bluuebunny/crossref_metadata_2025_split huggingface dataset:
Parameter identification and uncertainty quantification of a non‐linear pump‐turbine governing system based on the differential evolution adaptive Metropolis algorithm
Authors: Zhang Chu , Peng Tian , Zhou Jianzhong , Nazir Muhammad Shahzad 
Published: January 2021

AbstractPumped storage units (PSUs) are now widely used for energy storage. However, the uncertainty of the identification results of the pump‐turbine governing system (PTGS) caused by the random observation noises and the lack of prior knowledge remains an unaddressed issue. In recent years, the differential evolution adaptive Metropolis algorithm (DREAM) based on the Bayesian theory has been extensively used for parameter estimation and uncertainty analysis, but its application to the uncertainty analysis of PTGS has been rare. This study systematically evaluates the applicability of DREAM in the parameter identification and uncertainty quantification of PTGS. A real PSU in China has been employed as a case study for numerical experiments. Four groups of control experiments with different proportions of observation noises and different prior search spaces have been constructed in this study. It can be concluded from this study that: (a) accurate point identification results and effective uncertainty quantification can be obtained simultaneously using DREAM, (b) a lower proportion of observation noises can enhance the efficiency and effectiveness of the DREAM algorithm when applying to PTGS simulation. The DREAM method can narrow the prior search space of PTGS parameters effectively and thus help the hydropower engineers to make decisions.
Hybrid transformerless PV converters with low leakage currents: Analysis and configuration
Authors: Tang Zhongting , Yang Yongheng , Wan Jianghu , Blaabjerg Frede 
Published: January 2021

AbstractThis paper proposes a hybrid transformerless photovoltaic (PV) converter with simultaneous AC and DC outputs. It is specifically suitable for residential PV systems due to its high efficiency, versatility and flexibility, while maintaining lower leakage currents. The proposed converter is configured by replacing the control switch of the boost converter with a transformerless voltage‐source inverter (VSI), enabling multiple outputs. In addition, a symmetrical boost inductor is adopted to clamp the common‐mode voltage as a constant, resulting in low leakage currents. To illustrate the configuration principle, a hybrid converter with a highly efficient and reliable inverter concept (HERIC) as the VSI is exemplified. Besides, the dedicated modulation scheme for the proposed converter is detailed to achieve low leakage currents, reactive power injection and high efficiency. Furthermore, as the shoot‐through state of inverter legs is allowable for the proposed converter, i.e. no need to add dead time, the reliability and power quality of the proposed converter can be improved. Simulations and experimental tests are performed on an example hybrid converter (with an HERIC as the VSI) to validate the analysis.
A comprehensive review on time‐delay compensation techniques for grid‐connected inverters
Authors: Elhassan Garba , Zulkifli Shamsul Aizam , Pathan Erum , Khan Mubashir H. , Jackson Ronald 
Published: January 2021

AbstractThe control of grid‐connected inverters is recently executed with digital microprocessors due to the advances in digital signal processing technology. However, the digital realisation has a drawback of the phase lag induced by the time‐delay. This phase lag challenges the stability and robustness of the controller of the inverters. In view of the challenge, this paper presents a comprehensive review of time‐delay compensation techniques employed in both model‐free (MF), and model‐based (MB) controls of an inverter in grid connection. MF techniques mainly use proportional‐integral, and proportional resonance controllers with some techniques to reduce time‐delay. Meanwhile, for MB, this paper discusses the commonly used control techniques, which are the Smith predictor, modified Smith predictor, deadbeat controller and model predictive controller. Several related techniques from the literature that have been adopted to mitigate the delays are tabulated comprehensively, and critical issues regarding the MF and MB techniques are also discussed. Finally, this paper presents a hypothesis on which technique is superior at present and suggests a hybrid technique from the MF and MB techniques to give readers a direction for further research.
Strict Lyapunov super twisting observer design for state of charge prediction of lithium‐ion batteries
Authors: Sethia Gautam , Majhi Somanath , Nayak Sisir Kumar , Mitra Sagar 
Published: January 2021

