bluuebunny/crossref_metadata_2025 huggingface dataset:
Multi‐user two‐way relaying in the presence of co‐channel interference
Authors: Ozduran Volkan , Soleimani‐Nasab Ehsan
Published: February 2021

This study investigates the impact of co‐channel interference caused by external terminals on multi‐user bi‐directional amplify‐and‐forward based wireless relaying network. The investigation considers multi‐user pair and a single bi‐directional relay terminal and a finite number of co‐channel interference in the system model. A lower bound on the end‐to‐end outage probability is derived for the simultaneous transmission and the opportunistic source‐pair selection strategy. According to analytical, asymptotic, and Monte‐Carlo based computer simulation results, the opportunistic source‐pair selection strategy achieves a near‐optimal performance for the inter‐cell interference caused by other user‐pairs within the system. Results also show that the opportunistic source‐pair selection strategy also achieves optimal diversity order, which is equal to N, in high signal‐to‐noise ratio regimes. Results also show that the co‐channel interference degrades the achievable diversity order from N to 0 while also affecting the system coding gain.
Performance evaluation of heterogeneous wireless information and power networks
Authors: Li Rui , Cao Ning , Chen Yunfei , Mao Minghe
Published: February 2021

In this study, the performance of downlink simultaneous wireless information and power transfer (SWIPT) networks over Nakagami‐m fading is analysed. The SWIPT network is modelled as a two‐tier heterogeneous network, where one tier is the information transmission network and the other is the power transmission network. The seamless integration enables both data and energy to be transferred from access points to the users. Using the stochastic geometry theory, the expressions for outage probability at the information receiver are derived in decoupled and integrated SWIPT networks. Also, the average harvested energy at the power receiver is derived assuming a non‐linear energy harvesting model. Simulation results validate the analytical expressions and the impacts of various system parameters on the SWITP performance are investigated.
Novel fast session transfer decision‐making algorithm using fuzzy logic for Wi‐Fi/WiGig wireless local area networks
Authors: Mohamed Ehab Mahmoud , Nassef Ahmed M.
Published: February 2021

Fast session transfer (FST) is introduced by wireless gigabit (WiGig) standards to transfer the data communication session among wireless fidelity (Wi‐Fi) and WiGig channels based on the availability. In the conventional Wi‐Fi/WiGig FST decision‐making, the session of data transmission is transferred from Wi‐Fi to WiGig whenever it is possible regardless of the traffic loads on both bands and the expected WiGig blocking probability. Also, WiGig to Wi‐Fi FST occurs whenever the WiGig signal is lost even if the WiGig link is undergoing an instant path blocking. This results in Wi‐Fi/WiGig load imbalance as well as large average delay in user data delivery. In this study, a novel Wi‐Fi/WiGig FST decision‐making algorithm is proposed utilising fuzzy logic while considering the coverage probability of the WiGig link, the sizes of the users' remaining messages relative to the available data rates of both bands, and the probability of WiGig path blocking. Furthermore, a WiGig interruption‐classification methodology is proposed to detect the occurrence of the WiGig instant path blocking and then decide if it is better to wait for WiGig signal recovery or immediately transfer to Wi‐Fi. Simulation analysis demonstrates the effectiveness of the proposed Wi‐Fi/WiGig FST decision‐making algorithm, over the conventional one.
Buffer‐aided relaying: a survey on relay selection policies
Authors: El‐Rajab Mirna , Abou‐Rjeily Chadi , Kfouri Ronald
Published: February 2021

Ever since the idea of buffers was incorporated in wireless communications, buffer‐aided relaying has become an emerging breakthrough in the world of transmitting and receiving signals. Equipping the relays with buffers adds a new degree of freedom capable of enhancing numerous quality‐of‐service (QoS) metrics including throughput, outage probability, power efficiency and physical‐layer security. The QoS enhancement is achieved by compromising the end‐to‐end delay that is inflicted by storing the packets in the relays' buffers until a suitable source–relay or relay–destination link is selected. In this context, the selection of a relay for transmission/reception is important since it governs the QoS‐delay trade‐off that can be contemplated. In this survey, the authors review and analyse various link selection protocols in buffer‐aided relaying systems. These relaying strategies are categorised and contrasted according to their performance levels, limitations, applications, system model assumptions and complexity. Finally, they discuss current challenges, and highlight future research directions.
Joint AGC and receiver design for large‐scale MU‐MIMO systems with low‐resolution signals in C‐RANs
Authors: Cunha Thiago E.B. , de Lamare Rodrigo C. , Ferreira Tadeu N. , Landau Lukas T.N.
Published: February 2021

