Reduction of Real Power Loss by using Enhanced Particle Swarm Optimization Algorithm

In this paper, an Enhancedparticle swarm optimization algorithm (EPSO) has been proposed to solve the reactive power problem. Particle Swarm Optimization (PSO) is swarm intelligence based exploration and optimization algorithm which is used to solve global optimization problems. But due to deficiency of population diversity and early convergence it is often stuck into local optima. We can upsurge diversity and avoid premature convergence by using evolutionary operators in PSO. In this paper the intermingling crossover operator is used to upsurge the exploration capability of the swarm in the exploration space .Particle Swarm Optimization uses this crossover method to converge optimum solution in quick manner .Thus the intermingling crossover operator is united with particle swarm optimization to augment the performance and possess the diversity which guides the particles to the global optimum powerfully. The proposedEnhanced particle swarm optimization algorithm (EPSO) has been tested in standard IEEE 30, 57,118 bus test systems and simulation results shows clearly the improved performance of the projected algorithm in reducing the real power loss and control variables are well within the limits. Keywords: Optimal Reactive Power, Transmission loss, intermingling crossover operato

An Improved Bat Algorithm for solving Series-parallel power system problem

Today’s highly capitalized power societies require ‘maximum benefit with minimum cost.’ In order to achieve this goal, design engineers depend on cost optimization techniques. This work uses an improved bat algorithm (IBA) meta-heuristic optimization method to solve the problem of power optimization systems design. We consider the case where redundant electrical components are chosen to achieve a desirable level of reliability. The electrical power components of the system are characterized by their cost, capacity and reliability. The reliability is defined as the ability to satisfy the consumer demand which is represented as a piecewise cumulative load curve. The proposed meta-heuristic seeks for the optimal design of series-parallel power systems in which a multiple choice of generators, transformers and lines are allowed from a list of product available in the market. Our approach has the advantage to allow electrical power components with different parameters to be allocated in electrical power systems. To allow fast reliability estimation, a universal generating function (UGF) method is applied. A computer program has been developed to implement the UGF and the IBA algorithm. An illustrative example is presented. Keywords: Improved Bat Algorithm (IBA), Optimization, Power system design, reliability, Universal moment generating Function (UMGF

Enriched Particle Swarm Optimization for Solving Optimal Reactive Power Dispatch Problem

In this paper, a different approach, Enriched particle Swarm optimization (EPSO) Algorithm for solving optimal reactive power dispatch problem has been presented. Particle swarm optimization is affected by early convergence, no assurance in finding optimal solution. This paper proposes EPSO using multiple sub swarm PSO in blend with multi exploration space algorithm. The particles are alienated into equal parts and arrayed into the number of sub swarms available. Multi-exploration space algorithm is used to obtain an optimum solution for each sub swarm and these solutions are then arrayed yet into a new swarm to obtain the best of all the solution. The proposed EPSO algorithm has been tested on standard IEEE 30 bus test system and simulation results show the commendable performance of the proposed algorithm in reducing the real power loss. Keywords:Optimal Reactive Power, Transmission loss, Enriched particle Swarm optimization, Multi-exploratio

A Chaotic Particle Swarm Optimization (CPSO) Algorithm for Solving Optimal Reactive Power Dispatch Problem

This paper presents a chaotic particle swarm algorithm for solving the multi-objective reactive power dispatch problem. To deal with reactive power optimization problem, a chaotic particle swarm optimization (CPSO) is presented to avoid the premature convergence. By fusing with the ergodic and stochastic chaos, the novel algorithm explores the global optimum with the comprehensive learning strategy. The chaotic searching region can be adjusted adaptively.  In order to evaluate the proposed algorithm, it has been tested on IEEE 30 bus system and simulation results show that (CPSO)   is more efficient than other algorithms in reducing the real power loss and maximization of voltage stability index. Keywords:chaotic particle swarm optimization, Optimization, Swarm Intelligence, optimal reactive power, Transmission loss

Direct Torque Control Algorithm for Induction Motor Drives for the Mitigation of Common Mode Voltage

This paper presents a novel direct torque control (DTC) algorithm for induction motor drives for the reduction of common mode voltage. In the Proposed DTC algorithm-I the space vector plane is divided into six sectors same as that of Conventional DTC algorithm. In the proposed algorithm-II, the space vector plane is divided into twelve sectors instead of six sectors as in conventional DTC algorithm and Proposed DTC algorithm-I. Moreover, the proposed algorithm does not use the zero voltage vectors. To validate the proposed algorithm, numerical simulations have been carried out using MATLAB-Simulink and results are presented and compared. From the simulation results it can be observed the proposed algorithm reduces the common mode voltage variations compared to conventional DTC algorithm with slightly increased ripples in current, torque and flux

Atmosphere Clouds Model Algorithm for Solving Optimal Reactive Power Dispatch Problem

In this paper, a new method, called Atmosphere Clouds Model (ACM) algorithm, used for solving optimal reactive power dispatch problem. ACM stochastic optimization algorithm stimulated from the behavior of cloud in the natural earth. ACM replicate the generation behavior, shift behavior and extend behavior of cloud. The projected (ACM) algorithm has been tested on standard IEEE 30 bus test system and simulation results shows clearly about the superior performance of the proposed algorithm in plummeting the real power loss

Modified Monkey Optimization Algorithm for Solving Optimal Reactive Power Dispatch Problem

In this paper, a novel approach Modified Monkey optimization (MMO) algorithm for solving optimal reactive power dispatch problem has been presented. MMO is a population based stochastic meta-heuristic algorithm and it is inspired by intelligent foraging behaviour of monkeys. This paper improves both local leader and global leader phases.  The proposed (MMO) algorithm has been tested in standard IEEE 30 bus test system and simulation results show the worthy performance of the proposed algorithm in reducing the real power loss