2.5.4.      Battery Discharging

2.5.5.      Battery Gassing and Overcharge Reaction

2.5.6.      Charge Controller Types

2.5.7.      Charge Controller Selection

2.5.8.      Operating Without a Charge Controller

2.5.9.      Using Low-Voltage “Self-Regulating” Modules

2.5.10.  Using a Large Battery or Small Array

2.6.            MATLAB Model of SOC

2.7.            MATLAB Model of Charge Controller

2.8.            Inverter

2.9.            MATLAB/SIMULINK Model of Inverter

2.10.        Maximum Power Point Tracking

2.11.        MATLAB/SIMULINK Model of MPPT

2.11.1.  MPPT Techniques

2.11.2.  MATLAB/SIMULINK implementation of perturb and observe method

2.11.3.  MATLAB/SIMULINK model of the incremental conductance method

2.11.4.  PV module with MPPT techniques

Summary

Review Questions

 

                         

3.      SOFT COMPUTING TECHNIQUES IN SOLAR PV

3.1.            Introduction

3.2.            MPPT USING FUZZY LOGIC

3.2.1.      Implementation

3.2.2.      Description and Design of FLC

3.2.3.      Simulation and Results

3.3.            NEURAL NETWORKS FOR MPP TRACKING

3.3.1.      Background of Neural Networks

3.3.2.      Implementation

3.3.3.      Algorithm For ANN Based MPPT

3.3.4.      Simulation Results

3.4.            EURO-FUZZY BASED MPPT METHOD

3.4.1.      Fuzzy Neural Network Hybrids

3.4.2.      Theoretical Background of ANFIS

3.4.3.      Architecture of adaptive Neuro-Fuzzy inference system

3.4.4.      Hybrid learning algorithm

3.4.5.      Neuro-Fuzzy Network Model and Calculation Algorithm

3.4.6.      ANFIS Network Specifications

3.4.7.      Algorithm For Neuro-Fuzzy Based MPPT

3.4.8.      Results For Neuro-Fuzzy Based MPPT

3.5.            FUZZY BASED SOLAR TRACKING

3.5.1.      Design Process of the Fuzzy Controller

3.5.2.      SIMULINK MODEL

3.5.3.      Simulation Results of Solar Tracking System         

3.6.            MATLAB/SIMULINK Model of Two Axis Sun Tracker using Fuzzy Logic

3.6.1.      Sensors

3.6.2.      Design of FLC for Sun Tracking System

3.6.3.      SIMULINK Model and Results of FLC based Sun Tracker System

3.7.            FLC for Solar Powered Energy

3.7.1.      Methodology

3.7.2.      Theoretical Explanation

3.7.3.      SIMULINK Model of FLC blocks

3.7.4.      Simulation Results

3.8.            Fuzzy Optimization for Solar Array System

3.8.1.      Photovoltaic Systems

3.8.2.      Peak-Power-Transfer Search

3.8.3.      Fuzzy logic based Solar Array Controller

3.8.4.      Experimental Results

3.9.            Forecasting of Solar Irradiance using ANN

3.9.1.      Relation between Solar Irradiance and Weather Variations

3.9.2.      Reconstruction for the Input Vector of the Forecasting Model

3.9.3.      ANN Forecasting Model Using Statistical Feature Parameters

3.10.        Parameter Identification of Solar Cell using Genetic Algorithm

3.10.1.  Method of Determining the Parameters of Solar Cell using Genetic Algorithms

3.11.        Application of Neuro-Fuzzy Technique for Prediction of Solar Radiation

3.11.1.  Neuro-Fuzzy Predictor (NFP)

3.11.2.  Error Metrics

3.11.3.  Neural networks training

3.11.4.  Prediction results with NNP

Summary

Review Questions

 

