Levy Interior Search Algorithm-Based Multi-objective Optimal Reactive Power Dispatch for Voltage Stability Enhancement

Karthik, N.; Parvathy, A. K.; Arul, Rajakumar; Padmanathan, K.

doi:10.1007/978-981-15-7241-8_17

Cited by 7 publications

(3 citation statements)

References 32 publications

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“…Therefore, the following equation ( 6) exhibits the defined objective. The following expression [18] characterizes the 𝐿 𝑗 of the j th bus.…”

Section: Mitigation Of L-indexmentioning

confidence: 99%

Improved Mayfly Algorithm for Optimizing Power Flow with Integrated Solar and Wind Energy

Nagarajan,

Reddy,

Rajagopalan

et al. 2024

IJEER

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Across the globe, the transition towards sustainable energy systems necessitates seamless implementation of Renewable Energy Sources (RES) into traditional power grids. Such RESs include solar and wind power. The current research work intends to overcome the challenges associated with Optimal Power Flow (OPF) problem in power systems in which the traditional operation parameters ought to be optimized for effective and trustworthy integration of the RESs. The current study proposes an innovative nature-inspired approach by enhancing the Mayfly algorithm on the basis of mating behaviour of mayflies. The aim of this approach is to tackle the complexities introduced by dynamic and discontinuous nature of solar and wind power. The improved Mayfly algorithm aims at minimizing power losses, emission, optimize voltage profiles, and ensure reliable integration of solar and wind power. The current study outcomes provide knowledgeable insights towards power flow optimization in power systems with high penetration of renewable energy. The application results reveal that the improved mayfly algorithm achieved better efficacy compared to the classical mayfly algorithm and the rest of the optimization algorithms.

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“…Therefore, the following equation ( 6) exhibits the defined objective. The following expression [18] characterizes the 𝐿 𝑗 of the j th bus.…”

Section: Mitigation Of L-indexmentioning

confidence: 99%

Improved Mayfly Algorithm for Optimizing Power Flow with Integrated Solar and Wind Energy

Nagarajan,

Reddy,

Rajagopalan

et al. 2024

IJEER

View full text Add to dashboard Cite

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“…The first group is called composition group in which the composition of elements is changed to find a more beautiful view; whereas the second group is called mirror group in which mirrors are placed between these elements and the fittest element to find better views. Considering this concept, ISA method have been adopted to solve engineering optimization problem [214], economic dispatch problem [215], power dispatch problem [216]. To the author's knowledge, there is no single t-way strategy that adopt ISA method for combinatorial optimization.…”

Section: Human-based Techniquementioning

confidence: 99%

Review of Nature Inspired Metaheuristic Algorithm Selection for Combinatorial t-Way Testing

2022

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Metaheuristic algorithm is a very important area of research that continuously improve in solving optimization problems. Nature-inspired is one of the classifications of metaheuristic algorithm that are becoming more popular among researchers for the last decades. Nature-inspired metaheuristic algorithms contributes significantly to tackling many standing complex problems (such as combinatorial tway testing problem) and achieving optimal results. One challenge in this area is combinatorial explosion problem which always intended to find the most optimal final test suite that will cover all combinations of a given interaction strength. As such, test case generation is selected as the most active research area in combinatorial t-way testing as Non-deterministic Polynomial-time hardness (NP-hard). However, not all metaheuristics are effectively adopted in combinatorial t-way testing, some proved to be effective and thus have been popular tools selected for optimization whilst others are not adopted. This research paper outlines hundred and ten (110) outstanding nature-inspired metaheuristic algorithms for the last decades (2001 and 2021) such as Coronavirus Optimization Algorithm, Ebola Optimization Algorithm, Harmony Search, Tiki-Taka Algorithm, and so on. The purpose of this review is to revisit and carry out up-to-date review on these distinguished algorithms with their respective current state of use. This is to inspire future research in the field of combinatorial t-way testing for better optimization. Thus, we found that all metaheuristics has a simple structure to be adopted in different areas for becoming a more efficient in optimization. Finally, we suggested some future paths of investigation for researchers who are interested in the combinatorial t-way testing field to employ more of these algorithms by tuning their parameters setting to achieve an optimal solution.

