The increasing penetration of Distributed Generators (D.G.) into the existing power system has brought some real challenges regarding transient response electrical systems. injection D.G.s and abrupt load changes may cause massive power, current, voltage overshoots/undershoots, which consequently affects equilibrium deteriorate performance connected appliances. A robust intelligent control stra...

Many real world optimization problems are dynamic, meaning that their optimal solutions are time-varying. In recent years, an effective approach to address these problems has been the multi-swarm PSO (mPSO). Despite this, we believe that there is still room for improvement and, in this contribution we propose two simple strategies to increase the effectiveness of mPSO. The first one faces the d...

The automatic upgradation of equalizer weights in channel equalization demands a low-complexity, highly accurate estimation recovery at the minimum possible time. low-complexity frequency domain improves mean square error (MMSE) process. Adding superiority particle swarm optimization (PSO) to coefficient selection process enhances MMSE. This work proposes frequency-domain along with modified PS...

The dogleg severity is one of the most important parameters in directional drilling. Improvement of these indicators actually means choosing the best conditions for the directional drilling in order to reach the target point. Selection of high levels of the dogleg severity actually means minimizing well trajectory, but on the other hand, increases fatigue in drill string, increases torque and d...

Particle swarm optimization (PSO) has undergone many changes since its introduction in 1995. Being a stochastic algorithm, PSO and its randomness present formidable challenge for the theoretical analysis of it, and few of the existing PSO improvements have make an effort to eliminate the random coefficients in the PSO updating formula. This paper analyzes the importance of the randomness in the...

Este articulo presenta una nueva técnica de optimización para ajustar simultáneamente los parámetros controladores asociados a la regulación tensión y aumentar amortiguación generadores síncronos. Los del Regulador Automático Voltaje (AVR - Automatic Voltage Regulation) el Estabilizador Sistema Potencia (PSS Power System Stabilizer) se optimizan mediante modificación propuesta en Optimización E...

Traditional economic dispatch methods, which are used to minimize fuel costs, have become inadequate because they do not consider the environmental impact of emissions in optimization process. By taking into account horizon year load and carbon taxes, this paper examines operation power units a system. The objective function, including cost fuels is solved by modified particle swarm with time-v...

Wireless sensor network (WSN) is a network, which has more numbers of sensors that are small in nature and self organised. The inbuilt battery system provided the nodes through can communicate do good operations among other available network. Lifetime most essential parameter needs to be maximised for WSN. This measure important conservation energy, adequate efficient performance networks. pape...

Abstract Several studies exist in the literature that utilized metaheuristics and nature-inspired algorithms to solve engineering problems. Particle Swarm Optimization (PSO) is a well-known algorithm has been used for different optimization problems due its simplicity ability find near-optimal solutions. However, PSO suffers from problem of balancing between global search local abilities when a...

The implementation of meta-heuristic algorithm in defining the optimal solution for distribution network reconfiguration has been addressed by many researchers over the years. Nonetheless, the solution in minimizing the main objective which is total power losses could not be solved until today. In this study, the hybridization of evolutionary particle swarm optimization has been modified in ord...