Large‐scale multi‐user multiple‐input multiple‐output (MU‐MIMO) systems and cloud radio access networks (C‐RANs) are promising technologies for the fifth generation (5G) of wireless networks. In this context, the use of low‐resolution analogue‐to‐digital converters (ADCs) is key for energy efficiency and for complying with constrained fronthaul links. Processing signals with a few bits implies performance loss and, therefore, techniques that can compensate for quantisation distortion are fundamental. In wireless systems, an automatic gain control (AGC) precedes the ADCs to adjust the input signal level in order to reduce the impact of quantisation. In this work, the authors propose the joint optimisation of the AGC, which works in the remote radio heads (RRHs), and a low‐resolution aware (LRA) linear receive filter based on the minimum mean square error (MMSE), which works in the cloud unit (CU), for large‐scale MU‐MIMO systems with coarsely quantised signals. They develop linear and successive interference cancellation receivers based on the proposed joint AGC and LRA MMSE (AGC‐LRA‐MMSE) approach. An analysis of the achievable sum rates along with a computational complexity study is also carried out. Simulations show that the proposed AGC‐LRA‐MMSE design obtains substantial gains in bit error rates and achievable information rates over existing techniques.
Energy efficiency maximisation based on RALA protocol for underlay D2D communication
Authors: Saad Waleed , Refky Hajar , Shokair Mona
Published: February 2021

Energy efficiency (EE) maximisation is one of the most important necessities of the fifth‐generation (5G) wireless networks. In this study, both power allocation and channel assignment issues for the cellular network underlaid with device to device (D2D) communication are introduced. The main objective is to assign the users’ resources in order to maximise the total EE of the network. The distributions of both the D2D users (DUs) and the cellular users (CUs) are based on the stochastic geometry theory. Hence, the mathematical formula for the optimisation problem is demonstrated. Additionally, the resource allocation link admission (RALA) algorithm is proposed to achieve the maximum EE. Moreover, it assigns the optimal powers for each CU and DU in the system. Furthermore, the best channel assignment for each new D2D link request is determined. The optimisation problem in the RALA scheme is solved by utilising a proposed modified Cuckoo search algorithm. Furthermore, the complexity analysis for the proposed scheme is introduced. From simulation results, the proposed RALA scheme is efficient to assign the resource allocation for the users to achieve the near‐optimal EE.
Iterative AP selection, MMSE precoding and power allocation in cell‐free massive MIMO systems
Authors: Palhares Victoria M.T. , de Lamare Rodrigo C. , Flores André R. , Landau Lukas T.N.
Published: February 2021

In this work, the authors proposed the iterative access point (AP) selection (APS), linear minimum mean‐square error (MMSE) precoding and power allocation techniques for cell‐free massive multiple‐input multiple‐output (MIMO) systems. They considered the downlink channel with single‐antenna users and multiple‐antenna APs. They derive sum‐rate expressions for the proposed iterative APS techniques followed by MMSE precoding and optimal, adaptive, and uniform power allocation schemes. Simulations show that the proposed approach outperforms existing conjugate beamforming and zero‐forcing schemes and that performance remains excellent with APS, in the presence of perfect and imperfect channel state information.
Concurrent transmission scheduling algorithm based on Stackelberg game to enhance time reuse for D2D communications in mmWave networks
Authors: Li Yu , Wang Honggang , Guo Zhiwei , Yang Ting , Yang Shiju
Published: February 2021

Due to the tremendous propagation loss of millimeter wave (mmWave) communication, device‐to‐device (D2D) communications are widely used over directional mmWave networks to improve network throughput. Most of existing works are mainly focused on concurrent transmission among D2D pairs that have no mutual interference. However, considering the propagation loss and directional interference features, the D2D pairs that interfere with each other can be used to improve network throughput. In this paper, we propose a time resource sharing scheme based on Stackelberg game for D2D pairs to further enhance network throughput. The interference D2D pairs can access to the time resource through paying the price for the interference caused by them. At the same time, the non‐interference D2D pairs can be scheduled. Concurrent transmission scheduling among interference D2D pairs is formulated as a non‐cooperative game, which enables a distributed transmission power control for interference D2D pairs. Moreover, the price strategy can be adjusted by setting interference threshold such that the transmission quality can be guaranteed. Simulation results show that the proposed scheme can achieve significant performance gains compared with classical concurrent transmission in terms of network throughput and energy efficiency. In addition, the convergence and utility of the game are also verified.
Retracted: Combined mixed Gaussian model with pattern recognition in the automatic diagnosis of Alzheimer's disease
Authors: Qian Mingyue , Zhang Zhaoting , Chen Jiechun
Published: February 2021

