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Achieving Optimal PV Allocation in Distribution Networks Using a Modified reptile search algorithm

IEEE ACCESS 2024年 12卷 42651-42666页

作者： Kamel, Salah Abdel-Mawgoud, Hussein Hashim, Fatma A. Bouaouda, Anas Dominguez-Garcia, Jose Luis Aswan Univ Fac Engn Dept Elect Engn Aswan 81542 Egypt Helwan Univ Fac Engn Cairo 11795 Egypt Hassan II Univ Casablanca Fac Sci & Technol Casablanca 20650 Morocco IREC Catalonia Inst Energy Res Barcelona 08930 Spain

As a result of advancements in technology and population growth, there has been a significant rise in global electrical demand. Consequently, the integration of renewable sources such as photovoltaic (PV) systems into distribution systems has gained popularity as an effective solution to meet the increasing load requirements. This research paper introduces an optimized approach for allocating PV systems at various penetration levels, utilizing a powerful optimization algorithm known as the modified reptile search algorithm (MRSA). MRSA is an enhanced version of the reptile search algorithm (RSA) that addresses issues related to local optima stagnation and premature convergence by incorporating the disperse ambush strategy and proportional selection method. To assess the efficacy of the proposed optimizer, a comprehensive set of comparative experiments was conducted using the CEC'2020 test suite. The experimental results consistently demonstrate that the proposed technique outperforms alternative methods in terms of both convergence speed and accuracy. Additionally, the MRSA algorithm was employed to determine the optimal allocation of PV systems, with the total power loss serving as a single objective function while considering equality and inequality constraints. The IEEE 33-bus RDS was employed as the test system. The obtained results provide evidence that incorporating multiple PV systems yields superior outcomes compared to a single PV system at various penetration levels within the RDS. Furthermore, integrating PV systems at higher penetration levels yields better results than incorporating them at lower penetration levels.

关键词： Distribution network renewable energy PV penetration metaheuristic optimization reptile search algorithm

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Modified reptile search algorithm with multi-hunting coordination strategy for global optimization problems

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MATHEMATICAL BIOSCIENCES AND ENGINEERING 2023年第6期20卷 10090-10134页

作者： Wu, Di Wen, Changsheng Rao, Honghua Jia, Heming Liu, Qingxin Abualigah, Laith Sanming Univ Sch Educ & Mus Sanming 365004 Peoples R China Sanming Univ Sch Informat Engn Sanming 365004 Peoples R China Hainan Univ Sch Comp Sci & Technol Haikou 570228 Peoples R China Al Ahliyya Amman Univ Hourani Ctr Appl Sci Res Amman 19328 Jordan

The reptile search algorithm (RSA) is a bionic algorithm proposed by Abualigah. et al. in 2020. RSA simulates the whole process of crocodiles encircling and catching prey. Specifically, the encircling stage includes high walking and belly walking, and the hunting stage includes hunting coordination and cooperation. However, in the middle and later stages of the iteration, most search agents will move towards the optimal solution. However, if the optimal solution falls into local optimum, the population will fall into stagnation. Therefore, RSA cannot converge when solving complex problems. To enable RSA to solve more problems, this paper proposes a multi-hunting coordination strategy by combining Lagrange interpolation and teaching-learning-based optimization (TLBO) algorithm's student stage. Multi-hunting cooperation strategy will make multiple search agents coordinate with each other. Compared with the hunting cooperation strategy in the original RSA, the multi-hunting cooperation strategy has been greatly improved RSA's global capability. Moreover, considering RSA's weak ability to jump out of the local optimum in the middle and later stages, this paper adds the Lens pposition-based learning (LOBL) and restart strategy. Based on the above strategy, a modified reptile search algorithm with a multi-hunting coordination strategy (MRSA) is proposed. To verify the above strategies' effectiveness for RSA, 23 benchmark and CEC2020 functions were used to test MRSA's performance. In addition, MRSA's solutions to six engineering problems reflected MRSA's engineering applicability. It can be seen from the experiment that MRSA has better performance in solving test functions and engineering problems.