AbstractThe effective implementation of battery management system (BMS) in various applications such as electric vehicles (EVs), renewable energy sources (RES) integrated smart‐grids and micro‐grids, necessitates accurate estimation of the battery parameters and states. This paper primarily focuses on offering an improved solution to the state of charge (SOC) estimation problem of lithium‐ion (Li‐ion) batteries. After extensive analysis of the current state‐of‐the‐art methods, a new strict Lyapunov super twisting algorithm (SLSTA) based approach is proposed for precise estimation of SOC under a comprehensive range of uncertainties. The error convergence and robustness of the proposed state observer are demonstrated using Lyapunov stability theory. Since the modelling parameters of the battery equivalent circuit utilised in this paper vary with various operational and external factors, a standard online method is employed for their real‐time identification. The presented method is executed on a lithium‐polymer (LiPo) battery with the help of a dynamic stress test (DST). The experimental results demonstrate that the proposed approach outperforms the well‐known approaches in terms of accuracy, computational complexity, and convergence time.
A regression model for extreme events and the presence of bimodality with application to energy generation data
Authors: Vasconcelos Julio Cezar Souza , Cordeiro Gauss Moutinho , Ortega Edwin Moises Marcos , Ribeiro João Gabriel 
Published: January 2021

AbstractThe application of the theory of extreme values has been growing due to increasing interest in extreme natural events. Many articles on extreme values in data modelling consider unimodal data. This work introduces an appropriate regression for extreme values to detect the presence of bimodality by means of systematic components of two parameters of the odd log‐logistic log‐normal distribution. The global influence is addressed to verify the model robustness and to find possible influential points. Quantile residuals are proposed to detect distribution deficiencies and outliers in the new regression. A real dataset from the electricity generation area is analysed, namely the Santo Antônio Hydroelectric Plant in the state of Rondônia (Brazil), to illustrate the potential of the new regression. The main results indicate that the proposed regression can identify changes in the means and variability of the power generation between extreme events, that is, between the months of June and December.
Bi‐level power management strategy in harmonic‐polluted active distribution network including virtual power plants
Authors: Rohani Arash , Abasi Mahyar , Beigzadeh Arsalan , Joorabian Mahmood , B. Gharehpetian Gevork 
Published: January 2021

AbstractIn this paper, a bi‐level power management strategy is presented for an active distribution network (ADN) in the presence of virtual power plant (VPP). In the proposed strategy, VPP contains renewable energy source (RES), energy storage system (ESS) and electric vehicles (EVs) parking lot coordinated with VPP operator (VPPO), and there is a coordinated framework between VPPO and distribution system operator. The proposed power management strategy (PMS) is considered in the context of the bi‐level optimization problem. In the first level, the optimal harmonic power flow formulation of the ADN is considered by minimizing the summation of energy cost, voltage deviation function and voltage THD% as a normalized objective function. In the second level, the VPP is modeled according to the framework of day‐ahead energy and ancillary services markets. In the next step, the linear format of the proposed non‐linear original problem is obtained with an optimal solution and low calculation burden. Also, the Karush‐Kuhn‐Tucker condition is used to convert the proposed bi‐level PMS approach to a single‐level model, and the scenariobased stochastic programming models the uncertainty of load, energy price, RES power, and EVs demand. Finally, the proposed strategy is applied on the 33‐bus distribution network using GAMS software.
Cascaded diode clamped inverter based grid‐connected photovoltaic energy conversion system with enhanced power handling capability and efficiency
Authors: Rao Pandry Narendra , Saini Lalit Mohan , Nakka Jayaram 
Published: January 2021