The diagnosis and prevention of Alzheimer's disease plays an important role in improving patient cognition. It can be seen from the current situation that the diagnosis of Alzheimer's disease is still poor because it is affected by many factors. Based on this, combined with the symptoms of Alzheimer's disease, this study used computer‐aided to diagnose the symptoms of patients. First of all, this study analyses classical machine learning and chooses the appropriate model for diagnosis. Next, this study constructs a diagnostic system based on a mixed Gaussian model and uses a mixed Gaussian model to predict the probability of different distribution methods. Finally, this study designs experiments to analyse the performance of diagnostic models. Studies have shown that the mixed Gaussian model has a good effect on the automatic diagnosis of Alzheimer's disease, and can provide a theoretical reference for subsequent related research.
Category‐wise feature extractor based on ADL method for weak‐supervised object localisation
Authors: Hu Yanzhu , Zhu Dongdong , Ai Xinbo , Xu Yabo
Published: February 2021

Fully supervised object detection needs to use the data set with object category annotation and location annotation to train the model. In contrast, weak supervised object localisation only needs to use the data set with object category annotation to train the model, but it can complete the classification task and object localisation task at the same time. Inspired by the attention‐based dropout layer (ADL) method, this study designs a category‐wise feature extractor (CFE), which can explicitly obtain the localisation map used to indicate the object location, and it is directly related to the category output of the classification task. Although its amount of calculation is slightly larger than that of the ADL method, the performance is better than ADL in some tasks. In addition to the standard CFE method mentioned above, this study also designs a lightweight CFE‐tiny method, which adopts split‐attention mechanism, and the calculation amount of this method is much smaller than that of ADL method.
Modified demagnetisation control strategy for low‐voltage ride‐through enhancement in DFIG‐based wind systems
Authors: Senapati Manoj Kumar , Pradhan Chittaranjan , Nayak Paresh Kumar , Padmanaban Sanjeevikumar , Gjengedal Terje
Published: February 2021

The large‐scale wind energy conversion systems (WECSs) based on doubly‐fed induction generators (DFIGs) are very popular in recent years due to the numerous technical and economic benefits. With the increasing penetration level of wind energy, the latest grid codes require the DFIG‐based WECSs to remain connected to the grid under grid fault scenarios and deliver the required reactive power into the grid. However, the direct connection of the stator of the DFIG to the grid makes it prone to grid disturbances, especially to voltage sag. This study proposes a modified demagnetisation control strategy to enhance the low‐voltage ride‐through (LVRT) capability of the DFIG under grid faults. The proposed control strategy is implemented in a coordinated approach by using the existing demagnetisation control and the addition of an external resistance in the stator side of the DFIG. The demagnetisation control damps the direct current component of the stator flux and the external resistance accelerates the damping of the transient flux by decreasing the time constant and hence, enhancing the LVRT capability of DFIG. The effectiveness of the proposed control strategy is demonstrated under both symmetrical and asymmetrical grid faults simulated system through MATLAB/Simulink®. The comparative results justify the merits of the proposed methodology.
Hybrid islanding detection technique for single‐phase grid‐connected photovoltaic multi‐inverter systems
Authors: Barkat Fadila , Cheknane Ali , Guerrero Josep M. , Lashab Abderezak , Istrate Marcel , Viorel Banu Ioan
Published: February 2021

This study presents the performance of a novel hybrid islanding detection method for multi‐single‐phase photovoltaic (PV) inverters based on the combination of four active methods and three passive methods. Although islanding detection in PV multi‐inverter systems has been widely researched, most islanding studies are focused on three‐phase inverters, rather than single‐phase ones. In this study, different active and passive methods are used to detect the islanding of four paralleled single‐phase PV inverters. By combining those methods synergistically, it reduces their weakness of each method, while combining their advantages. The novelty of the proposed system methodology consists of four paralleled single‐phase inverters equipped with four different active methods, namely active frequency drift, Sandia frequency shift (SFS), sliding mode frequency shift, and Sandia voltage shift triggered by a block composed of three passive methods: voltage frequency protection, rate of change of frequency, and DC‐link. This novel hybrid system is studied under different detailed scenarios, where it shows its performance and characteristics.
Reliability‐oriented optimal planning of charging stations in electricity–transportation coupled networks
Authors: Xiang Yue , Meng Jinpeng , Huo Da , Xu Lixiong , Mu Yunfei , Gu Chenghong , Hou Kai , Teng Fei
Published: February 2021

