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improved jaya algorithm-based FOPID/PID for AVR system

COMPEL-THE INTERNATIONAL JOURNAL FOR COMPUTATION AND MATHEMATICS IN ELECTRICAL AND ELECTRONIC ENGINEERING 2020年第4期39卷 775-790页

作者： Bhookya, Jailsingh Jatoth, Ravi Kumar Natl Inst Technol Warangal Dept Elect & Commun Engn Warangal Andhra Pradesh India

Purpose This paper aims to get the optimal controller parameters of fractional order proportional integral derivative (FOPID)/proportional integral derivative (PID) i.e. K-p, K-i, K-d, lambda and mu for designing controller in automatic voltage regulator (AVR) system. Design/methodology/approach A novel method is proposed to get the optimal controller parameters for designing controller in AVR system using improved jaya algorithm (IJA). The time domain objective and regular integral error objectives are used to design the controller to estimate the performance of the AVR system based on optimal tuning FOPID/PID controller. Findings The proposed method captures time domain objective of the FOPID/PID controller design and demonstrates effective transient response and better control action. The efficient tuning of FOPID controller results in high superiority of control efforts. Practical implications The simulations of IJA-based FOPID/PID controller design method are performed in MatLab tool and compared with several methods in the recent state of the art and the same are observed to be robust for the AVR system. Originality/value The developed optimal FOPID/PID controller tuning using IJA optimization method is totally a new approach for the AVR system in the literature.

关键词： Fractional order PID Controller design improved jaya algorithm AVR system model Optimization technique Tuning of FOPID PID

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Structural damage identification using improved jaya algorithm based on sparse regularization and Bayesian inference

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MECHANICAL SYSTEMS AND SIGNAL PROCESSING 2019年 132卷 211-231页

作者： Ding, Zhenghao Li, Jun Hao, Hong Curtin Univ Ctr Infrastruct Monitoring & Protect Sch Civil & Mech Engn Kent St Bentley WA 6102 Australia

Structural damage identification can be considered as an optimization problem, by defining an appropriate objective function relevant to structural parameters to be identified with optimization techniques. This paper proposes a new heuristic algorithm, named improved jaya (I-jaya) algorithm, for structural damage identification with the modified objective function based on sparse regularization and Bayesian inference. To improve the global optimization capacity and robustness of the original jaya algorithm, a clustering strategy is employed to replace solutions with low-quality objective values and a new updated equation is used for the best-so-far solution. The objective function that is sensitive and robust for effective and reliable damage identification is developed through sparse regularization and Bayesian inference and used for optimization analysis with the proposed I-jaya algorithm. Benchmark tests are conducted to verify the improvement in the developed algorithm. Numerical studies on a truss structure and experimental validations on an experimental reinforced concrete bridge model are performed to verify the developed approach. A limited quantity of modal data, which is distinctively less than the number of unknown system parameters, are used for structural damage identification. Significant measurement noise effect and modelling errors are considered. Damage identification results demonstrate that the proposed method based on the I-jaya algorithm and the modified objective function based on sparse regularization and Bayesian inference can provide accurate and reliable damage identification, indicating the proposed method is a promising approach for structural damage detection using data with significant uncertainties and limited measurement information. (C) 2019 Elsevier Ltd. All rights reserved.

关键词： improved jaya algorithm Bayesian interference Sparse regularization Structural damage identification Uncertainty Measurement noise

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Practical multi-area bi-objective environmental economic dispatch equipped with a hybrid gradient search method and improved jaya algorithm

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IET GENERATION TRANSMISSION & DISTRIBUTION 2016年第14期10卷 3580-3596页

作者： Azizipanah-Abarghooee, Rasoul Dehghanian, Payman Terzija, Vladimir Univ Manchester Dept Elect & Elect Engn Manchester M13 9PL Lancs England Texas A&M Univ Dept Elect & Comp Engn College Stn TX 77843 USA

Generation dispatch decision making integrated into a centralised wholesale electricity market has been always a challenging concern for transmission system operators. The reason lies mainly in the complex and highly-interconnected structure of the grid, escalated demand, and the crisis of the amount and price of energy. For the dispatch solutions to be highly reliable with an acceptable level of accuracy, several factors need to be taken into account, among which one can mention the valve-point effect, multiple fuel options, disjoint prohibited zones, up/down ramp rate requirements of units, as well as the spinning reserve constraints which, in turn, intensify the non-smoothness, non-convexity, non-linearity, and dynamic restriction of such combinatorial problems. This study proposes a new optimization toolset for the bi-objective multi-area economic dispatch problem to determine the transmission power flow and power output of units while satisfying system demand and security constraints at each area. The proposed architecture builds on an improved gradient-based jaya algorithm to generate a feasible set of Pareto-optimal solutions corresponding to the operation cost and emission calculated through a new robust bi-objective gradient-based method. The projected algorithm is proved to be capable of finding the robust global or near-global Pareto solutions fast and accurate.

