8 research outputs found
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State-of-the-art of the most commonly adopted wave energy conversion systems
Copyright © 2023 The Authors. The vast diversity of wave energy conversion systems (WECSs) in the literature makes selecting the suitable WECS for wave energy harvest a stubborn process. This work summarizes six of the most widely adopted WECSs used heavily in previous research assessments and practical projects. This includes the Archimedes Wave Swing (AWS), the Wave Dragon (WD), Pelamis Wave Power (PWP), Aquabouy (AB), the Oyster, and the Oscillating Water Column (OWC). The work includes the mathematical modeling of these WECSs and the different projects and prototypes that involve these WECSs. Moreover, the latest research development in each of these WECSs is presented. Also, the wave energy potential in the world is discussed. Besides, the wave energy potential in Egypt, including that of the Mediterranean and the Red Sea, is discussed in detail. Furthermore, the steps required to perform a future feasibility study in Egypt and suggestions for the enhancement of an older study are provided. Finally, some suggestions and required equations are presented to explore the site power density and the most suitable WECS to be utilized in Egypt
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Load frequency control of interconnected power systems using hybrid algorithm based particle swarm and grey wolf optimizers
This study introduces a new hybrid optimization technique into the research field of load frequency control. The new technique is a hybrid technique that combines two metaheuristic-based algorithms: Particle Swarm Optimizer (PSO) and Grey Wolf Optimization (GWO). This new technique facilitates the selection of the best gain values of the controller used in the power system under study. The controller utilized in this study is the classical proportional-integral-derivative (PID) controller. This classical controller is selected in this study to make a reliable comparison with other applied techniques. The study's main goal is to retain the system frequency and tie-line power within permissible limits after applying a load disturbance to one of the system areas. The system under test is built as a three area network with thermal power generation units. The hybrid PSO-GWO (HPSOGWO) algorithm is applied to the system under test. The results obtained are verified by comparing them with other techniques, including the bacterial foraging technique (BFOA) and harmony search technique (HS). The results show that the HPSOGWO algorithm can preserve the frequency and tie-line power within the permissible bounds faster and with better transient specifications than that obtained using the other algorithms under comparison. The three area system is simulated in MATLAB environment for an easier interface
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Towards accurate calculation of supercapacitor electrical variables in constant power applications using new analytical closed-form expressions
Corrigendum (available online 8 March 2022, version of record 24 March 2022 at DOI URL: https://doi.org/10.1016/j.est.2022.104367)
On November the 20th 2020 the paper titled âLambert W function based closed-form expressions of supercapacitor electrical variables in constant power applicationsâ [which we now refer to as âPaper Aâ] was published in the journal âEnergyâ.
On August the 2nd 2021, our paper âTowards accurate calculation of supercapacitor electrical variables inconstant power applications using new analytical closed-form expressionsâ was published in the Journal of Energy Storage, [which we now refer to as Paper B].
Although our paper does have a novelty in applying Special Trans Function Theory to calculate the Lambert W function, paper A owns the originality of introducing the âthorough mathematical analysis which, by using the Lambert W function, accomplishes the explicit calculation of all the electrical variables involved in the charge/discharge processes of supercapacitors operated at constant power as a function of time.â
So, we acknowledge the priority of Paper A and apologize to the authors J.F. Pedrayes, M.G. Melero, J.M. Cano, J.G. Norniella, S.B. Duque, C.H. Rojas, and G. A. Orcajo for any inconvenience
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Optimal PID controllers for AVR system considering limited excitation voltage limitations using hybrid equilibrium optimizer
Automatic voltage regulator (AVR) represents the basic voltage regulator loop in power systems. The central part of this loop is the regulator, which has parameters that define the speed of the voltage regulation, quality of responses, and system stability. Furthermore, it has an impact on the excitation voltage change and value, especially during transients. In this paper, unlike literature approaches, the experimental verifications of the impact of regulator parameters on the excitation voltage and current value are presented. A novel hybrid metaheuristic algorithm for obtaining regulator parameters determination of the AVR system, and a novel regulator design taking into account excitation voltage limitation are presented. The proposed algorithm combines the properties and characteristics of equilibrium optimizer and evaporation rate water cycle algorithms. The proposed algorithm is effective, fast, and accurate. Both experimental and simulation results show that the limitation of the excitation voltage increases the settling time of the generator voltage during reference change. Additionally, the simulation results show that the optimal values of PID parameters are smaller for limited excitation voltage values
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Artificial neural network-based nonlinear black-box modeling of synchronous generators
Data availability: The complete experimental measurements presented in Figs. 6 and 7, along with some of the used Matlab codes and Simulink models, are located on the following link: https://drive.google.com/file/d/1OlNfo56QIgJUaKioGhenOJ28WNt88y3/view?usp=sharing. It can be downloaded with the permission of the authors
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Optimal power flow of modern power systems comprising mixed renewable energy sources using improved chaotic hunger games search optimization algorithm
Copyright: © 2021 by the authors. This article introduces an application of the recently developed hunger games search (HGS) optimization algorithm. The HGS is combined with chaotic maps to propose a new Chaotic Hunger Games search (CHGS). It is applied to solve the optimal power flow (OPF) problem. The OPF is solved to minimize the generation costs while satisfying the systemsâ constraints. Moreover, the article presents optimal siting for mixed renewable energy sources, photovoltaics, and wind farms. Furthermore, the effect of adding renewable energy sources on the overall generation costs value is investigated. The exploration field of the optimization problem is the active output power of each generator in each studied system. The CHGS also obtains the best candidate design variables, which corresponds to the minimum possible cost function value. The robustness of the introduced CHGS algorithm is verified by performing the simulation 20 independent times for two standard IEEE systemsâIEEE 57-bus and 118-bus systems. The results obtained are presented and analyzed. The CHGS-based OPF was found to be competitive and superior to other optimization algorithms applied to solve the same optimization problem in the literature. The contribution of this article is to test the improvement done to the proposed method when applied to the OPF problem, as well as the study of the addition of renewable energy sources on the introduced objective function