关键词： reptile search algorithm Lagrange interpolation teaching-learning-based optimization benchmark function test lens opposition-based learning restart strategy

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An Improved reptile search algorithm with Ghost Opposition-based Learning for Global Optimization Problems

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JOURNAL OF COMPUTATIONAL DESIGN AND ENGINEERING 2023年第4期10卷 1390-1422页

作者： Jia, Heming Lu, Chenghao Wu, Di Wen, Changsheng Rao, Honghua Abualigah, Laith Sanming Univ Sch Informat Engn Sanming 365004 Peoples R China Sanming Univ Sch Educ & Music Sanming 365004 Peoples R China Al Al Bayt Univ Prince Hussein Bin Abdullah Coll Informat Technol Mafraq 130040 Jordan Al Ahliyya Amman Univ Hourani Ctr Appl Sci Res Amman 19328 Jordan Middle East Univ Fac Informat Technol Amman 11831 Jordan Appl Sci Private Univ Appl Sci Res Ctr Amman 11931 Jordan Univ Sains Malaysia Sch Comp Sci George Town 11800 Malaysia

In 2021, a meta-heuristic algorithm, reptile search algorithm (RSA), was proposed. RSA mainly simulates the cooperative predatory behavior of crocodiles. Although RSA has a fast convergence speed, due to the influence of the crocodile predation mechanism, if the algorithm falls into the local optimum in the early stage, RSA will probably be unable to jump out of the local optimum, resulting in a poor comprehensive performance. Because of the shortcomings of RSA, introducing the local escape operator can effectively improve crocodiles' ability to explore space and generate new crocodiles to replace poor crocodiles. Benefiting from adding a restart strategy, when the optimal solution of RSA is no longer updated, the algorithm's ability to jump out of the local optimum is effectively improved by randomly initializing the crocodile. Then joining Ghost opposition-based learning to balance the IRSA's exploitation and exploration, the Improved RSA with Ghost Opposition-based Learning for the Global Optimization Problem (IRSA) is proposed. To verify the performance of IRSA, we used nine famous optimization algorithms to compare with IRSA in 23 standard benchmark functions and CEC2020 test functions. The experiments show that IRSA has good optimization performance and robustness, and can effectively solve six classical engineering problems, thus proving its effectiveness in solving practical problems.

关键词： reptile search algorithm local escaping operator restart strategy ghost opposition-based learning benchmark function test engineering problem

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Conglomeration of reptile search algorithm and Differential Evolution algorithm for Optimal Designing of FIR Filter

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CIRCUITS SYSTEMS AND SIGNAL PROCESSING 2023年第5期42卷 2986-3007页

作者： Chauhan, Sumika Vashishtha, Govind Kumar, Anil Abualigah, Laith Natl Inst Technol Delhi Dept Comp Sci New Delhi 110036 India St Longowal Inst Engn & Technol Dept Mech Engn Precis Metrol Lab Longowal 148106 India Wenzhou Univ Coll Mech & Elect Engn Wenzhou 325035 Peoples R China Al Ahliyya Amman Univ Hourani Ctr Appl Sci Res Amman 19328 Jordan Middle East Univ Fac Informat Technol Amman 11831 Jordan Appl Sci Private Univ Fac Informat Technol Amman 11931 Jordan Univ Sains Malaysia Sch Comp Sci George Town 11800 Pulau Pinang Malaysia

To solve the problems of sluggish convergence at local minima, a combination of reptile search algorithms with differential evolution (CRSADE) has been developed. The conglomerated algorithm also includes a lens opposition-based learning method, which boosts population diversity and speeds up convergence. The differential evolution algorithm used in the developed CRSADE improves the exploration of the reptile search algorithm through its high ability to locate feasible regions with the best solution. This accelerates convergence by enhancing the end product of the algorithm. The proposed CRSADE helps in designing finite impulse response filters in which absolute error difference is utilized as a fitness function which is minimized by the proposed CRSADE to obtain optimal filter coefficients. To demonstrate its superiority and consistency, a comparison has been made between the developed method and other existing optimization algorithms. The developed filter satisfies the intended objective effectively with lower ripples in the pass band and higher attenuation in the stop band.

关键词： Filter design Differential evolution reptile search algorithm Opposition based learning concept

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A modified reptile search algorithm for parametric estimation of fractional order model of lithium battery

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OPTIMAL CONTROL APPLICATIONS & METHODS 2023年第6期44卷 3204-3218页

作者： Ding, Jie Huang, Shimeng Hao, Yuefei Xiao, Min Nanjing Univ Posts & Telecommun Sch Automat & Artificial Intelligence Nanjing Peoples R China Nanjing Univ Posts & Telecommun Sch Automat & Artificial Intelligence Nanjing 210023 Peoples R China

In this paper, a Levy reptile search algorithm (LRSA) is proposed to improve the global search capability and convergence speed of reptile search algorithm which has advantages in solving single-modal, multi-modal and composite problems. Firstly, circle chaotic mapping is introduced to make the initial distribution of population more uniform and diversified. Secondly, Levy flight strategy is employed in the global search, which can improve the accuracy and convergence speed. In order to test and verify the optimization performance of the LRSA, 12 benchmark functions are tested and compared with four other intelligent optimization algorithms. It can be seen that LRSA is effective and advantageous in average convergence speed. In addition, the proposed LRSA is applied to a fractional order model identification of lithium battery with a very small error (less than 2%). The experimental results show that the LRSA can effectively estimate the parameters of the fractional order model and aid to state of charge and state of health estimation.

