Optimal power flow using hybrid daapso algorithm in. Transient stability constrained optimal power flow using. Optimal power flow using particle swarm optimization m. Muthuselvan 1 assistant professor, department of electrical and electronics engineering, college of engineering, guindy, anna university chennai, india 600025. Pdf optimal power flow using particle swarm optimization. Optimal power flow opf with facts devices on ieee 30bus system is scrutinized. A power flow method which considers realistic situations such as. The distributed sobol particle swarm optimization dspso algorithm was studies for solving optimal power flow problem opf, in this paper. Solution methodologies for optimum power flow problem are extensively covered in this chapter. Optimal power flow solution using particle swarm optimization. Particle swarm optimization based method for optimal.
Venkata silpa 1 1pg scholar department of eee, prasad v. Multiobjective particle swarm optimization for optimal. This paper solves the multiobjective optimal power flow problem using a new hybrid technique by combining the particle swarm optimization and ant colony optimization. Optimal power flow by particle swarm optimization for. Optimal power flow opf is one of the most effective tools used for the accurate analysis of power systems. Human tremor analysis using particle swarm optimization. Ghoshalparticle swarm optimization with an aging leader and challengers algorithm for the solution of optimal power flow. Incorporation of pso as a derivativefree optimization technique in solving opf problem significantly relieves the assumptions imposed on the optimized objective functions. Keywords improved particle swarm optimization, optimal power flow, transient stability. Pdf optimal power flow using a hybrid optimization. Hybrid psomfo is a combination of pso used for exploitation phase and mfo for exploration phase in an uncertain environment. Selection of most effective control variables for solving.
In proceedings of 2005 international conference on machine learning and cybernetics, 1821 august 2005, 5. Optimal power flow in hvdc modelling using particle swarm. Optimal power flow using genetic algorithm andparticle. Particle swarm optimization pso is a populationbased optimization method first proposed by kennedy and. In this work, particle swarm optimization pso for the solution of the optimal power flow opf with use of controllable facts devices is studied. A novel approach to multiobjective particle swarm optimization mopso technique for solving optimal power flow opf problem is proposed in this chapter. Particle swarm optimization with various inertia weight variants for optimal power flow solution prabha umapathy,1 c. Optimal power flow based on particle swarm optimization 257 keeps the path of the particle in the best position according to the previous best position. Hybrid particle swarm optimization technique for optimal. Control variables like reactive power output of generators generator bus voltages, tap ratios of transformers and reactive power output of shunt compensators like capacitors etc. We propose two algorithms for the solution of the optimal power flow opf problem to global. Optimal power flow by particle swarm optimization for reactive loss minimization pathak smita, prof. Particle swarm optimization pso, genetic algorithm ga,flexible a.
This paper uses the particle swarm optimization algorithm for solving the optimal power. A modified particle swarm optimization algorithm and its application in optimal power flow problem. Pso implementation using matlab particle swarm optimization implementation. Vaidya abstract optimal power flow opf problem in electrical power system is considered as a static, nonlinear, multiobjective or a single objective optimization problem. Optimal power flow using moth swarm algorithm sciencedirect. Ieee 30bus test system has been adapted to study the implementation pso algorithm in opf of conventionalthermal generators. Hybrid particle swarm optimization technique for optimal power flow leelaprasad. Abibual abate mitaw lecturer department of ece bule hora university, bulehora, ethiopia. Abstractthis paper presents a method for optimal siting and sizing of multiple distributed generators dgs using particle swarm optimization pso. Pdf this article presents a hybrid algorithm based on the particle swarm optimization and gravitational search algorithms for solving optimal power. I have solved the optimal reactive power dispatch problem using particle swarm optimization algorithm for ieee 30 bus test system. Enhancement of voltage stability in power system using voltage stability constraint optimal power flow and particle swarm optimization algorithm 1s. Enhancement of voltage stability in power system using. Optimal placement of facts devices using particle swarm.
The proposed psobased approach is tested on an ieee 30bus radial. Pso algorithm for opf optimize power flow with matlab. The proposed approach employs particle swarm optimization pso algorithm for optimal settings of opf problem control variables. Optimal power flow by vector pso file exchange matlab. Abstract this paper proposes an approach to solve the optimal power flow opf problem with an aim to. Particle swarm optimizationpso let x and v denotes a particles coordinate position and its corresponding velocity in a search space. A particle swarm optimization is proposed to solve the opf problem. Abstract in this paper, an optimal power flow solution method incorporating a cost model that associates the uncertainty. 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. This paper presents an efficient and reliable evolutionarybased approach to solve the optimal power flow opf problem.
Aalborg universitet an optimal power flow opf method with. Optimal reactive power dispatchorpd using particle swarm. D p kothari, and i j nagrath, modern power system analysis 4 th edition, tata mcgraw hill education private limited, new delhi. Optimal power flow using particle swarm optimization. Two conflicting objectives, generation cost, and environmental pollution are minimized simultaneously. A particle swarm optimization based optimal power flow. Arsicoptimal power flow using a hybrid optimization algorithm of particle swarm optimization and gravitational. Two types of facts devices, thyristor controlled series compensator tcsc and thyristorcontrolled phase shifters tcps are considered in this method. Optimal power flow incorporating renewable uncertainty. 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. In this paper, a modified smart technique using particle swarm optimization pso has been introduced to select the hourly optimal load flow with.
