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modified water cycle algorithm for optimal direction overcurrent relays coordination

APPLIED SOFT COMPUTING 2019年 74卷 10-25页

作者： Korashy, Ahmed Kamel, Salah Youssef, Abdel-Raheem Jurado, Francisco Aswan Univ Fac Engn Elect Engn Dept Aswan 81542 Egypt Univ Jaen Dept Elect Engn EPS Linares Jaen 23700 Spain Chongqing Univ State Key Lab Power Transmiss Equipment & Syst Se Chongqing Peoples R China South Valley Univ Fac Engn Elect Engn Dept Qena Egypt

The optimization model of Directional Over Current Relays (DOCRs) coordination is considered non-linear optimization problem with a large number of operating constraints. This paper proposes a modified version for water cycle algorithm (WCA), referred to as MWCA to effectively solve the optimal coordination problem of DOCRs. The main goal is to minimize the summation of operating times of all relays when they act as primary protective devices. The operating time of a relay depends on time dial setting and pickup current setting or plug setting, which they are considered as decision variables. In the proposed technique, the search space has been reduced by increasing the C-value of traditional WCA, which effects on the balance between explorative and exploitative phases, gradually during the iterative process in order to find the global minimum. The performance of proposed algorithm is assessed using standard test systems;8-bus, 9-bus, 15-bus, and 30-bus. The obtained results by the proposed algorithm are compared with those obtained by other well-known optimization techniques. In addition, the proposed algorithm has been validated using benchmark DIgSILENT PowerFactory. The results show the effectiveness and superiority of the proposed algorithm to solve DOCRs coordination problem, compared with traditional WCA and other optimization techniques. (C) 2018 Elsevier B.V. All rights reserved.

关键词： Direction overcurrent relays Coordination time interval Optimal coordination modified water cycle algorithm

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Optimal load flow via modified water cycle algorithm

JOURNAL OF THE FACULTY OF ENGINEERING AND ARCHITECTURE OF GA...

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JOURNAL OF THE FACULTY OF ENGINEERING AND ARCHITECTURE OF GAZI UNIVERSITY 2021年第2期36卷 1119-1131页

作者： Akdag, Ozan Yeroglu, Celaleddin Inonu Univ Dept Comp Engn TR-44040 Malatya Turkey

Power systems are getting more complex structure from production to consumption stages. The continuous, reliable, quality and economical delivery of electrical energy to the consumer depends on ensuring uninterrupted and optimized energy flow during the production/transmission/distribution stages. Optimum Power Flow (OPF) problem goals to optimize the parameters such as fuel cost, active/reactive power losses, etc by keeping the generators/ bus voltages, tap setting and active/reactive power within their secure limits. Therefore, it is important to optimize load flow in power systems with an effective method. This paper uses a recent heuristic algorithm, named as the modified water cycle algorithm (MWCA), for the OPF problem. For the purpose demonstrate the effectiveness of the recommended method, it has been analyzed on the IEEE 30 bus power system for varied object functions. The validity and flexibility of this algorithm are discussed by comparison with numerical conclusion of the many newly published heuristic methods in the literature. In this study, the result of the of fuel cost, which is important results of the IEEE 30 bus test system, is computed using MWCA as $798.9021/s. This value is best the fuel cost results of various methods reported in the study. In addition, this method, has applied to a part of the virtual model of 154 kV South Marmara transmission system to show that the active power losses of transmission system could be reduced in a realtime system.

关键词： Optimal power flow modified water cycle algorithm efficiency in power systems optimization

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Digital overcurrent relays coordination in renewable microgrids utilizing several operating characteristics using educational competition optimizer

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Energy Reports 2025年 13卷 6251-6266页

作者： Abdelmonem Draz Mohammed H. Alqahtani Ali S. Aljumah Attia A. El-Fergany Abdullah M. Shaheen Electrical Power and Machines Department Faculty of Engineering Zagazig University Zagazig 44519 Egypt Department of Electrical Engineering College of Engineering Prince Sattam bin Abdulaziz University Al-Kharj Saudi Arabia Department of Electrical Engineering Faculty of Engineering Suez University Suez 43221 Egypt

