SOLVING ECONOMIC DISPATCH PROBLEM USING PARTICLE SWARM OPTIMIZATION BY AN EVOLUTIONARY TECHNIQUE FOR INITIALIZING PARTICLES (original) (raw)
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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.
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.
Power Economic Dispatch Using Particle Swarm Optimization
Current market environment, ever growing difference between depleting energy resources and increasing power demand and increased expectations of customers from utility companies has made it necessary to adopt some good operational policies by electric utility companies. So the focus of utility companies has shifted towards increased customer focus, enhanced performance and to provide reliable supply at low cost. The electric power system must be operated in a way to schedule generations economically of generation facilities. In last two decades many evolutionary techniques has been developed to solve the optimization problems. Particle swarm optimization has acquired much recognition due to less memory requirement and its inherent simplicity. Particle swarm optimization technique proved to be having strong potential for solving complex and high dimensional optimization problem. PSO is free from local minimum solution convergence which is often encountered while solving nonlinear and non-convex optimization problem through conventional techniques. This paper presents a summarized view of application of PSO for solving power economic dispatch problem.
This paper describe about the optimization of economic loading dispatch (ELD) problem. Economic loading dispatch is one of the important optimization tasks which provide economic condition for a power system. The ELD problems have non-smooth objective function with equality and inequality constraints. This paper presents particle swarm optimization (PSO) method for solving the economic dispatch(ED) problem in power system. The particle swarm optimization is an efficient and reliable evolutionary computational technique, which is used to solve economic load dispatch with line power flows. This paper describes, a new PSO framework used to deal with the equality and inequality constraints in ELD problem. The proposed PSO can always provide satisfying results within a realistic computation time. The PSO is applied with non-smooth cost function. The six thermal units, 26 buses and 46 transmission lines system is used in this paper. The proposed PSO method results are compared with the genetic algorithm (GA) and conventional method to show the effectiveness of PSO method to solve the ELD problems in power system.
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.
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.
International Journal of Electrical and Computer Engineering (IJECE), 2020
Economic load dispatch problem under the competitive electric market (ELDCEM) is becoming a hot problem that receives a big interest from researchers. A lot of measures are proposed to deal with the problem. In this paper, three versions of PSO method such as conventional particle swarm optimization (PSO), PSO with inertia weight (IWPSO) and PSO with constriction factor (CFPSO) are applied for handling ELDCEM problem. The core duty of the PSO methods is to determine the most optimal power output of generators to obtain total profit as much as possible for generation companies without violation of constraints. These methods are tested on three and ten-unit systems considering payment model for power delivered and different constraints. Results obtained from the PSO methods are compared with each other to evaluate the effectiveness and robustness. As results, IWPSO method is superior to other methods. Besides, comparing the PSO methods with other reported methods also gives a conclusion that IWPSO method is a very strong tool for solving ELDCEM problem because it can obtain the highest profit, fast converge speed and simulation time.
Particle Swarm Optimization to solve Economic Dispatch considering Generator Constraints
2014
As we know that electrical energy plays a major role in day to day human life. It is not possible to imagine human life without electrical energy. This is because of the storage problem i.e. the electrical energy cannot be strong but is generated from natural sources and delivered as demand arises. An electrical engineer always tries to generate, transmit, and distribute the electrical energy at affordable cost while satisfying the constraints. Economic Dispatch is the process of allocation of optimal load to each committed generators while satisfying the equality and inequality constraints. The objective is to minimize the fuel cost by maintaining the generation power in limits and to reduce the computational time. The Economic Dispatch(ED) has been frequently solved by using classical optimization methods. In this proposed method the ED problem is formulated and solved by Particle Swarm Optimization technique. Three case studies are carried out on 6-unit and 15-unit systems. The solution is developed using MATLAB. Cost Generation is taken as an objective function and it is compared with the results of Genetic Algorithm (GA).