Fuzzy Logic Control in Energy Systems with design applications in MATLAB®/Simulink

• Main Author: Altaş, Ismail H.
• Format: eBook
• Language: English
• Published: Stevenage The Institution of Engineering and Technology 2017; Institution of Engineering and Technology (The IET); Institution of Engineering & Technology
• Edition: 1
• Subjects: Computer programming / software development; COMPUTERS; Control Theory & Optimization; Electrical; Electrical & Power Engineering; Electrical Design & Energy Efficiency; Electrical engineering; Power Resources; Process Design, Control & Automation; Programming; TECHNOLOGY & ENGINEERING; fuzzy sets; fuzzy partitioning; Simulink; fuzzy relation; MATLAB; fuzzy control; fuzzy processor; fuzzy logic controller; fuzzy decision maker; power control; energy systems; FLC; fuzzy decision making processing

Modern electrical power systems are facing complex challenges, arising from distributed generation and intermittent renewable energy. Fuzzy logic is one approach to meeting this challenge and providing reliability and power quality. The book is about fuzzy logic control and its applications in manag...

Table of Contents:

• Chapter 1: Introduction -- Chapter 2: Fuzzy sets -- Chapter 3: Fuzzy partitioning -- Chapter 4: Fuzzy relation -- Chapter 5: Fuzzy reasoning and fuzzy decision-making -- Chapter 6: Fuzzy processor -- Chapter 7: Fuzzy logic controller -- Chapter 8: System modelling and control -- Chapter 9: FLC in power systems -- Chapter 10: FLC in wind energy systems -- Chapter 11: FLC in PV solar energy systems -- Chapter 12: Energy management and fuzzy decision-making
• Title Page Preface Table of Contents 1. Introduction 2. Fuzzy Sets 3. Fuzzy Partitioning 4. Fuzzy Relation 5. Fuzzy Reasoning and Fuzzy Decision-Making 6. Fuzzy Processor 7. Fuzzy Logic Controller 8. System Modeling and Control 9. FLC in Power Systems 10. FLC in Wind Energy Systems 11. FLC in PV Solar Energy Systems 12. Energy Management and Fuzzy Decision-Making Index
• 10.3.2 Self-excited induction generator -- 10.4 FLC examples in WEC systems -- 10.5 Problems -- References -- 11. FLC in PV solar energy systems -- 11.1 Introduction -- 11.2 PV cell modelings -- 11.2.1 Reference I-V characteristics of a PV panel -- 11.2.2 Effects of changes in solar irradiation and temperature -- 11.2.3 PV panel modeling in Simulink -- 11.2.4 A PV array emulator -- 11.3 MPP search in PV arrays -- 11.3.1 MPP by lookup tables -- 11.3.2 MPP search algorithm based on measurements of SX and TX -- 11.3.3 MPP search algorithm based on voltage and current measurements -- 11.3.4 MPP search algorithm based on online repetitive method -- 11.4 MPPT of PV arrays -- 11.4.1 Constant maximum power angle approach -- 11.4.2 Online load matching approach -- 11.5 Problems -- References -- 12. Energy management and fuzzy decision-making -- 12.1 Introduction -- 12.2 Distributed generation and control -- 12.3 Energy management in a renewable integration system -- 12.3.1 Centralized control of distributed renewable energy systems -- 12.3.2 Distributed control of renewable energy systems -- 12.4 Problems -- References -- Index
