To overcome this shortcoming, a multiobjective particle swarm optimization is proposed and applied in reactive power optimization on. E student power system engineering 1,2department of electrical engineering 1,2k. Abuella a thesis submitted in partial fulfillment of the requirements for the master of science degree department of electrical and computer engineering southern illinois. Abstract the optimal power flow opf plays an important role in power system operation and control due to depleting energy resources, and increasing power generation cost and ever growing demand for electric energy. A particle swarm optimization for reactive power optimization. Optimal power flow solution using particle swarm optimization algorithm abstract. Create scripts with code, output, and formatted text in a. This paper proposes an efficient method to solve the optimal power flow problem in power systems using particle swarm optimization pso. Abido ma 2002 optimal power flow using particle swarm optimization. It solves a problem by having a population of candidate solutions, here dubbed particles, and moving these particles around in the searchspace according to simple mathematical formulae. He s, wen jy, prempain e, wu qh, fitch j, mann s 2004 an improved particle swarm optimization for optimal power flow. Request pdf optimal power flow using particle swarm optimization this paper proposes the application of particle swarm optimization pso technique to solve optimal power flow with inequality.
In optimization, many techniques are used to solve the problem in power system. Introduction optimal power flow is one of nonlinear constrained and occasionally combin atorial optimization problems of power systems. Study of using particle swarm for optimal power flow in ieee benchmark systems including wind power generators by mohamed a. Study of using particle swarm for optimal power flow 1. Gtu, kalol, india abstractreactive power plays an important role. Like evolutionary algorithms, pso technique conducts search using a population of particles, corresponding to individuals. This paper proposes a particle swarm optimization pso algorithm for optimal placement of distributed generation dg in a primary distribution system to minimize the total real power loss. D lecturer department of ece bule hora university, bulehora, ethiopia. Particle swarm optimization pso is a populationbased optimization method first proposed by kennedy and. Transmission system facts, optimal power flow opf introduction in opf2,3 the main objective is to minimize the cost of meeting the load demand for the power system while satisfying all. There are many ways to optimize the power flow out of which power loss minimization and voltage profile improvement are considered as the efficient ways. Particle swarm optimization based method for optimal. Pso algorithm for opf optimize power flow with matlab.
Basic particle swarm optimization pso model particle swarm optimization pso has been developed through simulation of simplified social models. Theoretical analysis, modifications, and applications to constrained optimization problems. This paper describes opf based on particle swarm optimization pso method in which total generation cost function is considered as the objective function. Flexible ac transmission system facts devices become more commonly used as the power market becomes more competitive. General terms power system, particle swarm optimization. Selection of optimal location and size of distributed. The number of hidden layers and the number of neurons in each layer of a deep machine learning network are two key parameters, which. Hybrid particle swarm optimization technique for optimal power flow. The proposed approach employs the pso algorithm for optimal setting of optimal power flow opf based on loss minimization lm function.
Optimal power flow, loss minimization,particle swarm optimization, improved p article swarm optimization i. Newtonraphson load flow algorithm has been used to generate the benchmark solutions taken as true values of the state variables to be estimated from the corrupted measurements available in the power system control center. Basically particle swarm optimization is a method for optimization of continuous nonlinear functions. Optimal placement of distributed facts devices in power. Particle swarm optimization research toolbox documentation.
Guide to conducting your own research clarifies how a motivated researcher could add constraints or make other improvements. The method was discovered through simulation of a simplified social model. This paper presents an efficient and reliable evolutionarybased approach to solve the optimal power flow opf problem. I need matlab code for dg placement considering load models using particle swarm optimization applied to ieee 9 bus system 14 bus, and 30 bus system, please if you can help then send it. Reactive power optimization is a complex combinatorial programming problem that reduces power loses and improves voltage profiles in a power system. Loss minimization using optimal power flow based on. Defining a standard for particle swarm optimization pdf. By making use of modified particle swarm optimization mpso, the optimal location of upfc in power system will be obtained.
