Abstract

Economic load dispatch solutions based on published methods, both conventional and artificial, have been very well-formulated through point-to-point movement methodologies to reach a convergence point. Iteration always starts from the starting point to obtain the following solution point, leading to the convergence point. This paper presents a new method to solve economic load dispatch problems by narrowing the minimum and maximum power limits between generator units. This idea approximates the solution point with a tiny space formed by the very narrow power limits of each generator. The methodology used is the distance between the minimum and maximum power limits of each generator divided into several segments. Then, the best segment is determined by the minimum total cost calculated based on the center point of the segment. Continue to the following iteration process until the best segment is the smallest. This iteration process is another artificial method that works without calculus calculations, so it does not depend on the objective function. This method has been validated using two generator units with differentiable objective functions, with calculation accuracy less than 0.00001 MW of the power distance of the generator limit, and the iteration stops at the <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$23^{\mathrm {rd}}$ </tex-math></inline-formula> step. Furthermore, this method has been successfully applied to the nondifferentiable objective function, piecewise and valve point effects.

Highlights

  • Economic dispatch problem (EDP) practices are always an interesting study

  • The DSD method shows the best results with balanced power compared to the Hybrid Genetic Algorithm (HGA) method at different solution points

  • The methodology developed narrows the feasible area at each iteration step to obtain a tiny feasible area

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Summary

Introduction

Economic dispatch problem (EDP) practices are always an interesting study. The EDP can generally be differentiated into differentiable EDPs and nondifferentiable EDPs. Examples of nondifferentiable EDP objective functions are non-smooth functions, having prohibited operation zones and steps. The development of this objective function has prompted experts to study it. The actual operation of the power plant can cause undifferentiated ELD problems, such as a non-smooth objective function and the presence of POZ in the fuel cost curve [2-4]. This makes the EDP problem even more complicated because it changes its objective function. This method consists of an artificial network and a Lagrange multiplier. Economic Dispatch (ED) problem solving by considering valve point effect (VPE), transmission loss, and restricted operating zone (POZ) has VOLUME XX, 2017

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