To coordinate the increasing application of electric vehicles (EVs), the deployment of charging stations becomes vital for supporting the charging and navigation for EVs, which also affects the reliability of the corresponding electricity network. To achieve the balanced reliability in both the electricity network and EV trip, an optimal planning method for charging stations in the electricity‐transportation coupled networks is proposed. Firstly, an integrated management strategy of EVs is demonstrated to model the reliability enhancement of the two networks. Thereafter, a coupled network reliability assessment method based on the quasi‐sequential Monte Carlo simulation is presented. This study proposes a novel reliability‐oriented multi‐objective optimal planning model for charging stations planning problem, which is resolved by implementing the optimal planning scheme from the candidate nodes. Additionally, correlation analysis is performed to ensure that the proposed model can be solved quickly for large‐scale electricity network with complex transportation flow input data. A test case is presented and simulated to validate the feasibility and effectiveness of the proposed method.
Hierarchical two‐stage robust optimisation dispatch based on co‐evolutionary theory for multiple CCHP microgrids
Authors: Tan Bifei , Chen Haoyong , Zheng Xiaodong
Published: February 2021

Combined cooling, heating, and power (CCHP) microgrids are a special form of a microgrid that is attracting increasing attention. This study contributes to the goal of minimising the operation cost of CCHP microgrids by proposing a hierarchical two‐stage robust optimisation dispatch model for multiple CCHP microgrid systems. The uncertainties associated with wind power output, electric power, heating, and cooling loads, and transmission line failures are considered in the proposed model. Moreover, the electricity purchasing and selling prices of each microgrid are independently determined. The proposed model applies the outputs of fuel cells, energy storage devices, and gas turbines, the distribution factor of waste heat, and the power transmission between the microgrids and an external grid as control variables. The optimised dispatch problem is solved using McCormick envelopes relaxation and a novel column and constraint generation algorithm that provides enhanced optimisation performance by implementing co‐evolutionary theory. In this way, the microgrid system is divided into several sections, and each section is represented as an individual min–max–min problem. The rationality and validity of the proposed model and the superiority of the solution performance of the improved algorithm are verified through simulation case studies involving a system composed of four CCHP microgrids.
Estimation of PV module degradation through extraction of I–V curve at inverter pre‐startup condition
Authors: Pradeep Kumar Boggarapu , Nitheesh Rajendran , Chakkarapani Manickam , Saravana Ilango Ganesan , Nagamani Chilakapati
Published: February 2021

Decline in photovoltaic (PV) output power is observed due to aging factors such as solder bond failure, corrosion of busbars, formation of cracks in solar cell, failures of bypass diode etc. Furthermore, these happenings reflect changes in PV module parameters such as increment in series resistance/reduction in open‐circuit voltage and/or decrease in fill factor etc. However, these parameter variations can be easily examined with the module level I–V curve. This study proposes a new approach of exploring the I–V curve of the PV module using an inverter pre‐startup condition, i.e. just before sending the PV power to the grid. From this pre‐startup I–V curve, one of the important parameters, i.e. module series resistance is estimated. The proposed method is investigated through simulations in MATLAB/Simulink and is experimentally tested on a PV output coupled to a grid‐connected micro‐inverter. The key advantage of the proposed method is that it does not require any additional circuitry/sensors to extract the I–V curve. Furthermore, there is no need to disconnect the PV from its normal operation.
Screening methodology of correlated wind turbines for wind direction prediction based on yawing manoeuvre data
Authors: Shen Xiaojun , Fu Xuejiao , Su Zhichao
Published: February 2021

