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1 – 10 of 173Shirin Hassanzadeh Darani, Payam Rabbanifar, Mahmood Hosseini Aliabadi and Hamid Radmanesh
The purpose of this paper is to present a new system frequency response model with participation of wind-hydro-thermal units to overcome frequency deviations.
Abstract
Purpose
The purpose of this paper is to present a new system frequency response model with participation of wind-hydro-thermal units to overcome frequency deviations.
Design/methodology/approach
The extracted minimum frequency equation is considered as a constraint in security-constrained unit commitment calculations. Because of high-order polynomials in the frequency transfer function and high degree of nonlinearity of minimum frequency constraint, Routh stability criterion method and piecewise linearization technique are used to reduce system order and linearize the system frequency response model, respectively.
Findings
The results of this paper indicate that by using this model, the hourly minimum frequency is improved and is kept within defined range.
Originality/value
This combined model can be used to evaluate the frequency of the power system following unexpected load increase or generation disturbances. It also can be used to investigate the system frequency performance and ensure power system security which are caused by peak load or loss of generation in presence of renewable energies.
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Geming Zhang, Lin Yang and Wenxiang Jiang
The purpose of this study is to introduce the top-level design ideas and the overall architecture of earthquake early-warning system for high speed railways in China, which is…
Abstract
Purpose
The purpose of this study is to introduce the top-level design ideas and the overall architecture of earthquake early-warning system for high speed railways in China, which is based on P-wave earthquake early-warning and multiple ways of rapid treatment.
Design/methodology/approach
The paper describes the key technologies that are involved in the development of the system, such as P-wave identification and earthquake early-warning, multi-source seismic information fusion and earthquake emergency treatment technologies. The paper also presents the test results of the system, which show that it has complete functions and its major performance indicators meet the design requirements.
Findings
The study demonstrates that the high speed railways earthquake early-warning system serves as an important technical tool for high speed railways to cope with the threat of earthquake to the operation safety. The key technical indicators of the system have excellent performance: The first report time of the P-wave is less than three seconds. From the first arrival of P-wave to the beginning of train braking, the total delay of onboard emergency treatment is 3.63 seconds under 95% probability. The average total delay for power failures triggered by substations is 3.3 seconds.
Originality/value
The paper provides a valuable reference for the research and development of earthquake early-warning system for high speed railways in other countries and regions. It also contributes to the earthquake prevention and disaster reduction efforts.
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This study aims to intend and implement the optimal power flow, where tuning the production cost is done with the inclusion of stochastic wind power and different kinds of…
Abstract
Purpose
This study aims to intend and implement the optimal power flow, where tuning the production cost is done with the inclusion of stochastic wind power and different kinds of flexible AC transmission systems (FACTS) devices. Here, the speed with fitness-based krill herd algorithm (SF-KHA) is adopted for deciding the FACTS devices’ optimal sizing and placement integrated with wind power. Here, the modified SF-KHA optimizes the sizing and location of FACTS devices for attaining the minimum average production cost and real power depletions of the system. Especially, the objective includes reserve cost for overestimation, cost of thermal generation of the wind power, direct cost of scheduled wind power and penalty cost for underestimation. The efficiency of the offered method over several popular optimization algorithms has been done, and the comparison over different algorithms establishes proposed KHA algorithm attains the accurate optimal efficiency for all other algorithms.
Design/methodology/approach
The proposed FACTS devices-based power system with the integration of wind generators is based on the accurate placement and sizing of FACTS devices for decreasing the actual power loss and total production cost of the power system.
Findings
Through the cost function evaluation of the offered SF-KHA, it was noted that the proposed SF-KHA-based power system had secured 13.04% superior to success history-based adaptive differential evolution, 9.09% enhanced than differential evolution, 11.5% better than artificial bee colony algorithm, 15.2% superior to particle swarm optimization and 9.09% improved than flower pollination algorithm.
Originality/value
The proposed power system with the accurate placement and sizing of FACTS devices and wind generator using the suggested SF-KHA was effective when compared with the conventional algorithm-based power systems.
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Advanced big data analysis and machine learning methods are concurrently used to unleash the value of the data generated by government hotline and help devise intelligent…
Abstract
Purpose
Advanced big data analysis and machine learning methods are concurrently used to unleash the value of the data generated by government hotline and help devise intelligent applications including automated process management, standard construction and more accurate dispatched orders to build high-quality government service platforms as more widely data-driven methods are in the process.
Design/methodology/approach
In this study, based on the influence of the record specifications of texts related to work orders generated by the government hotline, machine learning tools are implemented and compared to optimize classify dispatching tasks by performing exploratory studies on the hotline work order text, including linguistics analysis of text feature processing, new word discovery, text clustering and text classification.