关键词： gradient methods search problems environmental economics load dispatching power transmission economics load flow power system security power generation dispatch power generation economics Pareto optimisation practical multiarea biobjective environmental economic dispatch hybrid gradient search method improved jaya algorithm generation dispatch decision making centralised wholesale electricity market transmission system highly-interconnected structure power grid energy pricing valve-point effect multiple fuel option disjoint prohibited zone up-down ramp rate requirement spinning reserve constraint combinatorial hard problem optimisation toolset transmission interface power flow security constraint fuel combustion emission calculation near-global Pareto-optimal solution

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An improved jaya algorithm for solving the flexible job shop scheduling problem with transportation and setup times

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KNOWLEDGE-BASED SYSTEMS 2020年 200卷 106032-106032页

作者： Li, Jun-qing Deng, Jia-wen Li, Cheng-you Han, Yu-yan Tian, Jie Zhang, Biao Wang, Cun-gang Liaocheng Univ Coll Comp Sci Liaocheng 252059 Shandong Peoples R China Shandong Normal Univ Sch Informat Sci & Engn Jinan 25014 Peoples R China

Flexible job shop scheduling has been widely researched due to its application in many types of fields. However, constraints including setup time and transportation time should be considered simultaneously among the realistic requirements. Moreover, the energy consumptions during the machine processing and staying at the idle time should also be taken into account for green production. To address this issue, first, we modeled the problem by utilizing an integer programming method, wherein the energy consumption and makespan objectives are optimized simultaneously. Afterward, an improved jaya (Ijaya) algorithm was proposed to solve the problem. In the proposed algorithm, each solution is represented by a two-dimensional vector. Consequently, several problem-specific local search operators are developed to perform exploitation tasks. To enhance the exploration ability, a SA-based heuristic is embedded in the algorithm. Meanwhile, to verify the performance of the proposed Ijaya algorithm, 30 instances with different scales were generated and used for simulation tests. Six efficient algorithms were selected for detailed comparisons. The simulation results confirmed that the proposed algorithm can solve the considered problem with high efficiency. (C) 2020 Elsevier B.V. All rights reserved.

关键词： Flexible job shop improved jaya algorithm Energy consumption Transportation time Setup time

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An improved jaya algorithm-Based Strategy for T-Way Test Suite Generation 4th

An Improved Jaya Algorithm-Based Strategy for T-Way Test Sui...

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4th International Conference of Reliable Information and Communication Technology (IRICT)

作者： Nasser, Abdullah B. Hujainah, Fadhl Al-Sewari, AbdulRahman A. Zamli, Kamal Z. Univ Malaysia Pahang Fac Comp Syst & Software Engn Kuantan 26300 Pahang Malaysia

ISBN: (纸本)9783030335823;9783030335816

In the field of software testing, several meta-heuristics algorithms have been successfully used for finding an optimized t-way test suite (where t refers to covering level). T-way testing strategies adopt the meta-heuristic algorithms to generate the smallest/optimal test suite. However, the existing tway strategies' results show that no single strategy appears to be superior in all problems. The aim of this paper to propose a new variant of jaya algorithm for generating t-way test suite called improved jaya algorithm (IJA). In fact, the performance of meta-heuristic algorithms highly depends on the intensification and diversification capabilities. IJA enhances the intensification and diversification capabilities by introducing new operators search such levy flight and mutation operator in jaya algorithm. Experimental results show that the IJA variant improves the results of original jaya algorithm, also overcomes the problems of slow convergence of jaya algorithm.

