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This paper elucidatesa new improved optimization algorithm for economic Load dispatch (ELD) problem using self-adaptive real coded genetic algorithm. The ELD dilemma is formulated as a single-objective on-linear constrained optimization problem gratifying both equality and inequality constraints. The regeneration of population practice is integrated to the conventional real coded genetic algorithm...
This paper proposes a cuckoo search (CS) algorithm for economic dispatch (ED) of a power system integrated wind energy sources. The proposed algorithm is to seek the optimal generated-powers to minimize the total generation costs of the power system with thermal power plants. Additionally, the paper proposes to integrate the power system with wind energy sources which are renewable, widely distributed,...
The purpose of this work is to apply a hybrid algorithm based on Particle Swarm Optimization (PSO) and Genetic Algorithms (GA) for solving the problem of Economic Dispatch, which is based on supplying an energy demand, subjected to some restriction and reach out the best possible cost. Basically, we use the mutation operator from GAs aiming to explore regions in the search space that cannot be reached...
The location of a wind turbine is fundamental to enhance its performance. However, there are other factors that should be taken into account when deciding the best position for a wind turbine. This paper presents the influence of a wind penetration sitting in different distribution networks for the optimization of the economic dispatch problem. A genetic algorithm is developed to solve this problem...
This work proposes a novel heuristic-hybrid optimization method designed to solve the nonconvex economic dispatch problem in power systems. Due to the fast computational capabilities of the proposed algorithm, it is envisioned that it becomes an operations tool for both the generation companies and the TSO/ISO. The methodology proposed improves the overall search capability of two powerful heuristic...
This paper presents a new approach to emission constrained generation scheduling model based on cost optimization. The combined economic and emission dispatch is non-linear optimization problem with several constraints (economic and environmental) subject to reduce the emission of harmful pollutants and the operating cost of the thermal power plant. In this paper the problem of combined economic and...
In this paper, a self-adaptive differential evolution algorithm (SaDEA) is proposed for solving conventional economic dispatch (ED) problem with transmission losses consideration. The purpose of ED problem is to minimize the total fuel cost of thermal power plants associated with the technical operation and economical constraints. The software development has been performed within the mathematical...
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 paper introduced a genetic particle evolutionary swarm optimization (GPESO) for solving the economic dispatch (ED) in power systems. GPESO is based on the genetic particle swarm optimization (GPSO). GPSO was derived from the original particle swarm optimization (OPSO), which was incorporated with the genetic reproduction mechanisms, namely crossover and mutation. To enhance the search performance...
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