Accurate prediction of wind direction can improve wind energy utilisation and extend the life of the wind turbine yaw system effectively. The ‘measurement–sharing–correlation–prediction–verification’ (MSCPV) wind parameter sensing technology based on the turbine network provides a new perspective for wind direction prediction, in which the screening of correlated wind turbines is a key step. In this study, a calculation method of wind direction spatial correlation is proposed, and correlated turbines are selected according to the correlation strength. The study first analyses the limitations of traditional wind direction correlation based on the principle of MSCPV and proposes the concept of correlated turbine screening based on yawing correlation. Then, the modelling and calculation of yawing correlation are analysed in detail. The prediction based on correlated wind turbines selected by different methods is evaluated. Case study results show that compared to wind direction correlation and wind turbines' distance, the yawing correlation has a better effect on the screening of the spatially correlated turbines. The prediction accuracy based on different correlated turbines is positively correlated with the degree of yawing correlation, indicating the proposed screening method is effective.
Design of series resonant switched‐capacitor equaliser for series‐connected battery strings
Authors: Liu Lizhou , Xu Bin , Xiong Liang , Sun Wenbin , Zhou Wei , Li Yong , Mai Ruikun , He Zhengyou
Published: February 2021

The traditional pure switched‐capacitor equaliser brings the large inrush current and low energy density. This study proposes a series of resonant switched‐capacitor (ReSC) voltage equaliser, which realises energy transferred directly from source cells to target cells by the series ReSC converter. The ReSC converter eliminates the inrush current and improves the capacitors’ energy density to increase the balancing speed. Meanwhile, all the switches are controlled by a pair of complementary PWM signals at a fixed operational frequency without voltage monitors. Both simulation and experiment are used to verify the system feasibility and theoretical analysis of the proposed circuit. In the same experimental condition, the proposed series resonant circuit reduces the inrush current. It improves the energy density of capacitors three times compared with the pure series switched‐capacitor equaliser.
Numerical simulation of wind turbine wake based on extended k‐epsilon turbulence model coupling with actuator disc considering nacelle and tower
Authors: Li Ning , Liu Yongqian , Li Li , Chang Siyu , Han Shuang , Zhao Hao , Meng Hang
Published: February 2021

The Reynolds‐averaged Navier–Stokes (RANS) method coupling with the actuator disc model (ADM) is considered as a promising numerical simulation technology of wind turbine wake, and it is widely utilised in the aerodynamics of wind turbines and optimal layout of wind farms. The turbulence model is widely adopted, among the RANS‐based turbulence models. However, the turbulence model easily overestimates the turbulence viscosity in the wake, which results in fast recovery of wake velocity and failure in wake forecasting. In addition, ADM with the oversimplified geometrical structure ignores the effects of nacelle and tower on the wind turbine wake, which further lowers the accuracy of wake simulation. Therefore, the numerical simulation of wind turbine wake based on the extended turbulence model of EI Kasmi coupling with ADM considering nacelle and tower is proposed. Comparing the results of Marchwood Engineering Laboratories (MEL) ABL wind tunnel measurements and TNO wind tunnel experiments, it has been found that the proposed model improves the simulation effect for the near wake and has a certain contribution to the wake prediction accuracy overall.
Coordinated multiple HVDC modulation emergency control for enhancing power system frequency stability
Authors: Wang Tong , Xiang Yuwei , Li Congcong , Wang Zengping
Published: February 2021

High‐voltage direct current (HVDC) power modulation can effectively improve the system frequency stability after high power shortage fault disturbance. This study presents an emergency control method by coordinating the active powers of multiple HVDC lines for enhancing the frequency stability. Firstly, the system frequency response model with HVDC modulation is built, and then a simplified method for calculating the sensitivity of maximum frequency to HVDC modulation is proposed based on the first‐order differential method. Next, based on a functional relationship of the AC bus voltage and the actual HVDC modulation capacity, the methodology for calculating the HVDC real‐time modulation capacity is proposed. Finally, the coordinated multiple HVDC modulation emergency control model is established which aims to minimise the modulation cost considering the maximum frequency threshold. The proposed methodology has been tested in a real‐power system. The simulation results of different scenarios have verified its effectiveness in suppressing the rise of maximum frequency and enhancing frequency stability.
Recent developments of MPPT techniques for PV systems under partial shading conditions: a critical review and performance evaluation
Authors: Kermadi Mostefa , Salam Zainal , Eltamaly Ali M. , Ahmed Jubaer , Mekhilef Saad , Larbes Cherif , Berkouk El Madjid
Published: February 2021