关键词： circle chaotic map fractional order modeling levy flight reptile search algorithm

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Multi-objective scheduling of cloud tasks with positional information-enhanced reptile search algorithm

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INTERNATIONAL JOURNAL OF INTERACTIVE DESIGN AND MANUFACTURING - IJIDEM 2024年第7期18卷 4715-4728页

作者： Ding, Huaibao Zhang, Mengzi Zhou, Fei Ding, Xiaomei Chu, Shiwei Anhui Wenda Univ Informat Engn Sch Comp Engn Hefei 231201 Peoples R China Anhui Univ Sch Elect Informat Engn Hefei 231201 Peoples R China

With the proliferation of cloud services driven by accessibility, enhanced performance, and cost-effectiveness, cloud service providers continuously seek methods to expedite job completion, thereby augmenting profits and diminishing energy consumption expenditures. In pursuit of this objective, numerous scheduling algorithms have been devised. Nevertheless, many of these techniques address only one specific objective within the scheduling process. This paper introduces a novel approach founded on the reptile search algorithm (RSA). The RSA, albeit effective, predominantly navigates by tracing the path of optimal individuals, often overlooking valuable insights from others. Modified RSA (MRSA) is proposed to enhance RSA by incorporating a distribution estimation methodology to harness the maximum potential of the positional knowledge embedded within the majority population. MRSA is simulated using the Cloudsim tool and evaluated under diverse test conditions. The efficacy of MRSA is assessed by employing various parameters and comparing them with existing algorithms. The findings indicate that MRSA is superior to other algorithms regarding resource utilization, energy consumption, and execution cost.

关键词： Cloud computing Resource utilization Scheduling reptile search algorithm

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Enhanced reptile search algorithm with Levy flight for vehicle cruise control system design

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EVOLUTIONARY INTELLIGENCE 2023年第4期16卷 1339-1351页

作者： Ekinci, Serdar Izci, Davut Batman Univ Dept Comp Engn TR-72100 Batman Turkey Batman Univ Dept Elect & Automat TR-72060 Batman Turkey

A vehicle cruise control (VCC) system is one of the real-world engineering optimization problems gaining a considerable attention because of the concerns related to safety and cost-effectiveness. A VCC system requires an efficient control method for appropriately functioning. This paper, therefore, proposes a proportional-integral-derivative (PID) controller as a simple yet effective structure for VCC system control. To tune the PID controller for efficient operation, a novel metaheuristic algorithm is also developed in this paper which improves the performance of the reptile search algorithm via the integration of Levy flight concept. This paper then proposes a new objective function by modifying the performance index called integral of time multiplied squared error in order to increase the performance of the proposed algorithm to effectively adjust the PID parameters adopted in a VCC system. The performance of the proposed method is demonstrated comparatively using several assessments. Lastly, comparisons with the other available methods in the literature is performed in order to evaluate the performance of the proposed method from a wider perspective. In this way, the proposed method is shown to be an efficient approach to control a VCC system.

关键词： reptile search algorithm Levy flight Vehicle cruise control Metaheuristics PID tuning

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Enhancing reptile search algorithm with shifted distribution estimation strategy for coverage optimization in wireless sensor networks

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HELIYON 2024年第15期10卷 e34455页

作者： Ma, Na Wang, Shouxin Hao, Shuailing Res Inst China Telecom Beijing 102209 Peoples R China China Satellite Commun Co Ltd Beijing Peoples R China