• Intro -- Contents -- Preface -- Acknowledgments -- 1. Introduction -- 1.1 Introduction -- 1.2 Fuzziness -- 1.3 Fuzzy membership functions -- 1.4 Fuzzy sets -- References -- 2. Fuzzy sets -- 2.1 Introduction -- 2.2 Fuzzy sets and fuzzy membership functions -- 2.2.1 Triangular membership function -- 2.2.2 Trapezoid membership function -- 2.2.3 Gaussian membership function -- 2.2.4 Bell membership function -- 2.2.5 Cauchy membership function -- 2.2.6 Sinusoid membership function -- 2.2.7 Sigmoid membership function -- 2.3 Properties of fuzzy membership functions -- 2.4 Fuzzy set operations -- 2.4.1 Intersection: t-norm -- 2.4.2 Union: t-conorm -- 2.4.3 Complement -- 2.4.4 De Morgan laws -- 2.5 Adjustment of fuzziness -- 2.6 Problems -- References -- 3. Fuzzy partitioning -- 3.1 Introduction -- 3.2 Theoretical approaches -- 3.3 Fuzzy partition examples in energy systems -- 3.4 Problems -- References -- 4. Fuzzy relation -- 4.1 Introduction -- 4.2 Fuzzy relation -- 4.3 Operation with fuzzy relations -- 4.3.1 Intersection of two fuzzy relations -- 4.3.2 Union of two fuzzy relations -- 4.3.3 Negation of a fuzzy relation -- 4.3.4 Inverse of a fuzzy relation -- 4.3.5 Composition of fuzzy relations -- 4.3.6 Compositional rule of inference -- 4.3.7 The relational joint -- 4.4 Binary relations -- 4.5 The extension principle -- 4.5.1 The cylindrical extension -- 4.6 Fuzzy mapping -- 4.7 Problems -- References -- 5. Fuzzy reasoning and fuzzy decision-making -- 5.1 Introduction -- 5.2 Fuzzy implications -- 5.3 Approximate reasoning -- 5.4 Inference rules of approximate reasoning -- 5.4.1 Entailment rule of inference -- 5.4.2 Conjunction rule of inference -- 5.4.3 Disjunction rule of inference -- 5.4.4 Negation rule of inference -- 5.4.5 Projection rule of inference -- 5.4.6 Generalized modus ponens rule of inference -- 5.4.7 Compositional rule of inference
• 5.5 Fuzzy reasoning -- 5.5.1 Inference engine with single input single rule -- 5.5.2 Inference engine with multiple input single rule -- 5.5.3 Inference engine with multiple input multiple rule -- 5.6 Problems -- References -- 6. Fuzzy processor -- 6.1 Introduction -- 6.2 Mamdani fuzzy reasoning -- 6.2.1 Fuzzification -- 6.2.2 Fuzzy rule base -- 6.2.3 Fuzzy conclusion -- 6.2.4 Defuzzification -- 6.3 Takagi-Sugeno fuzzy reasoning -- 6.4 Tsukamoto fuzzy reasoning -- 6.5 Problems -- References -- 7. Fuzzy logic controller -- 7.1 Introduction -- 7.2 Physical system behaviors and control -- 7.3 Fuzzy processor for control -- 7.3.1 Fuzzy rules: the modeling of thoughts -- 7.3.2 The input-output interaction -- 7.4 Modeling the FLC in MATLAB -- 7.5 Modeling the FLC in Simulink -- 7.6 Problems -- References -- 8. System modeling and control -- 8.1 Introduction -- 8.2 System modeling -- 8.3 Modeling electrical systems -- 8.4 Modeling mechanical systems -- 8.4.1 Mechanical systems with linear motion -- 8.4.2 Mechanical systems with rotational motion -- 8.5 Modeling electromechanical systems -- 8.5.1 Field subsystem -- 8.5.2 Armature subsystem -- 8.5.3 Mechanical subsystem -- 8.5.4 Electromechanic interaction subsystem -- 8.5.5 Modeling DC motors -- 8.5.6 Modeling AC motors -- 8.6 Problems -- References -- 9. FLC in power systems -- 9.1 Introduction -- 9.2 Excitation control -- 9.2.1 Excitation system modeling -- 9.2.2 State-space model of excitation systems -- 9.2.3 FLC of excitation systems -- 9.3 LF control -- 9.3.1 Small signal modeling of power systems -- 9.3.2 FLC design for LFC -- 9.4 FLC in power compensation -- 9.4.1 Power factor improvement -- 9.4.2 Bus voltage control -- 9.5 Problems -- References -- 10. FLC in wind energy systems -- 10.1 Introduction -- 10.2 Wind turbine -- 10.3 Electrical generator -- 10.3.1 Dynamic modeling of induction generator