Application of Coulomb’s and Franklin’s laws algorithm to solve large-scale optimal reactive power dispatch problems

Ghasemi, Maryam; Akbari, Ebrahim; Davoudkhani, Iraj Faraji; Rahimnejad, Abolfazl; Asadpoor, Mohammad Bagher; Gadsden, S. Andrew

doi:10.1007/s00500-022-07417-w

Cited by 17 publications

(11 citation statements)

References 83 publications

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“…To assess the effectiveness of the suggested algorithm in comparison to the original Rao algorithms, we have chosen 14 real-world shifted functions with 30 dimensions (including unimodal, multimodal, and expanded multimodal functions), numbered in the order introduced in CEC 2005 ( Liu et al, 2013 ), whose data were extracted from Suganthan et al (2005) . These functions have been successfully utilized in many articles ( Ghasemi, Aghaei & Hadipour, 2017 ; Birogul, 2019 ; Ghasemi et al, 2019 ; Ghasemi et al, 2022a ; Ghasemi et al, 2022b ; Ghasemi et al, 2023 ; Akbari, Rahimnejad & Gadsden, 2021 ; Premkumar et al, 2021 ; Zou et al, 2022 ). The total count of function evaluations (NFE) during the execution of each algorithm is considered 300,000 based on Liu et al (2013) ; accordingly, the number of population members of each algorithm during the optimization is 30; therefore, the convergence curves, in this study, have been extracted for 10,000 iterations.…”

Section: Numerical Results Of Fisa For Solving Benchmark Test Functionsmentioning

confidence: 99%

A new metaphor-less simple algorithm based on Rao algorithms: a Fully Informed Search Algorithm (FISA)

Ghasemi

Rahimnejad

Akbari

et al. 2023

PeerJ Computer Science

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Many important engineering optimization problems require a strong and simple optimization algorithm to achieve the best solutions. In 2020, Rao introduced three non-parametric algorithms, known as Rao algorithms, which have garnered significant attention from researchers worldwide due to their simplicity and effectiveness in solving optimization problems. In our simulation studies, we have developed a new version of the Rao algorithm called the Fully Informed Search Algorithm (FISA), which demonstrates acceptable performance in optimizing real-world problems while maintaining the simplicity and non-parametric nature of the original algorithms. We evaluate the effectiveness of the suggested FISA approach by applying it to optimize the shifted benchmark functions, such as those provided in CEC 2005 and CEC 2014, and by using it to design mechanical system components. We compare the results of FISA to those obtained using the original RAO method. The outcomes obtained indicate the efficacy of the proposed new algorithm, FISA, in achieving optimized solutions for the aforementioned problems. The MATLAB Codes of FISA are publicly available at https://github.com/ebrahimakbary/FISA.

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Section: Numerical Results Of Fisa For Solving Benchmark Test Functionsmentioning

confidence: 99%

A new metaphor-less simple algorithm based on Rao algorithms: a Fully Informed Search Algorithm (FISA)

Ghasemi

Rahimnejad

Akbari

et al. 2023

PeerJ Computer Science

Self Cite

View full text Add to dashboard Cite

show abstract

“…One of the most representative algorithms is the simulated annealing algorithm(SA) 45 , which performs the search by simulating the property changes during the annealing of metals. Other competitive algorithms include the simultaneous heat transfer search (SHTS) 46 , the special relativity search algorithm (SRS) 47 , Young's double-slit experiment optimization (YDSE) 48 , the Fick's law algorithm (FLA) 49 , and the Franklin's law algorithm (FLIA) 50 . The main search mechanisms of these algorithms are weight-based combination and domain search.…”

Section: Introductionmentioning

confidence: 99%

Symmetric projection optimizer: concise and efficient solving engineering problems using the fundamental wave of the Fourier series