Findings
The complexity of the content of the work order is reduced by applying more standardized writing specifications based on combining text grammar numerical features. So, order dispatch success prediction accuracy rate reaches 89.6 per cent after running the LSTM model.
Originality/value
The proposed method can help improve the current dispatching processes run by the government hotline, better guide staff to standardize the writing format of work orders, improve the accuracy of order dispatching and provide innovative support to the current mechanism.
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Augustine Senanu Komla Kukah, De-Graft Owusu-Manu, Edward Badu, David J. Edwards and Eric Asamoah
Public-private partnership (PPP) power projects are associated with varying risk factors. This paper aims to develop a fuzzy quantitative risk allocation model (QRAM) to guide…
Abstract
Purpose
Public-private partnership (PPP) power projects are associated with varying risk factors. This paper aims to develop a fuzzy quantitative risk allocation model (QRAM) to guide decision-making on risk allocation in PPP power projects in Ghana.
Design/methodology/approach
A total of 67 risk factors and 9 risk allocation criteria were established from literature and ranked in a two-round Delphi survey using questionnaires. The fuzzy synthetic evaluation method was used in developing the risk allocation model.
Findings
The model’s output variable is the risk allocation proportions between the public body and private body based on their capability to manage the risk factors. Out of the 37 critical risk factors, the public sector was allocated 12 risk factors with proportions = 50%, while the private sector was allocated 25 risk factors with proportions = 50%.
Originality/value
To the best of the authors’ knowledge, this research presents the first attempt in Ghana at endeavouring to develop a QRAM for PPP power projects. There is confidence in the model to efficiently allocate risks emanating from PPP power projects.
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Mukul Anand, Debashis Chatterjee and Swapan Kumar Goswami
The purpose of this study is to obtain the optimal frequency for low-frequency transmission lines while minimizing losses and maintaining the voltage stability of low-frequency…
Abstract
Purpose
The purpose of this study is to obtain the optimal frequency for low-frequency transmission lines while minimizing losses and maintaining the voltage stability of low-frequency systems. This study also emphasizes a reduction in calculations based on mathematical approaches.
Design/methodology/approach
Telegrapher’s method has been used to reduce large calculations in low-frequency high-voltage alternating current (LF-HVac) lines. The static compensator (STATCOM) has been used to maintain voltage stability. For optimal frequency selection, a modified Jaya algorithm (MJAYA) for optimal load flow analysis was implemented.
Findings
The MJAYA algorithm performed better than other conventional algorithms and determined the optimum frequency selection while minimizing losses. Voltage stability was also achieved with the proposed optimal load flow (OLF), and statistical analysis showed that the proposed OLF reduces the frequency deviation and standard error of the LF-HVac lines.
Originality/value
The optimal frequency for LF-HVac lines has been achieved, Telegrapher’s method has been used in OLF, and STATCOM has been used in LF-HVac transmission lines.
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Min Zeng, Jianxing Xie, Zhitao Li, Qincheng Wei and Hui Yang
This study aims to introduce a novel technique for nonlinear sensor time constant estimation and sensor dynamic compensation in hot-bar soldering using an extended Kalman filter…
Abstract
Purpose
This study aims to introduce a novel technique for nonlinear sensor time constant estimation and sensor dynamic compensation in hot-bar soldering using an extended Kalman filter (EKF) to estimate the temperature of the thermocouple.
Design/methodology/approach
Temperature optimal control is combined with a closed-loop proportional integral differential (PID) control method based on an EKF. Different control methods for measuring the temperature of the thermode in terms of temperature control, error and antidisturbance are studied. A soldering process in a semi-industrial environment is performed. The proposed control method was applied to the soldering of flexible printed circuits and circuit boards. An infrared camera was used to measure the top-surface temperature.
Findings
The proposed method can not only estimate the soldering temperature but also eliminate the noise of the system. The performance of this methodology was exemplary, characterized by rapid convergence and negligible error margins. Compared with the conventional control, the temperature variability of the proposed control is significantly attenuated.
Originality/value
An EKF was designed to estimate the temperature of the thermocouple during hot-bar soldering. Using the EKF and PID controller, the nonlinear properties of the system could be effectively overcome and the effects of disturbances and system noise could be decreased. The proposed method significantly enhanced the temperature control performance of hot-bar soldering, effectively suppressing overshoot and shortening the adjustment time, thereby achieving precise temperature control of the controlled object.