4.      WIND ENERGY CONVERSION SYSTEMS

4.1.            Introduction

4.2.            Wind Characteristics

4.3.            Wind Turbine

4.3.1.      Fixed-speed wind turbines

4.3.2.      Variable-speed wind turbines

4.4.            Components of WECS

4.5.            Types of Wind Turbine Generators

4.5.1.      Type 1 WTG

4.5.2.      Type 2 WTG

4.5.3.      Type 3 WTG

4.5.4.      Type 4 WTG

4.5.5.      Type 5 WTG

4.6.            Power Converter Topologies for Wind Turbine Generators

4.6.1.      Permanent magnet synchronous generators

4.6.2.      Doubly fed induction generators

4.6.3.      Induction generators

4.6.4.      Synchronous generators

4.7.            Economics of Wind Energy Conversion Systems

4.8.            Grid Connection

4.8.1.      Unique Configurations for Linking Wind Turbines on the Grid

4.9.            Modeling of Wind Turbine using MATLAB/SIMULINK

4.10.        MATLAB/SIMULINK model of Type 1 WTG

4.11.        MATLAB/SIMULINK model of Type 2  WTG

4.12.        MATLAB/SIMULINK model of Type 3 WTG

4.13.        MATLAB/SIMULINK model of Type 4 WTG

4.14.        MATLAB/SIMULINK model of Grid Connection

Summary

Review Questions

 

5.      SOFT COMPUTING TECHNIQUES IN WECS

5.1.            Prediction of Wind Turbine Power Factor

5.1.1.      Problem Formulation

5.1.2.      Artificial Neural Networks

5.1.3.      Adaptive Neuro-Fuzzy Inference System (ANFIS)

5.1.4.      Description of profile types

5.1.5.      Design of the ANN

5.1.6.      ANFIS for prediction of power factor

5.1.7.      Estimation of the Optimal Power Factor

5.2.            Pitch Angle Control

5.2.1.      Problem Definition

5.2.2.      Fuzzy Logic controllers

5.2.3.      Genetic Algorithms

5.2.4.      Conventional Pitch Angle Control

5.2.5.      Fuzzy Logic for Pitch Control

5.2.6.      Genetic Algorithm Controller for Pitch Angle Control

5.3.            MPPT for WECS

5.3.1.      Fuzzy logic based MPPT Controller

5.4.            Economic Dispatch For Wind Power System

5.4.1.      Mathematical model of Economic Dispatch for Power System based on Wind Energy

5.4.2.      Quantum Genetic Algorithm (QGA) for Economic Dispatch of Wind Power System

5.4.3.      Strength Pareto Evolutionary Algorithm (SPEA) approach

5.5.            SEIG Driven by WECS

5.5.1.      Mathematical model for SEIG driven by WECS

5.5.2.      Controllers

5.5.3.      Fuzzy Logic Controller

5.5.4.      Genetic Algorithm

5.6.            FLC based STATCOM

5.6.1.      Modeling of STATCOM

5.6.2.      MATLAB/SIMULINK model

5.6.3.      Simulation Results

5.7.            FLC based Wind Energy Production System

5.7.1.      Wind/battery energy production system

5.7.2.      The wind turbine model

5.7.3.      Battery model

5.7.4.      Fuzzy Logic controller

5.7.5.      MATLAB SIMULINK model

5.7.6.      Simulation Results

5.8.            Prediction of Wind Speed based on FLC

5.8.1.      Controller model

5.8.2.      Experimental results

5.9.            Fuzzy Logic Controlled SPWM Converter for WECS

5.9.1.      Components of standalone WECS

5.9.2.      MATLAB/SIMULINK model

5.9.3.      Simulation Results

Summary

Review Questions

 

