A Novel Hybrid Particle Swarm Optimization and Sine Cosine Algorithm for Seismic Optimization of Retaining Structures

This study introduces an effective hybrid optimization algorithm, namely Particle Swarm Sine Cosine Algorithm (PSSCA) for numerical function optimization and automating optimum design of retaining structures under seismic loads. The new algorithm employs the dynamic behavior of sine and cosine functions in the velocity updating operation of particle swarm optimization (PSO) to achieve faster convergence and better accuracy of final solution without getting trapped in local minima. The proposed algorithm is tested over a set of 16 benchmark functions and the results are compared with other well-known algorithms in the field of optimization. For seismic optimization of retaining structure, Mononobe-Okabe method is employed for dynamic loading condition and total construction cost of the structure is considered as the objective function. Finally, optimization of two retaining structures under static and seismic loading are considered from the literature. As results demonstrate, the PSSCA is superior and it could generate better optimal solutions compared with other competitive algorithms

Adaptive Rat Swarm Optimization for Optimum Tuning of SVC and PSS in a Power System

This paper presents a new approach for the coordinated design of a power system stabilizer- (PSS-) and static VAR compensator- (SVC-) based stabilizer. For this purpose, the design problem is considered as an optimization problem, while the decision variables are the controllers' parameters. This paper proposes an effective optimization algorithm based on a rat swarm optimizer, namely, adaptive rat swarm optimization (ARSO), for solving complex optimization problems as well as coordinated design of controllers. In the proposed ARSO, instead of a random initial population, the algorithm starts the search process with fitter solutions using the concept of the opposite number. In addition, in each iteration of the optimization, the new algorithm replaces the worst solution with its opposite or a random part of the best solution to avoid getting trapped in local optima and increase the global search ability of the algorithm. The performance of the new ARSO is investigated using a set of benchmark test functions, and the results are compared with those of the standard RSO and some other methods from the literature. In addition, a case study from the literature is considered to evaluate the efficiency of the proposed ARSO for coordinated design of controllers in a power system. PSSs and additional SVC controllers are being considered to demonstrate the feasibility of the new technique. The numerical investigations show that the new approach may provide better optimal damping and outperform previous methods

Economic Design of Retaining Wall Using Particle Swarm Optimization with Passive Congregation

Abstract: This paper presents an effective optimization method for nonlinear constrained optimization of retaining structures. The proposed algorithm is based on the particle swarm optimization with passive congregation. The optimization procedure controls all geotechnical and structural design constraints while reducing the overall cost of the retaining wall. To applying the constraints, the algorithm employs penalty function method. To verify the efficiency of the proposed method, two design examples of retaining structures are illustrated. Comparison analysis between the results of the presented methodology, standard particle swarm optimization and nonlinear programming optimization method show the ability of the proposed algorithm to find better optimal solutions for retaining wall tasks than the others

Golden Search Optimization Algorithm

n/

Simultaneous Employment of Generation Rescheduling and Incentive-based Demand Response Programs for Congestion Management in Case of Contingency

Relieving congestion significantly influences the operation and security of the transmission network. Consequently, the congestion alleviation of transmission network in all power systems is imperative. Moreover, it could prevent price spikes and/or involuntary load shedding and impose high expenses on the transimission network, especially in case of contingency. Traditionally, the increasing or decreasing generation rescheduling has been used as one of the most imperative approaches for correctional congestion management when a contingency occurs. However, demand response programs (DRPs) could also be a vital tool for managing the congestion. Therefore, the simultaneous employment of generation rescheduling and DRPs is proposed for congestion management in case of contingency. The objective is to reschedule the generation of power plants and to employ DRPs in such a way so as to lessen the cost of congestion. The crow search algorithm is employed to determine the solution. The accuracy and efficiency of the proposed approach are assessed through the tests conducted on IEEE 30-bus and 57-bus test systems. The results of various case studies indicate the better performance of the proposed approach in comparison with different approaches presented in the literature

A Novel Hybrid Sine Cosine Algorithm and Pattern Search for Optimal Coordination of Power System Damping Controllers

This paper presents an effective hybrid optimization technique based on a chaotic sine cosine algorithm (CSCA) and pattern search (PS) for the coordinated design of power system stabilizers (PSSs) and static VAR compensator (SVC)-based controllers. For this purpose, the design problem is considered as an optimization problem whose decision variables are the controllers’ parameters. Due to the nonlinearities of large, interconnected power systems, methods capable of handling any nonlinearity of power networks are preferable. In this regard, a nonlinear time domain-based objective function was used. Then, the proposed hybrid chaotic sine cosine pattern search (hCSC-PS) algorithm was employed for solving this optimization problem. The proposed method employed the global search ability of SCA and the local search ability of PS. The performance of the new hCSC-PS was investigated using a set of benchmark functions, and then the results were compared with those of the standard SCA and some other methods from the literature. In addition, a case study from the literature is considered to evaluate the efficiency of the proposed hCSC-PS for the coordinated design of controllers in the power system. PSSs and additional SVC controllers are being considered to demonstrate the feasibility of the new technique. In order to ensure the robustness and performance of the proposed controller, the objective function is evaluated for various extreme loading conditions and system configurations. The numerical investigations show that the new approach may provide better optimal damping and outperforms previous methods. Nonlinear time-domain simulation shows the superiority of the proposed controller and its ability in providing efficient damping of electromechanical oscillations