AbstractThis paper proposes a high power factor converter based symmetrical topology entitled cascaded diode clamped half‐bridge multi‐level inverter for high voltage photovoltaic (PV) applications along with a hybrid multi‐level pulse width modulation technique. Due to the restriction of peak inverse voltage (PIV) on switching devices, the PV array voltage is restricted. Also, operating at high current causes switching losses and degrades the efficiency, hence limiting its power enhancement. Unbalance in the capacitor voltages leads to high PIV across the devices, which is undesirable. The proposed topology allows connecting double times PV array voltage keeping the PIV and current alike cascaded H‐bridge multi‐level inverter, hence increasing the efficiency, and thereby reducing cost and space. It ensures a capacity enhancement in renewable energy systems linked to on/off‐grid applications. The projected scheme allows even power distribution among the sources along with maximum and efficient energy conversion. The control scheme adopted has the ability to balance dc‐link capacitor voltage in each half‐bridge results in equal PIV and switching losses across all the devices. Simulations of PV connected modified topology is carried out and validated with experimental results.
Optimization of the reverse electrodialysis power output through the ratio of the feed solutions salinity
Authors: Zoungrana Ali , Çakmakci Mehmet 
Published: January 2021

AbstractA lab‐scale reverse electrodialysis module was constructed to highlight the optimal feed solutions concentration, the flow rate and their importance in improving the power density in reverse electrodialysis. The results showed that the increase of the feed solutions flow rate is beneficial by augmenting the power output, but too high flow rate harms the process performance. Even though the highest power density (0.54 W/m2) was obtained at 60 mL/min with 4 and 428 mm feed solutions, the optimal flow rate determined by this study was 30–45 mL/min. It has been discovered that the variation of NaCl concentration in the low compartment was more sensible in affecting the reverse electrodialysis performance compared to the high compartment solution. The NaCl concentration of 6 and 684 mm appeared to be the optimal values for low compartment and high compartment solutions, respectively, for high performance and efficient power generation with reverse electrodialysis using seawater and river. When 1/3 of the minimum flow rate of the Ceyhan River running into the Mediterranean Sea is operated in the reverse electrodialysis system, at least 17.18 × 106 KWh electrical energy was estimated to be generated per year, with a power density of 0.705 m2/W.
Demand response integration in microgrid planning as a strategy for energy transition in power systems
Authors: Mina‐Casaran Juan D. , Echeverry Diego F. , Lozano Carlos A. 
Published: January 2021

AbstractFor a long time, the planning of power systems has considered technical and economic aspects related to Supply Side Management. Given that this traditional planning approach is not very flexible, and due to new technological trends like the adoption of smart grids, it has become necessary for demand to play an active role in the operation of power systems. This raises the need to implement a new process for power system planning, focusing on technologies such as microgrids with Demand Side Management, which contribute to the sustainable development of communities. In this paper, a comprehensive review of microgrid planning, considering energy end‐user participation through Demand Response, is carried out. In addition, the main features and implications of Demand Response programs in microgrid planning are presented. As a contribution, in order to trigger a paradigm shift on how power systems are planned, the benefits of bottom‐up microgrid planning are presented.
GNSS data demodulation over fading environments: Antipodal and M‐ary CSK modulations
Authors: Ortega Lorenzo , Vilà‐Valls Jordi , Poulliat Charly , Closas Pau 
Published: January 2021

AbstractThis article investigates new strategies to compute accurate low‐complexity log‐likelihood ratio (LLR) values based on the Bayesian formulation under uncorrelated fading channels for both antipodal and code shift keying modulations when no channel state information (CSI) is available at the receiver. These LLR values are then used as input to modern error‐correcting schemes used in the data decoding process of last‐generation Global Navigation Satellite System signals. Theoretical analysis based on the maximum achievable rate is presented for the different methods in order to evaluate the performance degradation with respect to the optimal CSI channel. Finally, the frame error rate simulation results are shown, validating the appropriate performance of the proposed LLR approximation methods.
Magnetic properties of an ACSR conductor steel core at temperatures up to 230 ∘C and their impact on the transformer effect
Authors: Meyberg Ruyguara A. , Absi Salas Farith M. , Domingues Luis Adriano M. C. , Sens Márcio A. , Correia de Barros Maria Teresa , Lima Antonio C. S. 
Published: January 2021