6.      HYBRID ENERGY SYSTEMS

6.1.            Need for hybrid energy system

6.2.            Hybrid solar PV/wind energy system using MATLAB/SIMULINK

6.2.1.      Architecture of solar-wind hybrid system

6.2.2.      Implementation using MATLAB/SIMULINK

6.2.3.      Small domestic power grid based on hybrid electrical power

6.2.4.      Small industrial power system based on hybrid renewable energy

6.3.            Hybrid Model of Solar PV and Wind Energy System using CUK-SEPIC converter

6.3.1.      CUK – SEPIC based converter on source side

6.3.2.      CUK – SEPIC multi  input rectifier

6.3.3.      Model for hybrid wind and solar power plant

6.3.4.      Three phase uncontrolled AC-DC bridge rectifier

6.3.5.      Total harmonic distortion

6.3.6.      Test simulation and results

6.4.            Hybrid Model of Solar PV and Diesel Energy System

6.4.1.      Need for solar PV Diesel hybrid system

6.4.2.      Photovoltaic diesel hybrid system

6.4.3.      Components of the photovoltaic diesel hybrid system

6.4.4.      MATLAB/SIMULINK model of Solar PV/Diesel Hybrid System

6.5.            Energy management in HPS using the concept of multi-agent system

6.5.1.      Objective of MAS in Energy Management

6.5.2.      Concept of Multi-Agent System

6.5.3.      Application of MAS Concept

6.5.4.      Definition of Intelligent Agent

6.5.5.      Advantages of MAS Technology

6.5.6.      MAS in HPS

6.5.7.      Agentification of HPS

6.5.8.      Simulation and Results

6.6.            Fuzzy Logic Controller for Hybrid Power System

6.6.1.      FLC for HPS

6.6.2.      Description of the model

6.6.3.      Implementation in MATLAB

6.7.            Fuzzy Logic based MPPT for hybrid solar and WECS

6.7.1.      Methodology

6.7.2.      Design considerations

6.7.3.      Intelligent Controller

6.7.4.      Fuzzy Logic Controller based MPPT for HPS

6.7.5.      PID controller

6.7.6.      Simulation of Solar PV under atmospheric conditions

6.7.7.      Simulation of FLC based MPPT

Summary

Review Questions

 

7.      GRID INTEGRATION TECHNIQUES IN RENEWABLE ENERGY SYSTEMS

7.1.   Introduction

7.1.1.      Integration of small scale generation into distribution grids

7.1.2.      Different types of grid interfaces

7.1.3.      Issues related to grid Integration of small scale generation

7.1.4.      Integration of large scale renewable energy generation

7.2.   MATLAB model of Grid Integration

7.2.1.      Photovoltaic Module

7.2.2.      Boost Converter

7.2.3.      SIMULINK model of Boost Converter

7.2.4.      Implementation of Grid Integration using MATLAB

7.3.   Phase Locked Loop for Grid Connected Power System

7.3.1.      Challenges Imposed on an Inverter-Based DG Interface

7.3.2.      Requirements for establishing a Grid Connection

7.3.3.      Grid Synchronization Algorithms

7.3.4.      PLLs for Three phase systems

7.4.   Grid Connected Inverters

7.4.1.      Inverters

7.4.2.      Pulse Width Modulation Control

7.4.3.      Grid Filter

7.5.   CURRENT CONTROLLERS FOR PWM INVERTERS

7.5.1.      SRF PI current controller

7.5.2.      Cascaded Deadbeat and PI Controller

7.6.   SIMULINK MODEL OF PLL GRID CONNECTED POWER SYSTEM

7.6.1.      SIMULINK Model of a Synchronous Reference Frame PLL

7.6.2.      SIMULINK Model of a Synchronous Reference Frame PLL during Unbalanced fault

7.6.3.      SIMULINK Model of a DSRF PLL

7.6.4.      SIMULINK Model of a DSRF PLL under an Unbalanced Fault

7.6.5.      SIMULINK Model of αβPLL

7.6.6.      SIMULINK Model of a αβPLL during Unbalanced fault

7.6.7.      SIMULINK Model of a Dαβ PLL

7.6.8.      SIMULINK Model of a Dαβ PLL under an Unbalanced Fault

7.6.9.      SIMULINK model of a decoupled double synchronous reference frame PLL

7.6.10.  SIMULINK Model of a DDSRF PLL during an unbalanced fault

7.6.11.  SIMULINK diagram of grid synchronization of the inverter using the hybrid dαβ PLL

7.6.12.  SIMULINK model of SRF PI Controlled Voltage Source Inverter

7.6.13.  SIMULINK Diagram of Grid Synchronization of the Inverter Using Cascaded Deadbeat and PI Controller

7.6.14.  Comparison of Current THD of SRF PI and Cascaded Deadbeat and PI Controllers

Summary

Review Questions

 