The proposed approach employs particle swarm optimization pso algorithm for optimal settings of opf problem control variables. Introduction deregulation of the electricity supply system becomes an important issue in many countries. This project aims to find the optimum sizing and location of dg in power system by using particle swarm optimization pso. This project will use particle swarm optimization pso method to test on several cases, without dg installed, single dg, two dg, three dg and 10 dg installed. Particle swarm optimization artificial neural network for. Particle swarm optimization for power system state. By eci algorithm, it is much quickly and precisely to implement power flow calculations. Minimization of reactive power using particle swarm. Optimal power flow based on particle swarm optimization layth albahrani1, virgil dumbrava2 optimal power flow opf is one of the most important requirements in all developed power system.
In 12, developed a method for solving multiobjective optimal power flow using differential evolution algorithm. In this paper, an improved particle swarm optimization algorithm using eagle strategy espso is proposed for solving reactive power optimization. The optimal power flow opf is an important criterion in todays power system operation and control. Optimal power flow using particle swarm optimization. To do so, the optimization technique named particle swarm optimization pso is used. Ga and hybrid particle swarm optimization is used for distribution state estimation 10. Abstractthe distributed optimal power flow problem is addressed. Optimal power flow by particle swarm optimization with an aging. Optimal power flow using genetic algorithm andparticle. Constrained power loss minimization of dc microgrid using. Optimal power flow by vector pso file exchange matlab. Keywords transmission line, a shunt capacitor bank or a generation unit is artificial intelligence, distribution system, particle swarm optimization, power system restoration. In computational science, particle swarm optimization pso is a computational method that optimizes a problem by iteratively trying to improve a candidate solution with regard to a given measure of quality. Abstractthis article presents a hybrid algorithm based on the particle swarm optimization and gravitational search algorithms for solving.
Constrained optimal power flow using particle swarm optimization. Reactive power optimization using particle swarm optimization urvi c. Particle swarm optimization pso is a technique used to explore the search space of a given problem to. Pso learns from the scenario and uses it to solve the optimization problems 910. Particle swarm optimization as described by the inventers james kennedy and russell eberhart, particle swarm algorithm imitates human or insects social behavior. Key words load flow analysis, particle swarm optimization, artificial neural network, contingency analysis, voltage magnitudes, voltage angles. This issue can be formulated as a nonlinear optimization problem. Optimal power flow by particle swarm optimization for. Index terms independent system operator iso,particle swarm optimization pso, reactive optimal power flow ropf. Pdf optimal placement of distributed generation using. Particle swarm optimization based reactive power optimization. Optimal placement of facts devices using particle swarm. The pso technique nds the optimal solution using a population of particles.
Vaidya abstract optimal power flow opf problem in electrical power system is considered as a static, nonlinear, multiobjective or a single objective optimization problem. Each particle represents a candidate solution to the problem. Recent studies show that particle swarm optimization pso technique gives better results than classical optimization techniques, when applied to power engineering. Loss power minimization using particle swarm optimization. For load flow, newtonraphson method is used to calculate the power losses and voltage magnitude. The power loss minimization for distributed system has been performed with particle swarm optimization pso algorithm and the results are compared with forwardbackward load flow method. An improved particle swarm optimization algorithm using. Hybrid particle swarm optimization technique for optimal. A particle swarm optimization for reactive power and voltage control considering voltage stability. Particle swarm optimization pso, optimal power flow opf. Faculty of engineering, computer, and mathematical sciences. Introduction the power flow study is one of the most frequently carried out study performed by power utilities and. This often makes the problem even more computationally intensive.