It consists of several objective functions and constraints. This paper proposes an efficient method to solve the optimal power flow problem in power systems using particle swarm optimization pso. D lecturer department of ece bule hora university, bulehora, ethiopia. Different practical constraints are included into the opf problem. A particle swarm optimization for reactive power and voltage control in electric power systems, proc. Particle swarm optimization with various inertia weight. This option can reduce the cost of the generated energy and increase the system efficiency and reliability. You presented code that appears to implement particle swarm and you indicated a general desire i want to change my program for power flow, but you did not ask a question. 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. An optimal power flow opf method with improved power system stability. Selection of optimal location and size of distributed.
Optimal placement of distributed generation using particle. The new mopso technique evolves a multiobjective version of pso by proposing redefinition of global best and local best individuals in multiobjective optimization domain. In this paper, a modified smart technique using particle swarm optimization pso has been introduced. Thomas britto 1assistant professor, 2assistant professor, 3assistant professor 1electrical and electronics engineering. Optimal power flow using a hybrid particle swarm optimizer. The best position of each particle is called the individual best position or local best position pbest, while the best value over all the individual best. The proposed approach employs particle swarm optimization pso algorithm for optimal. Congress on evolutionary computation 1999, washington, dc, pp. Artificial electric field algorithm for optimal power flow.
In 12, developed a method for solving multiobjective optimal power flow using differential evolution algorithm. An optimal power flow to improve power system security by using particle swarm optimization b. Optimal placement of facts devices using particle swarm optimization technique for the increased loadability of a power system d. This paper presents a multiobjective optimal power flow technique using particle swarm. The proposed approach employs particle swarm optimization pso algorithm. This paper describes opf based on particle swarm optimization pso method in which total generation cost function is considered as the objective function. Hybrid swarm algorithm for multiobjective optimal power. Stability is an important constraint in power system operation. The obtained results using the ipso are compared with those obtained using other modern techniques for performance examination. Particle swarm optimization pso, optimal power flow opf, facts, emission control, power system. Optimal power flow for steady state security enhancement using enhanced genetic algorithm with facts devices are proposed in 14,15. This project aims to find the optimum sizing and location of dg in power system by using particle swarm optimization pso. A study of load flow analysis using particle swarm. Pdf optimal power flow using particle swarm optimization of.
Jayalaxmi2 1associate professor, electrical and electronics engineering department, kamala institute of technology and science, singapur, karimnagar, telangana state, india. An efficient particle swarm optimization algorithm to solve optimal. It assists in acquiring the optimized solution for the optimal power flow problem. Multi objective optimal power flow using particle swarm optimization. The particle swarm optimization pso is used to minimize the generating cost as an objective function through the inequality constraints as well as the conventional load flow is used to perform the equality constraints. An optimal power flow to improve power system security by. Padma combined economic and emission dispatch using multiobjective particle swarm optimization with svc installation,icettr20,page no. In this paper, a modified smart technique using particle swarm optimization pso has been introduced to select the hourly optimal load flow with renewable distributed generation dg integration. 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.
This adopted strategy would decrease the optimal power. Particle swarm optimization applied to optimal power flow solution. Learn more about pso, opf problem, power network, optimal power flow, ieee bus. This research presents a hybrid metaheuristic based optimization method, dragonfly algorithm da with aging particle swarm optimization apso for handling. In this paper, a modified smart technique using particle swarm optimization pso has been introduced to select the hourly optimal load flow with renewable distributed generation dg integration under different operating conditions in the 30bus ieee.
In the proposed method, swarm size of the particles is. The problem of voltage collapse in power systems due to increased loads can be solved by adding renewable energy sources like wind and photovoltaic pv to some busbars. Introduction optimal power flow opf is an important tool for power system operation, control and planning. In addition to selection of the most effective control variables based on sensitivity analysis to alleviate the violations and return the system back to its normal state. An intelligent alternating currentoptimal power flow for. Reduce the power system losses by the placement of tcsc using particle swarm optimization 21 3. Optimization methods application to optimal power flow in. Senthil arumugam2 1 faculty of engineering and technology, multimedia university, jalan ayer keroh lama, melaka 75450, malaysia 2 teaching fellow, school of engineering and physical sciences, heriotwatt. Calculate the loss using distribution load flow based on backwardforward sweep.
Optimal placement of distributed generation using particle swarm optimization wichit krueasuk. Ga and hybrid particle swarm optimization is used for distribution state estimation 10. Real coded genetic algorithm ga and particle swarm optimization pso methods developed using matlab are applied to ieee 14 and ieee 30 standart test. The optimal power flow opf is an important criterion in todays power system operation and control. Potluri siddhartha institute of technology, vijayawada, andhra pradesh, india. Objective of opf optimal power flow is to achieve reduction of power generation cost or loss by adjusting certain control variables while satisfying phys. A simple and effective cumulative performance index, utilizing voltage profile improvement, loss reduction and voltage stability index vsi improvement is considered in this work. Boukadoum3 1electrical engineering department, laboratory of electrotechnics of skikda, university of august 20th, 1955, skikda, algeria 2electrical engineering department, laboratory of electrotechnics of skikda. Optimal location and sizing of dg ieee 33 bus system. Optimal power flow using particle swarm optimization of. Arsicoptimal power flow using a hybrid optimization algorithm of particle swarm optimization and gravitational search algorithm electr. Power system, transient stability constrained optimal power flow tscopf, improved particle swarm optimizer ipso, optimal power flow opf, contingencies. In optimization, many techniques are used to solve the problem in power system.