A Novel Hybrid Sine Cosine Algorithm and Pattern Search for Optimal Coordination of Power System Damping Controllers

This paper presents an effective hybrid optimization technique based on a chaotic sine cosine algorithm (CSCA) and pattern search (PS) for the coordinated design of power system stabilizers (PSSs) and static VAR compensator (SVC)-based controllers. For this purpose, the design problem is considered as an optimization problem whose decision variables are the controllers’ parameters. Due to the nonlinearities of large, interconnected power systems, methods capable of handling any nonlinearity of power networks are preferable. In this regard, a nonlinear time domain-based objective function was used. Then, the proposed hybrid chaotic sine cosine pattern search (hCSC-PS) algorithm was employed for solving this optimization problem. The proposed method employed the global search ability of SCA and the local search ability of PS. The performance of the new hCSC-PS was investigated using a set of benchmark functions, and then the results were compared with those of the standard SCA and some other methods from the literature. In addition, a case study from the literature is considered to evaluate the efficiency of the proposed hCSC-PS for the coordinated design of controllers in the power system. PSSs and additional SVC controllers are being considered to demonstrate the feasibility of the new technique. In order to ensure the robustness and performance of the proposed controller, the objective function is evaluated for various extreme loading conditions and system configurations. The numerical investigations show that the new approach may provide better optimal damping and outperforms previous methods. Nonlinear time-domain simulation shows the superiority of the proposed controller and its ability in providing efficient damping of electromechanical oscillations

Assessment of rock mass erosion in unlined spillways using developed vulnerability and fragility functions

Hydraulic power can lead to the erosion of rock and cause dams to be at risk of failure. Methods exist to predict the degree of erosion for rock masses in spillways; however, these deterministic approaches are unable to consider the uncertainties of rock mass parameters. We develop a methodology that determines the vulnerability of a rock mass to hydrological erosion, and this approach takes into consideration the uncertainties related to the parameters of the rock mass at the study site. Monte Carlo simulation is used to create a dataset for each class of rock for then developing fragility and vulnerability curves. The effects of each geomechanical parameter on erosion level can be determined by applying this methodology to individual spillway sites. As a result, sensitivity analysis shows that the discontinuity orientation factor is a critical parameter for explaining the erosion of a rock mass; increasing this parameter decreases the vulnerability of the rock mass to erosion. Our approach has an advantage over deterministic methods as the uncertainties of rock mass parameters have been considered. The error associated with the predicted erosion level via our probability-based approach is significantly less than the error obtained via deterministic methods

Global Trend on Machine Learning in Helicobacter within One Decade: A Scientometric Study

Purpose. This study aims to create a science map, provide structural analysis, investigate evolution, and identify new trends in Helicobacter pylori (H. pylori) research articles. Methods. All Helicobacter publications were gathered from the Web of Science (WoS) database from August 2010 to 2021. The data were required for bibliometric analysis. The bibliometric analysis was performed with Bibliometrix R Tool. Bibliometric data were analyzed using the Bibliometrix Biblioshiny R-package software. Results. A total of 17,413 articles were reviewed and analyzed, with descriptive characteristics of the H. pylori literature included. In journals, 21,102 keywords plus and 20,490 author keywords were reported. These articles were also written by 56,106 different authors, with 262 being single-author articles. Most authors’ abstracts, titles, and keywords included “Helicobacter-pylori.” Since 2010, the total number of H. pylori-related publications has been decreasing. Gut, PLOS ONE, and Gastroenterology are the most influential H. pylori journals, according to source impact. China, the United States, and Japan are the countries with most affiliations and subjects. In addition, Seoul National University has published the most articles about H. pylori. According to the cloud word plot, the authors’ most frequently used keywords are gastric cancer (GC), H. pylori, gastritis, eradication, and inflammation. “Helicobacter pylori” and “infection” have the steepest slopes in terms of the upward trend of words used in articles from 2010 to 2021. Subjects such as GC, intestinal metaplasia, epidemiology, peptic ulcer, eradication, and clarithromycin are included in the diagram’s motor theme section, according to strategic diagrams. According to the thematic evolution map, topics such as Helicobacter pylori infection, B-cell lymphoma, CagA, Helicobacter pylori, and infection were largely discussed between 2010 and 2015. From 2016 to 2021, the top topics covered included Helicobacter pylori, H. pylori infection, and infection