Su,

Dong,

Liu

et al. 2024

Sci Rep

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The fitness function value is a kind of important information in the search process, which can be more targeted according to the guidance of the fitness function value. Most existing meta-heuristic algorithms only use the fitness function value as an indicator to compare the current variables as good or bad but do not use the fitness function value in the search process. To address this problem, the mathematical idea of the fitting is introduced into the meta-heuristic algorithm, and a symmetric projection optimizer (SPO) is proposed to solve numerical optimization and engineering problems more efficiently. The SPO algorithm mainly utilizes a new search mechanism, the symmetric projection search (SP) method. The SP method quickly completes the fitting of the projection plane, which is located through the symmetry of the two points and finds the minima in the projection plane according to the fitting result. Fitting by using the fitness function values allows the SP to find regions where extreme values may exist more quickly. Based on the SP method, exploration and exploitation strategies are constructed, respectively. The exploration strategy is used to find better regions, and the exploitation strategy is used to optimize the discovered regions continuously. The timing of the use of the two strategies is designed so that the SPO algorithm can converge faster while avoiding falling into local optima. The effectiveness of the SPO algorithm is extensively evaluated using seven test suites, including CEC2017, CEC2019, CEC2020, and CEC2022. It is also compared with two sets of 19 recent competitive algorithms. Statistical analyses are performed using five metrics such as the Wilcoxon test, the Friedman test, and variance. Finally, the practicality of the SPO algorithm is verified by four typical engineering problems and a real spacecraft trajectory optimization problem. The results show that the SPO algorithm can find superior results in 94.6% of the comparison tests and is a promising alternative for solving real-world problems.

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“…The proposed improvement relied on incorporating a new technique into TLBO, dubbed the "studying strategy," in which each member leverages the knowledge of another randomly selected participant to solve the OPF issues 7 . Large-scale optimal reactive power dispatch (LS-ORPD) problems were the topic of 8 , which examined how Coulomb's and Franklin's laws (CFA) may be applied to find optimal solutions. The safe and reliable functioning of electrical power grids is being increasingly affected by ORPD issues, making this a vital area of research.…”

Section: Introductionmentioning

confidence: 99%

“…Several restrictions from three IEEE standard power systems were used to verify the CFA optimizer's ability to resolve large-scale ORPD problems. When compared to existing solutions in the literature 8 , the proposed optimizer provides a more precise answer.…”

Section: Introductionmentioning

confidence: 99%

An enhanced turbulent flow of water-based optimization for optimal power flow of power system integrated wind turbine and solar photovoltaic generators

Zahedibialvaei,

Trojovský,

Hesari-Shermeh

et al. 2023

Sci Rep

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This paper uses enhanced turbulent flow in water-based optimization (TFWO), specifically ETFWO, to achieve optimal power flow (OPF) in electrical networks that use both solar photovoltaic (PV) units and wind turbines (WTs). ETFWO is an enhanced TFWO that alters the TFWO structure through the promotion of communication and collaboration. Individuals in the population now interact with each other more often, which makes it possible to search more accurately in the search area while ignoring local optimal solutions. Probabilistic models and real-time data on wind speed and solar irradiance are used to predict the power output of WT and PV producers. The OPF and solution methods are evaluated using the IEEE 30-bus network. By comparing ETFWO to analogical other optimization techniques applied to the same groups of constraints, control variables, and system data, we can gauge the algorithm’s robustness and efficiency in solving OPF. It is shown in this paper that the proposed ETFWO algorithm can provide suitable solutions to OPF problems in electrical networks with integrated PV units and WTs in terms of energy generation costs, improved voltage profiles, emissions, and losses, compared to the traditional TFWO and other proposed algorithms in recent studies.

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Application of Coulomb’s and Franklin’s laws algorithm to solve large-scale optimal reactive power dispatch problems

Cited by 17 publications

References 83 publications

A new metaphor-less simple algorithm based on Rao algorithms: a Fully Informed Search Algorithm (FISA)

A new metaphor-less simple algorithm based on Rao algorithms: a Fully Informed Search Algorithm (FISA)

Symmetric projection optimizer: concise and efficient solving engineering problems using the fundamental wave of the Fourier series

An enhanced turbulent flow of water-based optimization for optimal power flow of power system integrated wind turbine and solar photovoltaic generators

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