AbstractThe current density distribution between layers of steel‐reinforced conductors having an odd number of aluminum layers is modified by the transformer effect, as a result of the steel core magnetisation. This redistribution of current affects the conductor alternating current resistance, the transitory temperature radial distribution, and depends on the total current intensity, and the core permeability, which varies with temperature. Although some steel‐cored conductors are designed to operate at high temperatures to maximise their current capacity, the core magnetic properties in this scenario need to be further investigated. This paper presents the results of experimental work on an ACSR conductor, and on its steel core to investigate the steel core magnetic properties over an extended temperature range, and how they affect the transformer effect. Results show an unexpected hump‐shaped variation of the permeability with temperature in a specific range of magnetic field strength, with maximum permeability values occurring at a temperature ranging from 150 to 170 C , which were not covered in previous studies. A similar behaviour is seen in the variation of the axial magnetic flux with increasing conductor temperature, causing the flux to decrease at high temperatures, and thus weakening the transformer effect during the conductor operation.
The challenge of controlling microgrids in the presence of rare events with deep reinforcement learning
Authors: Levent Tanguy , Preux Philippe , Henri Gonzague , Alami Réda , Cordier Philippe , Bonnassieux Yvan 
Published: January 2021

AbstractThe increased penetration of renewable energies and the need to decarbonise the grid come with a lot of challenges. Microgrids, power grids that can operate independently from the main system, are seen as a promising solution. They range from a small building to a neighbourhood or a village. As they co‐locate generation, storage and consumption, microgrids are often built with renewable energies. At the same time, because they can be disconnected from the main grid, they can be more resilient and less dependent on central generation. Due to their diversity and distributed nature, advanced metering and control will be necessary to maximise their potential. This paper presents a reinforcement learning algorithm to tackle the energy management of an off‐grid microgrid, represented as a Markov Decision Process. The main objective function of the proposed algorithm is to minimise the global operating cost. By nature, rare events occur in physical systems. One of the main contribution of this paper is to demonstrate how to train agents in the presence of rare events. Merging the combined experience replay method with novel methods called ‘Memory Counter’ unstucks the agent during its learning phase. Compared to baselines, an extended version of double deep Q‐network with a priority list of actions into the decision making strategy process lowers significantly the operating cost. Experiments are conducted using 2 years of real‐world data from Ecole Polytechnique in France.
Impact of data availability and pseudo‐measurement synthesis on distribution system state estimation
Authors: Zufferey Thierry , Hug Gabriela 
Published: January 2021

AbstractThe influence of the advanced metering infrastructure (AMI) set‐up and of the related modelling of pseudo‐measurements on the accuracy of state estimation (SE) in distribution grids, especially at the low‐voltage level, is studied herein. A comprehensive sensitivity analysis is carried out that accounts for the type, the penetration level, and the placement of the metering devices that compose state‐of‐the‐art AMIs. Special care is given to the synthesis of active and reactive power pseudo‐measurements, which substantially impacts the estimation of peak values. Although crucial for system operators, peak values are very often neglected in the SE literature. For that purpose, this study promotes realistic approaches to generate synthetic load profiles and relies on evaluation metrics that are not purely based on the point‐wise precision but consider the statistical properties of the SE outcomes. This is tested on an actual 971‐bus distribution grid with the corresponding smart meter data and is evaluated with respect to the accuracy of active and reactive power injections, bus voltages, and line loadings.
Homological dimensions of Banach spaces
Authors: Sánchez F. Cabello , Castillo J. M. F. , García R. 
Published: January 2021

Abstract
The purpose of this paper is to lay the foundations for the study of the problem of when

in Banach spaces. We provide a number of examples of couples

,

such that

is (or is not)

