Modified cuckoo search algorithm for multiobjective short-term hydrothermal scheduling

Nguyen, Thang Trung; Vo, Dieu Ngoc

doi:10.1016/j.swevo.2017.05.006

Cited by 30 publications

(13 citation statements)

References 29 publications

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“…References [183], [184] have incorporated variants of canonical CS algorithms by making modifications in the Levy flights update to enhance the searchability of the conventional CS algorithm, to solve the MOSTHTS problem. Several test cases of MOSTHTS problems, considering, quadratic fuel cost functions/quadratic while considering power losses in the transmission system.…”

Section: Cuckoo Search Optimization Algorithm Applied On Sthts Problemmentioning

confidence: 99%

“…Reference [189] has implemented three distributions including Lévy distribution, Gaussian distribution and Cauchy distribution in the update equations of the Cuckoos search algorithm to solve CSTHTS problem. Reference [190] has implemented two distributions based Lévy distribution, in the update equations of the Cuckoos search algorithm to solve CSTHTS problem. In this modified method, the nests in the update process are classified into two groups i.e.…”

Section: Evolutionary Programming Algorithmsmentioning

confidence: 99%

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Conventional and Metaheuristic Optimization Algorithms for Solving Short Term Hydrothermal Scheduling Problem: A Review

et al. 2021

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Short term hydrothermal scheduling (STHTS) is a non-linear, multi-modal and very complex constrained optimization problem which has been solved using several conventional and modern metaheuristic optimization algorithms. A number of research articles have been published addressing STHTS using different techniques. This article presents a comprehensive review of research published for solving the STHTS problem in the last four decades.INDEX TERMS Short term hydrothermal scheduling, conventional algorithms, meta-heuristic algorithms, no free lunch theorem

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Section: Cuckoo Search Optimization Algorithm Applied On Sthts Problemmentioning

confidence: 99%

Section: Evolutionary Programming Algorithmsmentioning

confidence: 99%

Conventional and Metaheuristic Optimization Algorithms for Solving Short Term Hydrothermal Scheduling Problem: A Review

et al. 2021

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“…where rn s is a random number of the sth solution and randomly produced in the range between 0 and 1; and α is Lévy factor and determined as follows [38,39]:…”

Section: The Second Modificationmentioning

confidence: 99%

Finding Solutions for Optimal Reactive Power Dispatch Problem by a Novel Improved Antlion Optimization Algorithm

Cao

Đại

et al. 2019

Energies

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In this paper, a novel improved Antlion optimization algorithm (IALO) has been proposed for solving three different IEEE power systems of optimal reactive power dispatch (ORPD) problem. Such three power systems with a set of constraints in transmission power networks such as voltage limitation of all buses, limitations of tap of all transformers, maximum power transmission limitation of all conductors and limitations of all capacitor banks have given a big challenge for global optimal solution search ability of the proposed method. The proposed IALO method has been developed by modifying new solution generation technique of standard antlion optimization algorithm (ALO). By optimizing three single objective functions of systems with 30, 57 and 118 buses, the proposed method has been demonstrated to be more effective than ALO in terms of the most optimal solution search ability, solution search speed and search stabilization. In addition, the proposed method has also been compared to other existing methods and it has obtained better results than approximately all compared ones. Consequently, the proposed IALO method is deserving of a potential optimization tool for solving ORPD problem and other optimization problems in power system optimization fields.

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“…It was inspired by the behavior of some cuckoo species by laying eggs in the nests of other host birds. Compared to other artificial intelligence algorithms such as the genetic algorithm (GA) [26] and particle swarm optimization (PSO) [27], CS has the characteristics of higher solution quality, shorter computational time, and higher success rates [28]. It has been applied to various optimization problems.…”

Section: Introductionmentioning

confidence: 99%

A Gradient-Based Cuckoo Search Algorithm for a Reservoir-Generation Scheduling Problem

Yang

Zhou

et al. 2018

Algorithms

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Abstract:In this paper, a gradient-based cuckoo search algorithm (GCS) is proposed to solve a reservoir-scheduling problem. The classical cuckoo search (CS) is first improved by a self-adaptive solution-generation technique, together with a differential strategy for Lévy flight. This improved CS is then employed to solve the reservoir-scheduling problem, and a two-way solution-correction strategy is introduced to handle variants' constraints. Moreover, a gradient-based search strategy is developed to improve the search speed and accuracy. Finally, the proposed GCS is used to obtain optimal schemes for cascade reservoirs in the Jinsha River, China. Results show that the mean and standard deviation of power generation obtained by GCS are much better than other methods. The converging speed of GCS is also faster. In the optimal results, the fluctuation of the water level obtained by GCS is small, indicating the proposed GCS's effectiveness in dealing with reservoir-scheduling problems.

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Modified cuckoo search algorithm for multiobjective short-term hydrothermal scheduling

Cited by 30 publications

References 29 publications

Conventional and Metaheuristic Optimization Algorithms for Solving Short Term Hydrothermal Scheduling Problem: A Review

Conventional and Metaheuristic Optimization Algorithms for Solving Short Term Hydrothermal Scheduling Problem: A Review

Finding Solutions for Optimal Reactive Power Dispatch Problem by a Novel Improved Antlion Optimization Algorithm

A Gradient-Based Cuckoo Search Algorithm for a Reservoir-Generation Scheduling Problem

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