Improved particle swarm optimization algorithms for economic load dispatch considering electric market (original) (raw)
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Solution to Economic Load Dispatch using Particle Swarm Optimization
2014
This paper proposes to determine the feasible optimal solution of the economic load dispatch power systems problem using Particle Swarm Optimization (PSO) considering various generator constraints. The objective of the proposed method is to determine the steady-state operating point which minimizes the fuel cost, while maintaining an acceptable system performance in terms of limits on generator power, line flow, prohibited operating zone and non linear cost function. Three diff erent inertia weights; a constant inertia weight CIW, a timevarying inertia weight TVIW, and global-local best inertia weight GLbestIW, are considered with the (PSO) algorithm to analyze the impact of inertia weight on the performance of PSO algorithm. The PSO algorithm is simulated for each of the method individually. It is observed that the PSO algorithm with the proposed inertia weight (GLbestIW) yields better results, both in terms of optimal solution and faster convergence.
Particle Swarm Optimization Approach For Economic Load Dispatch: A Review
Particle swarm optimization (PSO) is an effective & reliable evolutionary based approach .Due to its higher quality solution including mathematical simplicity, fast convergence & robustness it has become popular for many optimization problems. There are various field of power system in which PSO is successfully applied. Economic Load Dispatch(ELD) is one of important tasks which provide an economic condition for a power system. it is a method of determine the most efficient, low cost & reliable operation of a power system by dispatching the available electricity generation resources to supply the load on the system. This paper presents a review of PSO application in Economic Load Dispatch problems.
Implementing Particle Swarm Optimization to Solve Economic Load Dispatch Problem
2009 International Conference of Soft Computing and Pattern Recognition, 2009
Economic Load Dispatch (ELD) is one of an important optimization tasks which provides an economic condition for a power systems. In this paper, Particle Swarm Optimization (PSO) as an effective and reliable evolutionary based approach has been proposed to solve the constraint economic load dispatch problem. The proposed method is able to determine, the output power generation for all of the power generation units, so that the total constraint cost function is minimized. In this paper, a piecewise quadratic function is used to show the fuel cost equation of each generation units, and the B-coefficient matrix is used to represent transmission losses. The feasibility of the proposed method to show the performance of this method to solve and manage a constraint problems is demonstrated in 4 power system test cases, consisting 3,6,15, and 40 generation units with neglected losses in two of the last cases. The obtained PSO results are compared with Genetic Algorithm (GA) and Quadratic Programming (QP) base approaches. These results prove that the proposed method is capable of getting higher quality solution including mathematical simplicity, fast convergence, and robustness to solve hard optimization problems.
Economic Load Dispatch is very vital research in generation of electrical power system. It is method by which we can make a plan of the preeminent achievable output of a number of generators power units so that to meet the domestic, industrial agriculture load demand at minimum possible cost, while satisfy all transmissions loss and operational constraints. This research paper tries to present the relevance of particle swarm optimization technique for the mathematical formulation of Economic load dispatch problem using soft computing technique in power generation system considering various parameters like load demand, physical and generation system constraints.
Application of Improved Particle Swarm Optimization in Economic Dispatch of Power System
2017 10th International Symposium on Computational Intelligence and Design (ISCID), 2017
This paper introduces an improved particle swarm optimization to solve economic dispatch problems involving numerous constraints. Depending on the type of generating units, there are optimization constraints and practical operating constraints of generators such as prohibited operating zones and ramp rate limits. The algorithm is a hybrid technique made up of particle swarm optimization and bat algorithm. Particle swarm optimization as the main algorithm integrates bat algorithm in order to boost its velocity and adjust the improved solution. The new technique is firstly tested on five different cases of economic dispatch problems comprising 6, 13, 15, 40 and 140 generating units. The simulation results show that it performs better than both particle swarm and bat technique.
International Journal of Science and Research (IJSR), 2016
The economic load dispatch plays a crucial role in the operation of the power grid. The unit commitment or pre-dispatch is the first problem, to satisfy the expected load and supply a specified margin of operational reserve over a specified amount of your time and second side of economic dispatch is that the online economic dispatch, whereby it's needed to distribute the load amongst offered generating units paralleled with the system in such a way. In this practice to optimize the load dispatch at minimum cost there is to work is going on like Genetic algorithm, artificial bee colony, bat algorithm, lambda iteration etc. this paper used particle swarm optimization techniques to obtain the optimized solution of economic dispatch. In this paper, we study different cases to find the suitable solution for Economic load dispatch.
2015
One of the most important tasks in power system is to determine and provide an economic condition for generating unit while satisfying all the constraints, which is known as Economic Load Dispatch (ELD). This paper presents particle swarm optimization technique for solving ELD problem. The proposed method is used to solve economic dispatch problem for three and six generating unit system with and without transmission losses. The result obtained by PSO method is compared with the result of the traditional lambda iteration method. The comparison shows that the PSO is capable of providing a higher quality solution with fast convergence in ELD problem.
An Extension of Particle Swarm Optimization (E-PSO) Algorithm for Solving Economic Dispatch Problem
2013 1st International Conference on Artificial Intelligence, Modelling and Simulation, 2013
Producing the energy power that meets the load demands at a minimum cost while satisfying the constraints is known as economic dispatch. Economic dispatch becomes one of the most complex problems in the planning and operation of a power system that aims to determine the optimal generation scheduling at minimum cost. For that reason many optimization researches on finding an optimal solution regarding the total cost of generation have been carried out. This paper presents the implementation of the extension of the PSO (E-PSO) system in solving the continuous nonlinear function of the cost curves of the generator. In this paper, a 6unit generation system has been applied to show the effectiveness of the E-PSO compared to the standard PSO. The results show that E-PSO is capable in solving the economic dispatch problem in term of minimizing the total cost of generation while considering the generator limits and transmission losses.