This review covers global maximum power point tracking (GMPPT) methods for photovoltaic (PV) systems under partial shading conditions. Unlike the previous review works that primarily focused on soft computing and hybrid GMPPT, this study gives exclusive attention to the improvement achieved by the conventional MPPT (perturb and observe, hill climbing, and incremental conductance). The improved methods include the popular 0.8 × Voc model and, more recently, the skipping algorithms. In addition to providing qualitative descriptions of the available techniques, this work also attempts to provide a fair evaluation of GMPPT to determine their comparative performances. The competing algorithms, which are selected to represent every category (conventional and soft computing and hybrid MPPT), are benchmarked under carefully selected operating conditions and shading scenarios. The evaluation is focused on four main criteria: tracking accuracy, convergence time, length of voltage fluctuations, and transient efficiency during the search for the global maximum power point. The results obtained from this study can become a basis for researchers and designers to select the best MPPT technique for their respective applications.
Optimal recovery strategy of DERs integrated distribution network based on scheduling rationality
Authors: Wang Jun , Zheng Xiaodong , Tai Nengling , Liu Yu , Yang Zengli , Wang Jing , Tu Qi
Published: February 2021

In order to better schedule distributed energy resources (DERs) to improve the recovery ability of the distribution network, the optimal recovery strategy is proposed in this study. The strategy can be applied to speed up the recovery process and reduce the power shortage of shedding loads in the distribution network when a power outage occurs. The scheduling coefficient is defined to quantify the rationality of each scheduling resource. Based on this index, this study establishes an optimal scheduling model, which consists of three objectives. The non‐dominated sorting genetic algorithm‐II is applied to search this multi‐objective optimal recovery solution in this study. Then, the modified IEEE 39‐node system is used as the case study to verify the feasibility of the proposed model and the test results prove the effectiveness and efficiency of the proposed model.
Demystifying the use of ERA5‐land and machine learning for wind power forecasting
Authors: Marinšek Alexander , Bajt Gregor
Published: February 2021

Wind is a highly unstable renewable energy source. Accurate forecasting can mitigate the effects of wind inconsistency on the electric grid and help avoid investments in costly energy storage infrastructure. Basing the predictions on open‐source forecast models and climate data also makes them entirely free of charge. The present work studies the feasibility of using two machine learning (ML) models and one deep learning (DL) model, random forest (RF) regression, support vector regression (SVR), and long short‐term memory (LSTM) for short‐term wind power forecasting based on the publicly accessible ERA5‐Land dataset. For each forecast model, a selection of hyperparameters is first tuned, followed by determining the best performing input data structure using surrounding data grid points and increasing the time interval of data affecting a single prediction. Both the ML models and the DL model perform better than the baseline (BL) model when forecasting wind speed up to 24 hours ahead. However, a reduced forecast duration is needed to achieve satisfactory wind turbine (WT) power output forecast accuracy. Most notably, the RF is able to produce 3‐hour forecasts with the combined WT power output prediction error amounting to less than 10 % of the WT's nominal power.
Value of bifacial photovoltaics used with highly reflective ground materials on single‐axis trackers and fixed‐tilt systems: a Danish case study
Authors: Riedel‐Lyngskær Nicholas , Poulsen Peter Behrensdorff , Jakobsen Michael Linde , Nørgaard Per , Vedde Jan
Published: February 2021

The energy produced by bifacial photovoltaic (PV) arrays can be augmented via albedo enhancements. However, the value of the additional energy must outweigh the costs for such modifications to be economically viable. In this work, the electrical performance and economic value of six 13 kWp crystalline‐silicon (c‐Si) PV arrays with distinct configurations are evaluated. The system designs include horizontal single axis trackers (HSAT) and 25° fixed‐tilt structures, monofacial and bifacial PV panels, and low and high ground albedo. The value of the system designs is assessed using onsite electrical measurements and spot prices from the Nord Pool electricity market. We find that HSAT systems increase the annual value factor (VF) by 4% and decrease levelized cost of energy (LCOE) by 3.5 EUR/MWh relative to fixed‐tilt systems. The use of bifacial panels can increase the VF by 1% and decrease LCOE by 4.0 EUR/MWh. However, a negligible VF increase and modest LCOE decrease was found in systems with bifacial panels and ground albedo enhancements. Although our results show that albedo enhancements result in lower LCOE than designs without, the uncertainty in upfront and ongoing costs of altering the ground in utility‐scale PV parks makes the solution presently unadvisable.
Robust fault detection approach for wind farms considering missing data tolerance and recovery
Authors: Zhang Yuchen , Su Xiangjing , Meng Ke , Dong Zhao Yang
Published: February 2021