关键词： T-way testing Meta-heuristics jaya algorithm improved jaya algorithm

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A novel grid-oriented dynamic weight parameter based improved variant of jaya algorithm

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ADVANCES IN ENGINEERING SOFTWARE 2020年 150卷 102904-102904页

作者： Leghari, Zohaib Hussain Hassan, Mohammad Yusri Said, Dalila Mat Jumani, Touqeer Ahmed Memon, Zeeshan Anjum Univ Teknol Malaysia UTM Ctr Elect Energy Syst CEES Inst Future Energy IFE Johor Baharu 81310 Johor Malaysia Univ Teknol Malaysia UTM Fac Engn Sch Elect Engn SKE Johor Baharu 81310 Johor Malaysia Mehran Univ Engn & Technol MUET Dept Elect Engn Jamshoro 76062 Sindh Pakistan Mehran Univ Engn & Technol MUET Dept Elect Engn SZAB Campus Khairpur Mirs 66020 Sindh Pakistan

jaya algorithm (JA) is a single-step metaheuristic optimization technique that is free from algorithm-specific parameters. Regardless of its simplicity, JA proved its effective performance against the variety of optimization algorithms (Du et al., 2018). However, like other swarm-based optimization techniques, the JA also suffers from the inadequacies of slow or premature convergence (Farah and Belazi, 2018). In this study, an improved variant of JA (Ijaya) is proposed whose functioning depends on the randomly initiated bounds based grid-oriented weight parameters. Initially, aiming to balance the global exploration and local exploitation capabilities of JA, a dynamic weight parameter is introduced as a varying coefficient for the entire solution updating expression of JA. Then, to maintain the population diversity and to mitigate the complexity of parameter tuning, the introduced weight parameter is dealt with the randomly selected parameter bounds based grid-search mechanism. The proposed Ijaya algorithm is benchmarked on well-known 15 unconstrained mathematical test functions, and its performance is analyzed against the standard JA, one modified variant of JA, some well-known state-ofthe-art, and few newly introduced optimization algorithms. Furthermore, the non-parametric Friedman and Quade rank tests are also conducted which confirmed the superiority of proposed Ijaya both in convergence rate and solution quality. The paper also presents the results obtained by Ijaya in two classical structural design problems (a cantilever beam and a 3-bar truss) and a real-world electrical power engineering problem. Numerical results clearly prove the efficiency of the proposed algorithm.

关键词： jaya algorithm improved jaya algorithm Dynamic weight parameter Grid-search

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An efficient framework for integrating distributed generation and capacitor units for simultaneous grid-connected and islanded network operations

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INTERNATIONAL JOURNAL OF ENERGY RESEARCH 2021年第10期45卷 14920-14958页

作者： Leghari, Zohaib Hussain Hassan, Mohammad Yusri Said, Dalila Mat Memon, Zeeshan Anjum Hussain, Saddam Univ Teknol Malaysia UTM Inst Future Energy IFE Ctr Elect Energy Syst CEES Skudai 81310 Johor Bahru Malaysia Univ Teknol Malaysia UTM Fac Engn Sch Elect Engn SKE Johor Baharu Malaysia Mehran Univ Engn & Technol MUET Dept Elect Engn Jamshoro 76062 Pakistan Mehran Univ Engn & Technol MUET Dept Elect Engn SZAB Campus Khairpur Mirs Pakistan

This paper proposes a two-stage planning approach for the efficient utilization of distributed generation (DG) and capacitor banks (CBs) for the simultaneous grid-connected and islanded operations of the balanced distribution networks. The first stage determines the optimal installation locations and capacities of DGs and CBs using an improved variant of the jaya optimization algorithm (Ijaya) to minimize the power losses and voltage deviation during the grid-connected operation of the distribution network. The second stage identifies the optimal operating point of the DG and CB combination to carry the maximum load during the islanded network operation under power supply-demand imbalance conditions. For the second stage, an analytical approach is proposed to identify the best operating power factor for the DG-CB combination, calculating the power loss, and under-utilization of the installed real-reactive power sources. Simulation results on the IEEE 33-bus grid-dependent distribution network demonstrate that the proposed Ijaya significantly improved the network performance and outperforms various existing optimization methods. In addition, during the network's islanded operation, maintaining the network power factor equal to the source power factor (pf(source)) makes the DG-CB combination operate at their rated capacities.