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Ting Zhou, Yingjie Wei, Jian Niu and Yuxin Jie
Metaheuristic algorithms based on biology, evolutionary theory and physical principles, have been widely developed for complex global optimization. This paper aims to present a…
Abstract
Purpose
Metaheuristic algorithms based on biology, evolutionary theory and physical principles, have been widely developed for complex global optimization. This paper aims to present a new hybrid optimization algorithm that combines the characteristics of biogeography-based optimization (BBO), invasive weed optimization (IWO) and genetic algorithms (GAs).
Design/methodology/approach
The significant difference between the new algorithm and original optimizers is a periodic selection scheme for offspring. The selection criterion is a function of cyclic discharge and the fitness of populations. It differs from traditional optimization methods where the elite always gains advantages. With this method, fitter populations may still be rejected, while poorer ones might be likely retained. The selection scheme is applied to help escape from local optima and maintain solution diversity.
Findings
The efficiency of the proposed method is tested on 13 high-dimensional, nonlinear benchmark functions and a homogenous slope stability problem. The results of the benchmark function show that the new method performs well in terms of accuracy and solution diversity. The algorithm converges with a magnitude of 10-4, compared to 102 in BBO and 10-2 in IWO. In the slope stability problem, the safety factor acquired by the analogy of slope erosion (ASE) is closer to the recommended value.
Originality/value
This paper introduces a periodic selection strategy and constructs a hybrid optimizer, which enhances the global exploration capacity of metaheuristic algorithms.
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Vaishali Rajput, Preeti Mulay and Chandrashekhar Madhavrao Mahajan
Nature’s evolution has shaped intelligent behaviors in creatures like insects and birds, inspiring the field of Swarm Intelligence. Researchers have developed bio-inspired…
Abstract
Purpose
Nature’s evolution has shaped intelligent behaviors in creatures like insects and birds, inspiring the field of Swarm Intelligence. Researchers have developed bio-inspired algorithms to address complex optimization problems efficiently. These algorithms strike a balance between computational efficiency and solution optimality, attracting significant attention across domains.
Design/methodology/approach
Bio-inspired optimization techniques for feature engineering and its applications are systematically reviewed with chief objective of assessing statistical influence and significance of “Bio-inspired optimization”-based computational models by referring to vast research literature published between year 2015 and 2022.
Findings
The Scopus and Web of Science databases were explored for review with focus on parameters such as country-wise publications, keyword occurrences and citations per year. Springer and IEEE emerge as the most creative publishers, with indicative prominent and superior journals, namely, PLoS ONE, Neural Computing and Applications, Lecture Notes in Computer Science and IEEE Transactions. The “National Natural Science Foundation” of China and the “Ministry of Electronics and Information Technology” of India lead in funding projects in this area. China, India and Germany stand out as leaders in publications related to bio-inspired algorithms for feature engineering research.
Originality/value
The review findings integrate various bio-inspired algorithm selection techniques over a diverse spectrum of optimization techniques. Anti colony optimization contributes to decentralized and cooperative search strategies, bee colony optimization (BCO) improves collaborative decision-making, particle swarm optimization leads to exploration-exploitation balance and bio-inspired algorithms offer a range of nature-inspired heuristics.
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Feifei Zhong, Guoping Liu, Zhenyu Lu, Lingyan Hu, Yangyang Han, Yusong Xiao and Xinrui Zhang
Robotic arms’ interactions with the external environment are growing more intricate, demanding higher control precision. This study aims to enhance control precision by…
Abstract
Purpose
Robotic arms’ interactions with the external environment are growing more intricate, demanding higher control precision. This study aims to enhance control precision by establishing a dynamic model through the identification of the dynamic parameters of a self-designed robotic arm.
Design/methodology/approach
This study proposes an improved particle swarm optimization (IPSO) method for parameter identification, which comprehensively improves particle initialization diversity, dynamic adjustment of inertia weight, dynamic adjustment of local and global learning factors and global search capabilities. To reduce the number of particles and improve identification accuracy, a step-by-step dynamic parameter identification method was also proposed. Simultaneously, to fully unleash the dynamic characteristics of a robotic arm, and satisfy boundary conditions, a combination of high-order differentiable natural exponential functions and traditional Fourier series is used to develop an excitation trajectory. Finally, an arbitrary verification trajectory was planned using the IPSO to verify the accuracy of the dynamical parameter identification.
Findings
Experiments conducted on a self-designed robotic arm validate the proposed parameter identification method. By comparing it with IPSO1, IPSO2, IPSOd and least-square algorithms using the criteria of torque error and root mean square for each joint, the superiority of the IPSO algorithm in parameter identification becomes evident. In this case, the dynamic parameter results of each link are significantly improved.
Originality/value
A new parameter identification model was proposed and validated. Based on the experimental results, the stability of the identification results was improved, providing more accurate parameter identification for further applications.
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