The rapid development of the Internet of Things (IoT) has extensively promoted the development of Wireless Sensor Networks (WSNs), an essential technology for series displaying perception and data collected from the physical world. In densely distributed areas, sensor nodes are unevenly distributed, which leads to the network coverage build-up and the consequent efficiency and effectiveness of WSNs. To address this issue, this paper proposes a new method for WSN coverage optimization based on the reptile search algorithm (RSA). In the past, the reptile search algorithm has been used to solve optimization problems, which means it can improve different processes. However, the RSA needs to track the trajectory of optimal individuals in each iteration, which will ignore non-optimal individuals' bioeconomic characteristics. Therefore, the paper introduces a distribution estimation strategy into the RSA framework, which can fully mine all the positional information hidden in the entire population. We selected several functions as optimization test benchmark functions to evaluate the feasibility of the proposed method. This paper compares the proposed improved RSA with the standard RSA and some traditional optimization algorithms. The result has been calculated through a series of experiments on network coverage optimization, and the change of parameters also determines the effect of the RSA in the optimization of network coverage. The simulated results of the three similar network coverage optimization experiments show that the improved RSA can be used efficiently within different scenarios.

关键词： Wireless sensor network Internet of things Coverage Optimization reptile search algorithm

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Determination of AVR System PID Controller Parameters Using Improved Variants of reptile search algorithm and a Novel Objective Function

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Energy Engineering 2023年第7期120卷 1515-1540页

作者： Baran Hekimoglu Department of Electrical&Electronics Engineering Faculty of Engineering and ArchitectureBatman UniversityBatman72100Turkey

Two novel improved variants of reptile search algorithm(RSA),RSA with opposition-based learning(ORSA)and hybrid ORSA with pattern search(ORSAPS),are proposed to determine the proportional,integral,and derivative(PID)controller parameters of an automatic voltage regulator(AVR)system using a novel objective function with augmented *** the proposed algorithms,the opposition-based learning technique improves the global search abilities of the original RSA algorithm,while the hybridization with the pattern search(PS)algorithm improves the local search *** algorithms are compared with the original RSA algorithm and have shown to be highly effective algorithms for tuning the PID controller parameters of an AVR system by getting superior *** analyses such as transient,stability,robustness,disturbance rejection,and trajectory tracking are conducted to test the performance of the proposed algorithms,which have validated the good promise of the proposed methods for controller *** performances of the proposed design approaches are also compared with the previously reported PID controller parameter tuning approaches to assess their *** is shown that both proposed approaches obtain excellent and robust results among all compared *** is,with the adjustment of the weight factorα,which is introduced by the proposed objective function,for a system with high bandwitdh(α=1),the proposed ORSAPS-PID system has 2.08%more bandwidth than the proposed ORSA-PID system and 5.1%faster than the fastest algorithm from the *** the other hand,for a system where high phase and gain margins are desired(α=10),the proposed ORSA-PID system has 0.53%more phase margin and 2.18%more gain margin than the proposed ORSAPS-PID system and has 0.71%more phase margin and 2.25%more gain margin than the best performing algorithm from the literature.

关键词： reptile search algorithm pattern search multidirectional search metaheuristics automatic voltage regulator optimal PID controller

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An Improved reptile search algorithm Based on Cauchy Mutation for Intrusion Detection

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Computer Systems Science & Engineering 2023年第8期46卷 2509-2525页

作者： Salahahaldeen Duraibi Department of Computer and Network Engineering Jazan UniversityJazan 82822-6649Saudi Arabia

With the growth of the discipline of digital communication,the topic has acquiredmore attention in the *** Intrusion Detection(ID)system monitors network traffic to detect malicious *** paper introduces a novel Feature Selection(FS)approach for *** search algorithm(RSA)—is a new optimization algorithm;in this method,each agent searches a new region according to the position of the host,which makes the algorithm suffers from getting stuck in local optima and a slow convergence *** overcome these problems,this study introduces an improved RSA approach by integrating Cauchy Mutation(CM)into the RSA’s ***,the CM can effectively expand search space and enhance the performance of the *** developed RSA-CM is assessed on five publicly available ID datasets:KDD-CUP99,NSL-KDD,UNSW-NB15,CIC-IDS2017,and CIC-IDS2018 and two engineering *** RSA-CM is compared with the original RSA,and three other state-of-the-art FS methods,namely particle swarm optimization,grey wolf optimization,and multi-verse optimizer,and quantitatively is evaluated using fitness value,the number of selected optimum features,accuracy,precision,recall,and F1-score *** results reveal that the developed RSA-CMgot better results than the other competitive methods applied for FS on the ID datasets and the examined engineering ***,the Friedman test results confirm that RSA-CMhas a significant superiority compared to other methods as an FS method for ID.

关键词： Feature selection intrusion detection metaheuristic algorithms reptile search algorithm cauchy mutation

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