8.      HARMONIC REDUCTION TECHNIQUES IN RENEWABLE ENERGY SYSTEMS

8.1.   Introduction

8.2.   Power Quality Issues

8.3.   Sources and Effects of Power Quality Problems

8.4.   Standards associated with power quality

8.4.1.      IEEE standards

8.4.2.      SEMI International Standards

8.5.   MEASUREMENT OF POWER QUALITY IN SOLAR PV SYSTEMS

8.5.1.      System Description

8.5.2.      Measurement Procedure for Power Quality in PV System

8.5.3.      Assessment Procedure for Power Quality in PV Systems

8.5.4.      Description of Case Studies

8.5.5.      Problem Evaluation and Solution Description

8.6.   DISTRIBUTION STATIC COMPENSATOR

8.6.1.      SIMULINK Model of DSTATCOM

8.6.2.      Simulation Results

8.7.   DYNAMIC VOLTAGE RESTORER

8.7.1.      Equations Related to DVR

8.7.2.      SIMULINK Model of DVR

8.7.3.      Results and Discussion

8.8.   UNIFIED POWER QUALITY CONDITIONER

8.8.1.      UPQC with PV array

8.8.2.      SIMULINK model of UPQC

8.8.3.      Simulation Results

8.9.   HARMONIC REDUCTION IN WECS

8.9.1.      Power Quality Standards and Issues

8.9.2.      Power Curtailment or Wind Turbine Disconnection

8.9.3.      Coordination with other Generating Plants

8.9.4.      Load Control

8.9.5.      Reactive Compensation and Voltage Control

8.10.                    POWER QUALITY IN WECS- A CASE STUDY

8.10.1.  Topology for Power Quality Improvement

8.10.2.  SIMULINK Model of Grid connected WECS

8.10.3.  SIMULINK Model of Grid connected WECS with STATCOM

8.10.4.  FFT Analysis

SUMMARY

Review Questions

 

9.      FUEL CELL AND CONVERTERS

9.1.            Introduction

9.2.            Fuel Cell Technology

9.2.1.      Importance of Fuel Cell

9.2.2.      Types of fuel cells

9.2.3.      Electrical Behaviour of Fuel Cell

9.2.4.      Need for power electronic converters

9.2.5.      DC-DC converters

9.2.6.      Conventional Boost Converter

9.2.7.      Cascaded Boost Converter

9.2.8.      Interleaved Boost Converter

9.2.9.      Isolated Converters

9.2.10.  Flyback Converter

9.2.11.  Forward Converter

9.2.12.  Half bridge converter

9.2.13.  Full bridge converter

9.3.            Inverters

9.3.1.      Single phase inverter

9.3.2.      Half-Bridge Configuration

9.3.3.      Half Bridge with Resistive Load

9.3.4.      Half Bridge with RL Load

9.3.5.      Full Bridge Configuration

9.3.6.      Full Bridge with Resistive Load

9.3.7.      Full Bridge with Resistive Load

9.3.8.      Three Phase Inverter

9.3.9.      Z-Source Inverter

9.3.10.  LLCC Resonant Inverter

9.4.            Fuel Cell System with Motor Load

9.5.            Architecture of Multiple Fuel Cells for High Voltage/High Power Applications

9.5.1.      Series Architecture

9.5.2.      DC Bus Distribution Architecture

9.5.3.      HFAC Distribution Architecture

9.5.4.      Multilevel Architecture

Summary

Review Questions

 

Appendix I – SOFTWARE TOOLS FOR SOLAR PV AND WECS

Appendix II – RESEARCH PROJECTS

Appendix III – SIMULINK BLOCKSETS

Appendix IV - SOLAR RADIATION DATA