关键词： analytical method capacitor banks distributed generation distribution network grid‐ connected and islanded operations improved jaya algorithm

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Corrective economic dispatch and operational cycles for probabilistic unit commitment with demand response and high wind power

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APPLIED ENERGY 2016年第0期182卷 634-651页

作者： Azizipanah-Abarghooee, Rasoul Golestaneh, Faranak Gooi, Hoay Beng Lin, Jeremy Bavafa, Farhad Terzija, Vladimir Univ Manchester Sch Elect & Elect Engn Manchester M13 9PL Lancs England Nanyang Technol Univ Sch Elect & Elect Engn Singapore Singapore PJM Interconnect Norristown PA USA Shiraz Univ Technol Sch Elect Elect Engn Shiraz Iran

We propose a probabilistic unit commitment problem with incentive-based demand response and high level of wind power. Our novel formulation provides an optimal allocation of up/down spinning reserve. A more efficient unit commitment algorithm based on operational cycles is developed. A multi-period elastic residual demand economic model based on the self- and cross-price elasticities and customers' benefit function is used. In the proposed scheme, the probability of residual demand falling within the up/down spinning reserve imposed by n - 1 security criterion is considered as a stochastic constraint. A chance-constrained method, with a new iterative economic dispatch correction, wind power curtailment, and commitment of cheaper units, is applied to guarantee that the probability of loss of load is lower than a pre-defined risk level. The developed architecture builds upon an improved jaya algorithm to generate feasible, robust and optimal solutions corresponding to the operational cost. The proposed framework is applied to a small test system with 10 units and also to the IEEE 118-bus system to illustrate its advantages in efficient scheduling of generation in the power systems. (C) 2016 Elsevier Ltd. All rights reserved.

关键词： Chance-constrained programming Cycle based on/off Wind energy Incentive-based demand response program Unit commitment improved jaya algorithm

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A Novel Approach to Overcome the Limitations of Reliability Centered Maintenance Implementation on the Smart Grid Distance Protection System

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IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS II-EXPRESS BRIEFS 2020年第2期67卷 320-324页

作者： Rafiei, Mehdi Khooban, Mohammad-Hassan Afshari-Igder, Mosayeb Boudjadar, Jalil Shiraz Univ Technol Dept Elect & Elect Engn Shiraz 84138 Iran Aarhus Univ Dept Engn DK-8200 Aarhus Denmark

This brief proposes a novel approach to apply reliability centered maintenance (RCM) on a distance protection system in a smart grid. In the proposed approach, instead of focusing on individual equipment, the RCM is implemented for the whole protection system. The approach helps to calculate the reliability of protection systems by overcoming the limitation of their hidden function and also considering the effect of all system equipment on reliability. Markov process and improved jaya algorithm (IJA) are used to calculate the reliability and find the optimal maintenance plan. The proposed approach has been applied to real data of smart grid distance protection systems, which results in a higher level of reliability and less cost. Furthermore, in order to validate the suggested technique and its efficiency, the simulation is carried out using a real-time digital simulators and hardware-in-the-loop testing equipment known as opal-RT technology.

关键词： Task analysis Maintenance engineering Reliability Relays Smart grids Markov processes Circuits and systems Reliability centered maintenance smart grid distance protection system Markov process improved jaya algorithm OPAL-RT

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A Mixed-Strategy-Based Whale Optimization algorithm for Parameter Identification of Hydraulic Turbine Governing Systems with a Delayed Water Hammer Effect

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ENERGIES 2018年第9期11卷 2367页

作者： Ding, Tan Chang, Li Li, Chaoshun Feng, Chen Zhang, Nan Huazhong Univ Sci & Technol Sch Hydropower & Informat Engn Wuhan 430074 Peoples R China

For solving the parameter optimization problem of a hydraulic turbine governing system (HTGS) with a delayed water hammer (DWH) effect, a Mixed-Strategy-based Whale Optimization algorithm (MSWOA) is proposed in this paper, in which three improved strategies are designed and integrated to promote the optimization ability. Firstly, the movement strategies of WOA have been improved to balance the exploration and exploitation. In the improved movement strategies, a dynamic ratio based on improved jaya algorithm is applied on the strategy of searching for prey and a chaotic dynamic weight is designed for improving the strategies of bubble-net attacking and encircling prey. Secondly, a guidance of the elite's memory inspired by Particle swarm optimization (PSO) is proposed to lead the movement of the population to accelerate the convergence speed. Thirdly, the mutation strategy based on the sinusoidal chaotic map is employed to avoid prematurity and local optimum points. The proposed MSWOA are compared with six popular meta-heuristic optimization algorithms on 23 benchmark functions in numerical experiments and the results show that the MSWOA has achieved significantly better performance than others. Finally, the MSWOA is applied on parameter identification problem of HTGS with a DWH effect, and the comparative results confirm the effectiveness and identification accuracy of the proposed method.

关键词： whale optimization algorithm meta-heuristic improved jaya algorithm chaotic mutation HTGS parameter identification

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