. We show that

for all

when

is the Kadec space. In particular, both the projective and injective dimensions of

are infinite.
Bibliography: 48 titles.
Cross-linguistic influence in the second language processing of Korean morphological and syntactic causative
constructions
Authors: Park Sun Hee , Kim Hyunwoo 
Published: January 2021

Abstract
This study investigated the effects of cross-linguistic influence in Japanese speakers’ integration of
morphological and syntactic information during the processing of Korean transitive causative constructions. We examined whether
Japanese speakers would process two types of Korean causative constructions as efficiently as native speakers: (a) when one target
structure was instantiated differently from learners’ L1 correspondents and (b) when the other type was unique to the L2. Although
the learners showed native-like performance during an acceptability judgment task, they had difficulties with the integration of
morphological and syntactic information during a self-paced reading task when the target construction gave rise to
cross-linguistic competitions with the L1 correspondent, but not when the target construction was unique to the L1. Our findings
support the claim that cross-linguistic cue competitions are a major source of difficulties in L2 sentence processing.
Corrigendum: Analytic expressions for gravitational inner multipole moments of elementary solids and for the force between two rectangular solids (2005 Class. Quantum Grav.
23
125)
Authors: Lee J G , Adelberger E G , Collins N A , Hoyle C D 
Published: January 2021

Abstract
We correct errors in seven of the more than 100 expressions for the gravitational inner spherical multipole moments of several homogeneous solids. No additional corrections have been found.
A high-precision unmanned aerial vehicle positioning system based on ultra-wideband technology
Authors: Li Tian-yu , Duan Fa-jie , Liang Chun-jiang , Jiang Jia-jia , Fu Xiao , Wang Qi , Huang Hui-xiong , Wei Qi-feng 
Published: January 2021

Abstract
With the help of artificial intelligence technology, the unmanned aerial vehicle (UAV) industry is booming. In the civilian field, a series of fully functional UAV products have emerged one after another, giving birth to a huge industrial chain. To strengthen the UAV market supervision, many countries have introduced a series of standards to regulate UAV products, but they have not yet developed a high-precision positioning system for UAV quality inspection. In this paper, we proposed a high-precision UAV positioning method based on ultra-wideband (UWB) technology. We analyzed the algorithm, base station layout, and clock synchronization to improve the accuracy of the UWB positioning system and established a high-precision UAV trajectory tracking and measurement system based on UWB technology, realizing real-time high-precision positioning of UAVs. Based on the Chan algorithm, we analyzed the base station layout method in combination with the system construction site and proposed a new delay calibration method between positioning base stations. Experimental results show that we have achieved a horizontal accuracy of under 0.1 m and a vertical accuracy of under 0.15 m in a space of 120 m × 60 m × 40 m.
Magnetohydrodynamic simulations of runaway electron beam termination in JET
Authors: Bandaru V , Hoelzl M , Reux C , Ficker O , Silburn S , Lehnen M , Eidietis N , Team JOREK 
Published: January 2021

Abstract
A runaway electron (RE) fluid model is used to perform non-linear magnetohydrodynamic simulations of a relativistic electron beam termination event in JET. The case considered is that of a post-disruption low density cold plasma in the runaway plateau phase, wherein high-Z impurities have been largely flushed out via deuterium second injection (Shot:95135). Details of the experiment are found in separate publications. Our studies reveal that a combination of low plasma density and a hollow current profile which is confirmed by experimental studies causes fast growth of a double-tearing mode, which in turn leads to stochastization of the magnetic field and a prompt loss of REs. The phenomenology of events leading to the crash and the timescales of the dynamics are in excellent agreement with the experiment. Simulations also indicate significant toroidal variation in RE deposition but without localized hotspots. The strong stochastization setting in first from the edge leads to a poloidally broad deposition footprint that partly explains the benign nature of the termination event. This work further supports the potential possibility to engineer a benign RE beam termination scenario via deuterium second injection in ITER, as proposed by Reux et al ‘Runaway electron beam suppression using impurity flushing and large magnetohydrodynamic instabilities’ (submitted to Physical Review Letters).