Voltage Constrained Reactive Power Planning Problem for Reactive Loading Variation Using Hybrid Harris Hawk Particle Swarm Optimizer

G., Swetha Shekarappa; Mahapatra, Sheila; Raj, Saurav

doi:10.1080/15325008.2021.1970060

Cited by 43 publications

(18 citation statements)

References 46 publications

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“…Shekarappa et al [207] used a hybrid algorithm between HHO and PSO called (HHOPSO) to solvea reactive power planning problem. The HHOPSO was tested using IEEE 57-bus.…”

Section: Hho Applicationsmentioning

confidence: 99%

Recent Advances in Harris Hawks Optimization: A Comparative Study and Applications

et al. 2022

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The Harris hawk optimizer is a recent population-based metaheuristics algorithm that simulates the hunting behavior of hawks. This swarm-based optimizer performs the optimization procedure using a novel way of exploration and exploitation and the multiphases of search. In this review research, we focused on the applications and developments of the recent well-established robust optimizer Harris hawk optimizer (HHO) as one of the most popular swarm-based techniques of 2020. Moreover, several experiments were carried out to prove the powerfulness and effectivness of HHO compared with nine other state-of-art algorithms using Congress on Evolutionary Computation (CEC2005) and CEC2017. The literature review paper includes deep insight about possible future directions and possible ideas worth investigations regarding the new variants of the HHO algorithm and its widespread applications.

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“…Shekarappa et al [207] used a hybrid algorithm between HHO and PSO called (HHOPSO) to solvea reactive power planning problem. The HHOPSO was tested using IEEE 57-bus.…”

Section: Hho Applicationsmentioning

confidence: 99%

Recent Advances in Harris Hawks Optimization: A Comparative Study and Applications

et al. 2022

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“…It is applied to the standard IEEE-57 bus system. Shekarappa et.al [9] have presented a hybrid Harris hawk particle swarm optimization for optimal reactive power planning issues by installing the reactive compensation at the weak bus. The weak buses are first detected by using VCPI and then the reactive sources are installed on these buses.…”

Section: Literature Surveymentioning

confidence: 99%

Statistical Analysis of Modified Whale Optimization Algorithm for Active Power Loss Minimization

Sahay

Upputuri

Kumari

et al. 2022

Preprint

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Optimal reactive power dispatch has an influential impact on improving the power quality of different utilities connected to the power system. It is a non-linear, non-convex, mixed-integer type problem formulated to minimize the active power loss considering generator voltage, tap setting value, and reactive power compensation as a control variable. In this article, a novel modified whale optimization algorithm is applied to solve this problem. A non-linear adaptive weight and an improved golden sign operator are being used to modify the basic whale algorithm. It improves the randomness due to parameter variation and enlarges the search area for accurate global solutions. It prevents the algorithm from local convergence. It also improves the convergence speed as compared to the basic whale optimization algorithm. It is tested and verified on the standard IEEE-57 bus system and IEEE-118 bus system. The solutions given by this method are compared with that of recently developed techniques for proving its dominance over the other techniques. The power losses of the IEEE-57 bus system are reduced to 1.78% and for the IEEE-118 bus system are reduced to 2.66%. Additionally, the comparative statistical analysis is performed in terms of the probability density function and cumulative density function along with the Wilcoxon rank test on the above test systems for 30 independent runs. The statistical analysis results prove that this algorithm is highly efficient in solving this problem compared to other techniques.

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“…Additionally, many optimization methods have been used to solve various problems [22]. It is also worth mentioning that the optimization methods proved their ability in solving many other problems such as solve complex engineering optimization problems [23], reactive power planning problems [24], parameter estimation problems [25], voltage-constrained power problems [26], and others.…”

Section: Introductionmentioning

confidence: 99%

Hybrid Reptile Search Algorithm and Remora Optimization Algorithm for Optimization Tasks and Data Clustering

Almotairi

Abualigah

2022

Symmetry

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Data clustering is a complex data mining problem that clusters a massive amount of data objects into a predefined number of clusters; in other words, it finds symmetric and asymmetric objects. Various optimization methods have been used to solve different machine learning problems. They usually suffer from local optimal problems and unbalance between the search mechanisms. This paper proposes a novel hybrid optimization method for solving various optimization problems. The proposed method is called HRSA, which combines the original Reptile Search Algorithm (RSA) and Remora Optimization Algorithm (ROA) and handles these mechanisms’ search processes by a novel transition method. The proposed HRSA method aims to avoid the main weaknesses raised by the original methods and find better solutions. The proposed HRSA is tested on solving various complicated optimization problems—twenty-three benchmark test functions and eight data clustering problems. The obtained results illustrate that the proposed HRSA method performs significantly better than the original and comparative state-of-the-art methods. The proposed method overwhelmed all the comparative methods according to the mathematical problems. It obtained promising results in solving the clustering problems. Thus, HRSA has a remarkable efficacy when employed for various clustering problems.

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Voltage Constrained Reactive Power Planning Problem for Reactive Loading Variation Using Hybrid Harris Hawk Particle Swarm Optimizer

Cited by 43 publications

References 46 publications

Recent Advances in Harris Hawks Optimization: A Comparative Study and Applications

Recent Advances in Harris Hawks Optimization: A Comparative Study and Applications

Statistical Analysis of Modified Whale Optimization Algorithm for Active Power Loss Minimization

Hybrid Reptile Search Algorithm and Remora Optimization Algorithm for Optimization Tasks and Data Clustering

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