Abstract

Abstract

Abstract
In a deregulated profit-based environment, consumers and producers need short-term intelligent prediction tools to predict their bid strategies in the energy market. Also, all markets players need accurate forecasting tools with lower uncertainty, allowing to maximizing their profits. Hence, this manuscript presents a new intelligent approach based on a combination of Wavelet Transform (WT), Evolutionary Particle Swarm Optimization (EPSO) and Adaptive Network and Fuzzy Inference System (ANFIS) for forecasting in power engineering systems. The results of two real-world case studies are shown, regarding energy prices and wind power, which show the proficiency of the proposed intelligent approach. © 2012 IEEE.

Abstract
This paper presents the classification of power quality (PQ) disturbances using modular probabilistic neural network (MPNN), support vector machines (SVMs) and least square support vector machines (LS-SVMs) in grid-connected wind energy systems. Different types of sag and swell disturbances due to the change in load and wind speed are created using MATLAB/Simulink. Classification scheme encompasses suitable features extracted by S-transform (ST) and is subsequently trained with MPNN, SVM and LS-SVM to effectively classify the PQ disturbances. The accuracy and reliability of the proposed classifier are also validated on signals with noise content. A comparative study is also carried out to determine the efficacy of the proposed techniques. © 2012 IEEE.

Abstract
This paper proposes evolutionary particle swarm optimization (EPSO) combined with an adaptive-network-based fuzzy inference system (ANFIS) for short-term electricity prices forecasting. In a deregulated framework, producers and consumers require short-term price forecasting to derive their bidding strategies to the electricity market. Accurate forecasting tools are required for producers to maximize their profits and for consumers to maximize their utilities. The accuracy of the price forecasting attained with the proposed intelligent system is thoroughly evaluated, reporting the numerical results from a real-world case study. © 2011 IEEE.

Abstract
This paper is concerned with the protection of wind turbines against the indirect effects of lightning. Lightning damages involving wind turbines have come to be regarded with increasing concern. The wind power generation is rapidly growing in Portugal, but still there are few studies regarding the lightning protection of wind turbines using models of the Electro-Magnetic Transients Program (EMTP). Hence, a case study is presented in this paper, based on a wind turbine with an interconnecting transformer, considering that lightning strikes the soil near the tower. Computer simulations are provided by using the recently restructured version of EMTP, EMTP-RV, highlighting the need for adequate protection measures. © 2011 IEEE.