Renewable microgrids (MGs), characterized by bi-directional power flow, require enhanced attention in designing protection schemes, particularly in the coordination of overcurrent relays (OCRs). Accordingly, a fresh metaheuristic algorithm named educational competition optimizer (ECO) is proposed in this study to solve the OCRs coordination problem with various operation scenarios among digital relays. Additionally, two fitness functions are incorporated into the optimization mechanism considering several relay operating characteristics (CCs) along with continuous current pickup and time dial. In this context, the programmed simulation model is validated rigorously against two other metaheuristic optimizers: artificial bee colony (ABC) and dung beetle optimizer (DBO). Initially, the effectiveness of the ECO is assessed on the IEEE 15-bus benchmark network prior to validating the proposed methodology in the IEC benchmark MG. Considering all operational scenarios, ECO attempts the best shot in minimizing the total operating time (TOT) of OCRs in both investigated networks. For instance, the ECO attains TOT of 3.2704 s and 6.3968 s with various operating CCs for 15-bus and IEC MG respectively. Undoubtedly, ECO earns this rival for all scenarios compared to ABC and DBO besides additional 16 metaheuristic literature algorithms. It is worth highlighting that when optimizing the OCR’s curve among 17 CCs, TOT is enhanced by 64.9 % and 43 % compared to fixed standard curve for 15-bus and MG respectively. Eventually, ECO consistently proves its superiority over other published optimizers in addressing the complex problem of OCR’s coordination especially in renewable MGs.

关键词： ANSI American National Standards Institute DG Distributed Generation RESs Renewable Energy Sources TOT Total Operating Time ORC Optimal Relay Coordination DOCRs Directional Overcurrent Relays OC Overcurrent FA Firefly algorithm AI Artificial Intelligence GA Genetic algorithm IEEE Institute of Electric and Electronic Engineers FF Fitness Function PSO Particle Swarm Optimizer NSGA Non-dominated Sorting Genetic algorithm IEC International Electrotechnical Commission MG Microgrid HAS Harmony Search algorithm SQP Sequential Quadratic Programming HHO Harris Hawks Optimizer DE Differential Evolution GWO Grey Wolf Optimizer ABC Artificial Bee Colony GSA Gravitational Search algorithm ECO Educational Competition Optimizer DBO Dung Beetle Optimizer P/B Primary/Backup pairs CCs Characteristics WTGs Wind Turbine Generators EGWO Enhanced Grey Wolf Optimizer MEFO modified Electromagnetic Field Optimizer SMA Slime Mould algorithm MFA modified Firefly algorithm NI Normal Inverse SI Standard Inverse VI Very Inverse EI Extremely Inverse MI Moderately Inverse LI Long Inverse DI Definite Inverse OLF Over Loading Factor WCA water cycle algorithm MWCA modified water cycle algorithm ETAP Electrical Transient Analyzer Program DIgSILENT PF DIgital SImuLation of Electrical NeTworks Power Factory Optimal coordination Overcurrent relays Metaheuristic optimizers Distributed generation Microgrids protection

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A combination forecasting approach applied in multistep wind speed forecasting based on a data processing strategy and an optimized artificial intelligence algorithm

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APPLIED ENERGY 2018年 230卷 1108-1125页

作者： Yang, Zhongshan Wang, Jian Dongbei Univ Finance & Econ Sch Stat Dalian 116025 Peoples R China

Owing to the complexity and uncertainty of wind speed, accurate wind speed prediction has become a highly anticipated and challenging problem in recent years. Researchers have conducted numerous studies on wind speed prediction theory and practice;however, research on multi-step wind speed prediction remains scarce, which hinders further development in this area. To improve upon the accuracy and stability of multi-step wind speed prediction, this paper proposes a combination model based on a data preprocessing strategy, an improved optimization model, a no negative constraint theory, and several single prediction models. To improve upon forecasting performance, an improved water cycle algorithm based on a quasi-Newton algorithm is proposed to optimize the weight coefficients of the single models. In the empirical research, 10-min and 30-min wind speed data from Shandong Province in China, collected for case studies, were used to assess the comprehensive performance of the proposed combination model. Finally, we used 10-fold cross-validation and multiple error criteria to evaluate the comprehensive performance of the proposed combination model. The simulation results indicate that (a) the quasi-Newton algorithm can effectively increase the diversity of the water cycle algorithm particles, resulting in improved water cycle algorithm optimization performance;(b) the combination model exhibits superior predictive performance to a single model by taking advantage of each single model;and (c) the proposed combination model can effectively improve multi-step wind speed prediction results.

关键词： Wind speed forecasting Complementary ensemble empirical model modified water cycle algorithm Broyden family Combination model

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