Economic dispatch of all thermal power systems with fuzzy load

Madouh, Jamal Y.; El‐Hawary, Mohamed E.

doi:10.1109/lescpe.2004.1356257

Cited by 6 publications

(1 citation statement)

References 23 publications

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“…Venkatesh et al, [15] applied Economic load dispatch (ELD) and economic emission dispatch (EED) to get optimum fuel value and optimum emission of generating units, severally. Madouh and El-Hawary [16] presented a completely new and easy technique to elucidate the optimal resolution of a short-term economic disadvantage of all thermal power systems when the load on the system was fuzzy.…”

Section: Introductionmentioning

confidence: 99%

A Multi-Restart Dynamic Harris Hawk Optimization Algorithm for the Economic Load Dispatch Problem

2021

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In this study, we propose an algorithm based on a recently proposed metaheuristic called the Harris Hawk Optimization (HHO). We utilized a dynamic control strategy to enhance the exploration capability. To further avoid trapping in local optima, we incorporate opposition-based learning (OLB) and a multi-restart strategy. The proposed algorithm is used to solve economic load dispatch (ELD) problems with non-smooth cost functions. The ELD problems have a very large search space and therefore it is difficult to find global optimum using analytical methods. The results of the proposed approach are very competitive compared with notable results from previous research.

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Section: Introductionmentioning

confidence: 99%

A Multi-Restart Dynamic Harris Hawk Optimization Algorithm for the Economic Load Dispatch Problem

2021

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An Interval Fuzzy Optimization-Based Technique to Optimal Generation Scheduling with Load Uncertainty

2016

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A fuzzy interval optimization-based approach to optimal generation scheduling in uncertainty environment

Derghal

Goléa

Essounbouli

2016

Journal of Renewable and Sustainable Energy

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This paper proposes a fuzzy interval optimization approach to solve the Environmental/Economic Dispatch (EED) problem with uncertain parameters in the constraints and the objective functions. The objective functions considered are fuel cost and the gaseous emissions of the generating units. Two different types of fuel cost functions are considered in this study, namely, the conventional quadratic function and the augmented quadratic function to introduce more accurate modeling that incorporates the valve loading effects. The latter model presents non-differentiable and nonconvex regions that challenge most gradient-based optimization algorithms. In the proposed approach, objective functions are fuzzified and integrated to represent the fuzzy decision value. On the other hand, load uncertainties are modeled using fuzzy intervals. This fuzzy EED problem formulation provides a modeling flexibility, relaxation in constraints and allows the method to seek a practical solution. The obtained fuzzy multi-objective optimization problem is solved using non-dominated sorting genetic algorithm-II, known for its global searching capabilities, to get the best compromise among all the objectives. The performance of this solution is examined and applied to the standard IEEE 30-bus six-generator test system and the Indian power network of 82-bus by comparing its results with that of the existing methods. Different cases with different complexities have been considered in the study reported in this paper.

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Economic dispatch of all thermal power systems with fuzzy load

Cited by 6 publications

References 23 publications

A Multi-Restart Dynamic Harris Hawk Optimization Algorithm for the Economic Load Dispatch Problem

A Multi-Restart Dynamic Harris Hawk Optimization Algorithm for the Economic Load Dispatch Problem

An Interval Fuzzy Optimization-Based Technique to Optimal Generation Scheduling with Load Uncertainty

A fuzzy interval optimization-based approach to optimal generation scheduling in uncertainty environment

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