Ebook: Computational Intelligence in Power Engineering

Computational Intelligence (CI) is one of the most important powerful tools for research in the diverse fields of engineering sciences ranging from traditional fields of civil, mechanical engineering to vast sections of electrical, electronics and computer engineering and above all the biological and pharmaceutical sciences. The existing field has its origin in the functioning of the human brain in processing information, recognizing pattern, learning from observations and experiments, storing and retrieving information from memory, etc. In particular, the power industry being on the verge of epoch changing due to deregulation, the power engineers require Computational intelligence tools for proper planning, operation and control of the power system. Most of the CI tools are suitably formulated as some sort of optimization or decision making problems. These CI techniques provide the power utilities with innovative solutions for efficient analysis, optimal operation and control and intelligent decision making. This edited volume deals with different CI techniques for solving real world Power Industry problems. The technical contents will be extremely helpful for the researchers as well as the practicing engineers in the power industry.

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Computational Intelligence (CI) is one of the most important powerful tools for research in the diverse fields of engineering sciences ranging from traditional fields of civil, mechanical engineering to vast sections of electrical, electronics and computer engineering and above all the biological and pharmaceutical sciences. The existing field has its origin in the functioning of the human brain in processing information, recognizing pattern, learning from observations and experiments, storing and retrieving information from memory, etc. In particular, the power industry being on the verge of epoch changing due to deregulation, the power engineers require Computational intelligence tools for proper planning, operation and control of the power system. Most of the CI tools are suitably formulated as some sort of optimization or decision making problems. These CI techniques provide the power utilities with innovative solutions for efficient analysis, optimal operation and control and intelligent decision making. This edited volume deals with different CI techniques for solving real world Power Industry problems. The technical contents will be extremely helpful for the researchers as well as the practicing engineers in the power industry.

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Computational Intelligence (CI) is one of the most important powerful tools for research in the diverse fields of engineering sciences ranging from traditional fields of civil, mechanical engineering to vast sections of electrical, electronics and computer engineering and above all the biological and pharmaceutical sciences. The existing field has its origin in the functioning of the human brain in processing information, recognizing pattern, learning from observations and experiments, storing and retrieving information from memory, etc. In particular, the power industry being on the verge of epoch changing due to deregulation, the power engineers require Computational intelligence tools for proper planning, operation and control of the power system. Most of the CI tools are suitably formulated as some sort of optimization or decision making problems. These CI techniques provide the power utilities with innovative solutions for efficient analysis, optimal operation and control and intelligent decision making. This edited volume deals with different CI techniques for solving real world Power Industry problems. The technical contents will be extremely helpful for the researchers as well as the practicing engineers in the power industry.
Content:
Front Matter....Pages -
Robust Design of Power System Stabilizers for Multimachine Power Systems Using Differential Evolution....Pages 1-18
An AIS-ACO Hybrid Approach for Multi-Objective Distribution System Reconfiguration....Pages 19-73
Intelligent Techniques for Transmission Line Fault Classification....Pages 75-101
Fuzzy Reliability Evaluations in Electric Power Systems....Pages 103-130
Load Forecasting and Neural Networks: A Prediction Interval-Based Perspective....Pages 131-150
Neural Network Ensemble for 24-Hour Load Pattern Prediction in Power System....Pages 151-169
Power System Protection Using Machine Learning Technique....Pages 171-198
Power Quality....Pages 199-234
Particle Swarm Optimization PSO: A New Search Tool in Power System and Electro Technology....Pages 235-294
Particle Swarm Optimization and Its Applications in Power Systems....Pages 295-324
Application of Evolutionary Optimization Techniques for PSS Tuning....Pages 325-366
A Metaheuristic Approach for Transmission System Expansion Planning....Pages 367-379
Back Matter....Pages -

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Computational Intelligence (CI) is one of the most important powerful tools for research in the diverse fields of engineering sciences ranging from traditional fields of civil, mechanical engineering to vast sections of electrical, electronics and computer engineering and above all the biological and pharmaceutical sciences. The existing field has its origin in the functioning of the human brain in processing information, recognizing pattern, learning from observations and experiments, storing and retrieving information from memory, etc. In particular, the power industry being on the verge of epoch changing due to deregulation, the power engineers require Computational intelligence tools for proper planning, operation and control of the power system. Most of the CI tools are suitably formulated as some sort of optimization or decision making problems. These CI techniques provide the power utilities with innovative solutions for efficient analysis, optimal operation and control and intelligent decision making. This edited volume deals with different CI techniques for solving real world Power Industry problems. The technical contents will be extremely helpful for the researchers as well as the practicing engineers in the power industry.
Content:
Front Matter....Pages -
Robust Design of Power System Stabilizers for Multimachine Power Systems Using Differential Evolution....Pages 1-18
An AIS-ACO Hybrid Approach for Multi-Objective Distribution System Reconfiguration....Pages 19-73
Intelligent Techniques for Transmission Line Fault Classification....Pages 75-101
Fuzzy Reliability Evaluations in Electric Power Systems....Pages 103-130
Load Forecasting and Neural Networks: A Prediction Interval-Based Perspective....Pages 131-150
Neural Network Ensemble for 24-Hour Load Pattern Prediction in Power System....Pages 151-169
Power System Protection Using Machine Learning Technique....Pages 171-198
Power Quality....Pages 199-234
Particle Swarm Optimization PSO: A New Search Tool in Power System and Electro Technology....Pages 235-294
Particle Swarm Optimization and Its Applications in Power Systems....Pages 295-324
Application of Evolutionary Optimization Techniques for PSS Tuning....Pages 325-366
A Metaheuristic Approach for Transmission System Expansion Planning....Pages 367-379
Back Matter....Pages -
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