Titlebook: Computational Intelligence in Power Engineering; Bijaya Ketan Panigrahi,Ajith Abraham,Swagatam Das Book 2010 Springer-Verlag Berlin Heidel

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Particle Swarm Optimization and Its Applications in Power Systems,f employing PSO in many applications in science and technology have indicated its promising potential. Thus, the basics of PSO theory, development, main features, and its applications in power systems are presented in the following sections.

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Robust Design of Power System Stabilizers for Multimachine Power Systems Using Differential Evolutiferential Evolution (DE) technique to search for optimal settings of PSS parameters. An eigenvalue-based objective function to enhance system damping for electromechanical modes is considered. The robustness of the proposed approach to the initial population is demonstrated. The performance of the p

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An AIS-ACO Hybrid Approach for Multi-Objective Distribution System Reconfiguration, formulated as a multi-objective optimization problem. The algorithm maintains a population of candidate solutions called antibodies. The search space is explored by means of the hypermutation operator that perturbs existing antibodies to produce new ones. A table of pheromones is used to reinforce

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Intelligent Techniques for Transmission Line Fault Classification,digital form include distance, current differential, phase comparison, directional comparison and travelling wave protection schemes. The transmission system protection techniques in general are involved in defining the system’s state through identifying the pattern of the associated voltage and cur

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Fuzzy Reliability Evaluations in Electric Power Systems,ility requirement for power system is very high. The classical reliability evaluations of Power System adopts the widely accepted definition of reliability as the probability of a device performing its purpose adequately for he period of time indented under the operating conditions encountered [1].

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Load Forecasting and Neural Networks: A Prediction Interval-Based Perspective, high volatility of loads make their accurate prediction somewhat problematic. Presence of uncertainty in data also significantly degrades accuracy of point predictions produced by deterministic load forecasting models. Therefore, operation planning utilizing these predictions will be unreliable. Th

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Power System Protection Using Machine Learning Technique,VM). SVM is a relatively new computational learning method based on the statistical learning theory. The proposed technique is used for developing protection schemes for Thyristor Controlled Series Compensated (TCSC) Line using post fault current samples for half cycle (10 samples) from the inceptio

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Particle Swarm Optimization PSO: A New Search Tool in Power System and Electro Technology, system applications. As the complexities of the problem increase, especially with the introduction of uncertainties to the system, more complicated optimization techniques, such as stochastic programming have to be used. Particle Swarm Optimization (PSO) technique can be an alternative solution for