The advancement in sensing technologies and infrastructure allows real‐time condition monitoring on wind turbines (WTs), which helps improve the power generation efficiency, lower the maintenance costs of wind farms (WFs). Practically, the real‐time measurements could be unavailable at the Supervisory Control and Data Acquisition end due to unintended events such as sensor faults and communication loss, which significantly depreciates the condition monitoring and fault detection performance. Aiming to mitigate the missing data impact on data‐driven WF applications, this study develops a robust anomaly detection approach for WT fault detection using a denoising variational autoencoder. In presence of missing measurements, the proposed approach can not only sustain high fault detection performance but also recover the missing data as an auxiliary function. The proposed approach is tested on a realistic offshore WF and compared with other autoencoder variants and traditional anomaly detection methods. The testing results verify the outstanding robustness of the proposed approach against missing data events and demonstrate its great potential in missing data recovery.
Optimal placement of phase‐reconfiguration devices in low‐voltage distribution network with residential PV generation
Authors: Liu Bin , Meng Ke , Dong Zhao Yang , Wong Peter K.C. , Wei Wei
Published: February 2021

As residential PV generation penetrates in the low‐voltage distribution network (LVDN), the unbalance issue may be intensified due to the asymmetry of generations/loads in different phases. Phase‐reconfiguration device (PRD), which can reconfigure connected phases of residential customers, provides an effective method to address this issue. Noting that although the benefit brought by PRDs can vary if they are placed at different locations in the network, little literature has been reported on this topic. To bridge the research gap, this paper presents a novel method to optimally place PRDs in an LVDN aiming at minimizing the power unbalance running through the distribution transformer. The problem considers both installation, operational constraints, and boils down to a challenging mixed‐integer non‐convex programming problem, which is then reformulated as an efficient solvable mixed‐integer linear programming problem. Moreover, operational constraints are relaxed with slack variables penalized in the objective function, which makes sure a feasible solution is always available without or with minimal operational violations. Case studies based on a modified IEEE system and a practical system in Australia demonstrate that an efficient strategy can be provided to address the unbalance issue while improving the network's power supply qualities.
Validating grid‐forming capabilities of hybrid power park technologies in future OFTO networks
Authors: Dyśko Adam , Ierna Richard , Yu Mengran , Egea‐Àlvarez Agustí , Avras Andreas , Li Can , Horley Mark , Booth Campbell , Urdal Helge
Published: February 2021

In recent years, there has been considerable interest in convertor‐based generating solutions which to a greater or lesser extent mimic the behaviour of synchronous machines, thus overcoming many of the disadvantages of the existing technologies which are potentially destabilising at high penetration. Such solutions are frequently referred to as grid‐forming convertors (GFCs). This study focuses on the application of GFC technologies in offshore windfarms, where installation, maintenance and/or modification of any offshore equipment is very expensive and carries greater commercial risks, requiring extensive testing and confidence building prior to deployment in real applications. This is time consuming and particularly significant for GB and where there are large quantities of offshore generation. Onshore solutions to stability are therefore desirable for off‐shore transmission owners (OFTOs), especially, if they could be applied by retrofitting to existing conventional converter plant. Consequently, this study proposes and investigates the performance of hybrid solutions for offshore networks where the conventional STATCOM onshore unit is replaced by alternative options such as synchronous compensator and virtual synchronous machine converter of similar (or appropriate) rating with the aim of achieving grid‐forming capability. A laboratory‐scale implementation of the proposed control algorithm is also presented with selected validation test results.
State‐of‐the‐art and comprehensive study of renewable energy sources based microgrid with single‐phase self‐excited induction generator
Authors: Kalla Ujjwal Kumar , Singh Bhim , Kumar Praveen , Agarwal Kusum Lata , Murthy S.S.
Published: February 2021

This study presents a comprehensive study of microgrid systems using a single‐phase self‐excited induction generator (SEIG) using renewable energy sources (RESs) and their integration with other energy sources. It investigates on the use of a single‐phase two‐winding SEIG for off‐grid single‐phase power generation from different RESs. Various solid‐state controllers are implemented for each configuration. This is the first time, such an attempt is made to use a specially designed SEIG for sustainable energy application to feed single‐phase loads vastly prevalent in isolated and distant locations in accessible to the grid. This work has great importance due to the non‐availability of the power in remote regions in developing countries. Moreover, there is a need to use local RESs such as bio, hydro, wind in combination with the solar energy. The present global need to generate pollution free electricity makes this work quite important. Thus, this study presents a comprehensive review of different modes of SEIG using RESs for single‐phase power generation realising the microgrid feeding a combination of practical loads with viable and successful controllers to ensure desired quality power across loads.
An algorithm to locate the centers of baryon acoustic oscillations
Authors: Brown Z. , Mishtaku G. , Demina R. , Liu Y. , Popik C.
Published: February 2021

Context.The cosmic structure formed from baryon acoustic oscillations (BAO) in the early universe is imprinted in the galaxy distribution observable in large-scale surveys and is used as a standard ruler in contemporary cosmology. Typically, BAOs are detected as a preferential length scale in two-point statistics, which gives little information about the location of the BAO structures in real space.