It is an optimization problem try to make a redistribution of the active and reactive power caused a minimizing of an objective function with. Optimal power flow for steady state security enhancement using enhanced genetic algorithm with facts devices are proposed in 14,15. The power loss in electrical power systems is an important issue. In this paper, a modified smart technique using particle swarm optimization pso has been introduced to select the hourly optimal load flow with renewable. So, this paper aims at determining optimal dg allocation and sizing. Enhancement of power quality through particle swarm. Optimal power flow opf is one of the most effective tools used for the accurate analysis of power systems. Being a distributed solution, dfacts provides flexibility in terms of deployment. Power system restoration using particle swarm optimization. The various algorithms for solving such problems ca n be found in the literature. Study of using particle swarm for optimal power flow. Particle swarm optimization pso, genetic algorithm ga,flexible a. The particle swarm optimization algorithm pso is a populationbased optimization method that was rst proposed by kennedy and eberhart 10.
Optimal power flow by particle swarm optimization for reactive loss minimization pathak smita, prof. Particle swarm optimization for constrained and multiobjective problems. Optimization is a concept introduced for the optimization of nonlinear functions using particle swarm methodology. Reactive power optimization using particle swarm optimization. Optimal power flow using a hybrid optimization algorithm of. This paper presents a particle swarm optimization pso as an efficient approach for loss reduction study. Hybrid particle swarm optimization technique for optimal power flow leelaprasad.
Swarm intelligence ken 01, originally entitled particle swarm optimization pso, my friend jim kennedy has devoted three chapters out of eleven to this subject, above all as an illustration of the more general concept of collective intelligence without dwelling on the details of practical im plementation. Particle swarm optimization based method for optimal siting and sizing of multiple distributed generators naveen jain, s. Many techniques are used to reduce active power losses in a power system where the controlling of reactive power is one of the methods for decreasing the losses in any power system. In this paper, a modified smart technique using particle swarm optimization pso has been introduced to select the hourly optimal load flow with. Pdf optimal power flow using particle swarm optimization. They may be used to improve the transient responses of. Parameters optimization of deep learning models using. Optimal power flow using particle swarm optimization of. Srivastava, senior member, ieee d 16th national power systems conference, 15th17th december, 2010 669. Optimal power flow using particle swarm optimization of renewable hybrid distributed generation article pdf available in energies 107. In computational science, particle swarm optimization pso is a computational method that. This paper discussed the application of particle swarm optimization pso algorithm for power system state estimation. However, successful application of deep learning depends upon appropriately setting its parameters to achieve high quality results.
The particle swarm optimization algorithm abbreviated as pso is a novel populationbased stochastic search algorithm and an alternative solution to the complex nonlinear optimization problem. Deep learning has been successfully applied in several fields such as machine translation, manufacturing, and pattern recognition. In this paper, a particle swarm optimization pso with an aging leader and challengers alcpso is applied for the solution of opf problem of power system. Also, pso does not use the gradient of the problem being optimized, which means pso. Loss minimization using optimal power flow based on swarm intelligences 2 controllable system quantities are generator mw, controlled voltage magnitude, reactive power injection from reactive power sources and transformer tap setting.
Abibual abate mitaw lecturer department of ece bule hora university, bulehora, ethiopia. Mathematical modelling and applications of particle swarm. Particle swarm optimization with various inertia weight variants for. Particle swarm optimization comprises a very simple. Particle swarm optimization with various inertia weight. The main goal of this paper is to verify the viability of using pso.
Optimal location of facts for voltage stability using. Improved particle swarm optimization based loss minimization. The particle swarm optimization research toolbox is currently designed to handle continuous, singleobjective optimization problems. Proceedings of the inter conference on power systems technology, 2. Power flow ropf formulation is developed as an analysis tool and the validity of proposed method is examined using an ieee14 bus system. The objective used herein is to minimize the overall power transmission losses by optimizing the. Individuals interact with one another while learning from their own experience, and gradually the population members move into better regions of. Particle swarm optimization, evolutionary computation, reactive power and voltage control, mixedinteger nonlinear optimization problem, voltage securitycollapse point. The objective of the proposed method is to find the steadystate operating point which minimizes the fuel cost, while maintaining an acceptable system performance in terms of limits on generator power, line flow, and voltage. Particle swarm optimization pso is a population based stochastic optimization technique developed. Each particle represents a candidate solution to the problem at hand. Optimal power flow using particle swarm optimization m.