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This paper aims at providing a solution to Optimum Power Flow (OPF) in practical power systems by using a flexible genetic algorithm (GA) model. The proposed approach finds the optimal setting of OPF control variables which include generator active power output, generator bus voltages, transformer tap-setting and shunt devices with the objective function of minimising the fuel cost. The proposed GA...
This paper proposes a novel global optimization technique to solve the nonconvex economic load dispatch (NCELD) problem. The foraging strategy of the pachycondyla apicalis ant (API) is hybridized with a genetic algorithm (GA) strategy to incorporate key features of both API and GA and form a relatively simple but robust algorithm, entitled GAAPI. The novel algorithm proposed in this paper combines...
This study presents a new approach to solve the well-known power system economic load dispatch problem (ED) using a hybrid algorithm consisting of genetic algorithm (GA), pattern search (PS) and sequential quadratic programming (SQP). GA is the main optimizer of this algorithm, whereas PS and SQP are used to fine-tune the results obtained from the GA, thereby increasing solution confidence. To test...
This paper presents the application of self adaptation phenomenon in real-coded genetic algorithms (GA) for the solution of economic dispatch (ED) problems, taking into account the nonlinear generator characteristics such as prohibited operating zones and ramp-rate limits. The self adaptation is achieved by means of tournament selection along with simulated binary crossover (SBX). This selection process...
Economic dispatch is one of the most challenging problems of power system. Various algorithms for solving optimal power flow problem are found in the literature. The Genetic Algorithm (GA) based solution techniques are more promising than other techniques due to its capability of global searching, robustness, and it does not require derivative information. This paper presents a genetic-fuzzy based...
In this paper, an improved genetic algorithm is proposed to solve the economic dispatch (ED) problem with valve point loading effects. The proposed algorithm reduces the dimension of the search space in a certain way such that it is less time consuming. The evolutionary algorithm is proved to be efficient in solving the economic dispatch problem. Furthermore, it provides a suitable framework for future...
This paper proposes a particle swarm optimization (PSO) method for solving the economic dispatch (ED) problem in power systems. Many nonlinear characteristics of the generator are considered for practical generator operation, such as ramp rates, prohibited operating zones, and non-smooth cost functions. The feasibility of the proposed method is demonstrated for two different systems, and is Compared...
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