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“…Many such optimization techniques have used since the last decade in the area ORPD, among which few recent methods are the Whale optimization algorithm (ben oualid Medani, K., Sayah, S., & Bekrar, A., 2018), Backtracking search optimizer (Shaheen, A. M., El-Sehiemy, R. A., & Farrag, S. M., 2016), Enhanced Red Wolf Optimization (Lenin, K., 2019), Improved social spider optimization (Nguyen, T. T., & Vo, D. N., 2020), Antlion optimization algorithm (Li, Z., Cao, Y., Dai, L. V., Yang, X., & Nguyen, T. T., 2019), Fractional swarming strategy (Yasir Muhammad, et. al, 2019), Tractable linear/quadratic programming (LP/QP) (P. Fortenbacher & T. Demiray, 2019), Stochastic fractal search method (Thanh Long Duong, Minh Quan Duong, Van-Duc Phan & Thang Trung Nguyen, 2020), Grey Wolf Optimization (GWO) algorithm (Jamal, R., Men, B., & Khan, N. H., 2020), Hybrid Grey Wolf Optimization and Particle Swarm Optimization (GWO-PSO) method (Mohamed A.M. Shaheen, Hany M. Hasanien & Abdulaziz Alkuhayli, 2020), Fractional particle swarm optimization gravitational search algorithm (Khan, N. H., et al 2020a), Water wave optimization algorithm (Zhou, Y., Zhang, J., Yang, X., & Ling, Y., 2020), Levy interior search algorithm (N. Karthik, A. K. Parvathy, R. Arul, & K. Padmanathan, 2021), Improved Differential Evolution Algorithm (Rui Chi, Zheng Li, Xuexin Chi, Zhijian Qu & Hong-bin Tu, 2021), Adaptive Range Composite Differential Evolution (Ming Niu, et. al, 2021), Improved Salp Swarm Algorithm (Andrei M. Tudose, Irina I. Picioroaga, Dorian O. Sidea & Constantin Bulac, 2021), etc.…”

Section: Introductionmentioning

confidence: 99%

A novel Weighted Adaptive Aquila Optimizer technique for solving the Optimal Reactive Power Dispatch problem

Das

Roy

Mandal

2022

Preprint

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The major problems in the field of power system engineering can be mostly solved with the help of the ORPD problem. Many recently developed optimization techniques have been implemented in this area of power system to optimize the objective function of minimum power loss, and determine its optimal solution leading to a more efficient and secured system. In this paper, a novel Weighted Adaptive Aquila Optimizer (WAAO) has been proposed to solve the highly complex and non-linear problem of Optimal Reactive Power Dispatch (ORPD). The Aquila optimizer (AO) has been modified with the addition of the unique search feature to develop an algorithm with the capability of optimizing any optimization technique faster and better compared to many other efficient techniques including AO technique. Here, the proposed algorithm has been tested on IEEE 30, 57 and 118 bus systems to minimize the power loss objective function of the ORPD problem, and obtain the optimal solutions to the control variables. The results obtained showed a significant improvement in terms of power saving by minimizing the power loss to a large margin for all the three mentioned test cases, which has not yet been reported earlier in the literature. The detailed study in this work proved that the WAAO has better optimization capability compared to AO and many other well-established techniques in solving the problem of ORPD.

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Levy Interior Search Algorithm-Based Multi-objective Optimal Reactive Power Dispatch for Voltage Stability Enhancement

Cited by 7 publications

References 32 publications

Improved Mayfly Algorithm for Optimizing Power Flow with Integrated Solar and Wind Energy

Improved Mayfly Algorithm for Optimizing Power Flow with Integrated Solar and Wind Energy

Review of Nature Inspired Metaheuristic Algorithm Selection for Combinatorial t-Way Testing

A novel Weighted Adaptive Aquila Optimizer technique for solving the Optimal Reactive Power Dispatch problem

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