M. Sudhakaran

Application of Particle Swarm Optimization for Economic Load Dispatch Problems

This paper presents an efficient and reliable particle swarm optimization (PSO) method for the economic load dispatch (ELD) problems. The PSO method was developed through the simulation of a simplified social system and has been found to be robust in solving continuous nonlinear optimization problems in terms of accuracy of the solution and computation time and it can out perform other algorithms. The proposed algorithm is applied for the ELD of three unit & six unit thermal plant systems and extended to three plant system in which one plant is combined cycle co-generation plant. The performance of the proposed PSO method is compared with the conventional method and genetic algorithm method and it is observed that this method is reliable and may replace effectively the conventional practices presently performed in different central load dispatch centers. The comparison of results shows that the proposed PSO method was indeed capable of obtaining higher quality solutions efficiently for ELD problems within less computation time.

Particle Swarm Optimization Based Energy Optimized Dynamic Voltage Restorer

Implementation of particle swarm optimization (PSO) application for solving the optimization problem in the field of electric power system is proposed. PSO is a powerful tool for optimizing multidimensional discontinuous nonlinearity problems. The optimization problem in power system like minimization of energy capacity of a dynamic voltage restorer is identified and analyzed in the proposed work. The growing interest in power quality has led to a variety of devices designed for mitigating power disturbances, primarily voltage sags. Among several devices, a dynamic voltage restorer (DVR) is a novel custom power device proposed to compensate for voltage disturbances in a distribution system. The compensation capability of a DVR depends primarily on the maximum voltage injection ability and the amount of stored energy available within the restorer. A novel PSO based phase advancement compensation (PAC) strategy is proposed in this work for optimizing the energy storage capacity of the DVR in order to enhance the voltage restoration property of the device. The proposed algorithm is tested on a sample three phase system for various levels of sag in a particular phase. The proposed algorithm identifies the required value of phase advancement angle corresponding to minimum power injection from the energy storage element such as a capacitor or a battery. The results of swarm intelligence based DVR are compared with the conventional DVR techniques and is found encouraging.

Analysis Design and Implementation of Soft Single Switched Boost Converter

This paper proposes a better family of PWM soft single switched (SSS) Boost converter topology with low voltage and current stresses in switches. Soft switching condition is carried out through single switch. In most of the converter topologies under zero current condition (ZCS) only the switch is triggered to on mode and switch is made to off mode under zero voltage condition (ZVS).In a prototype model for soft turn on and turn off switch is applied to a boost(PWM) SSS converter, The operating principle of the converter topology is analyzed and its operating modes are studied .The experimental results of a prototype boost converter is compared with the theoretical analysis.

Tabu search-enhanced artificial bee colony algorithm to solve profit-based unit commitment problem with emission limitations in deregulated electricity market

This paper proposes a new foraging ABC algorithm that integrates the features of ABC and Tabu search (TS) to solve the profit-based unit commitment (PBUC) problem in deregulated electricity market with emission limitations. The multiobjective optimisation problem is formulated to maximise the profit and minimise the pollutants into the atmosphere by satisfying all the system constraints. ABC algorithm is applied to solve the 1-0 part of the PBUC problem and lambda iterative method optimises the economic load dispatch problem. The ideas of Tabu array (TA) and logical aspiration factor are applied to adjust the search process in the solution space. The proposed TS-enhanced ABC algorithm is verified on IEEE 39 bus test system having 10 generating units for 24-h load pattern. The solutions of traditional UC and PBUC with and without emission limitations are compared with improved ABC shuffled frog leaping algorithm, Mullers and ACO method.

Optimal Location and Control Parameter Settings of UPFC using Differential Evolution Algorithm

The main objective of this paper is to find the optimal location and control parameters settings of Unified Power Flow Controller (UPFC) with regard to power loss minimization. The proposed algorithm is based on steady state power injection model of UPFC. In this paper, two Evolutionary optimization techniques, namely Differential Evolution Algorithm (DE) and Genetic Algorithm (GA) are employed to solve optimal power flow problems. IEEE 14 bus & IEEE 30 bus test power systems are used for studies. The obtained results indicate that both techniques can successfully find the optimal location and control parameter settings of UPFC, but DE is faster than GA from the time perspective.