Aims.The aim of the algorithm described in this paper is to find probable centers of BAOs in the cosmic matter distribution.

Methods.The algorithm convolves the three-dimensional distribution of matter density with a spherical shell kernel of variable radius placed at different locations. The locations that correspond to the highest values of the convolution correspond to the probable centers of BAOs. This method is realized in an open-source, computationally efficient algorithm.

Results.We describe the algorithm and present the results of applying it to the SDSS DR9 CMASS survey and associated mock catalogs.

Conclusions.A detailed performance study demonstrates the ability of the algorithm to locate BAO centers and in doing so presents a novel detection of the BAO scale in galaxy surveys.
Magnetic properties on the boundary of an evolving pore
Authors: García-Rivas M. , Jurčák J. , Bello González N.
Published: February 2021

Context. Analyses of the magnetic properties on umbrae boundaries have led to the Jurčák criterion, which states that umbra-penumbra boundaries in stable sunspots are equally defined by a constant value of the vertical magnetic field, Bvercrit, and by a 50% continuum intensity of the quiet Sun, IQS. Umbrae with vertical magnetic fields stronger than Bvercrit are stable, whereas umbrae with vertical magnetic fields weaker than Bvercrit are unstable and prone to vanishing.

Aims. We aim to investigate the existence of a critical value of the vertical magnetic field on a pore boundary and its role in the evolution of the magnetic structure.

Methods. We analysed SDO/HMI vector field maps corrected for scattered light and with a temporal cadence of 12 min during a 26.5-hour period. A continuum intensity threshold (Ic  =  0.55 IQS) is used to define the pore boundary and we study the temporal evolution of the magnetic properties there.

Results. We observe well-defined stages in the pore evolution: (1) during the initial formation phase, total magnetic field strength (B) and vertical magnetic field (Bver) increase to their maximum values of ∼1920 G and ∼1730 G, respectively; (2) then the pore reaches a stable phase; (3) in a second formation phase, the pore undergoes a rapid growth in terms of size, along with a decrease in B and Bver on its boundary. In the newly formed area of the pore, Bver remains mostly below 1731 G and B remains everywhere below 1921 G; (4) ultimately, pore decay starts. We find overall that pore areas with Bver < 1731 G, or equivalently B < 1921 G, disintegrate faster than regions that fulfil this criteria.

Conclusions. We find that the most stable regions of the pore, similarly to the case of umbral boundaries, are defined by a critical value of the vertical component of the magnetic field that is comparable to that found in stable sunspots. In addition, in this case study, the same pore areas can be similarly well-defined by a critical value of the total magnetic field strength.
On the influence of non-individual binaural cues and the impact of level normalization on auditory distance estimation of nearby sound sources
Authors: Arend Johannes M. , Liesefeld Heinrich R. , Pörschmann Christoph
Published: February 2021

Nearby sound sources provide distinct binaural cues, mainly in the form of interaural level differences, which vary with respect to distance and azimuth. However, there is a long-standing controversy regarding whether humans can actually utilize binaural cues for distance estimation of nearby sources. Therefore, we conducted three experiments using non-individual binaural synthesis. In Experiment 1, subjects had to estimate the relative distance of loudness-normalized and non-normalized nearby sources in static and dynamic binaural rendering in a multi-stimulus comparison task under anechoic conditions. Loudness normalization was used as a plausible method to compensate for noticeable intensity differences between stimuli. With the employed loudness normalization, nominal distance did not significantly affect distance ratings for most conditions despite the presence of non-individual binaural distance cues. In Experiment 2, subjects had to judge the relative distance between loudness-normalized sources in dynamic binaural rendering in a forced-choice task. Below chance performance in this more sensitive task revealed that the employed loudness normalization strongly affected distance estimation. As this finding indicated a general issue with loudness normalization for studies on relative distance estimation, Experiment 3 directly tested the validity of loudness normalization and a frequently used amplitude normalization. Results showed that both normalization methods lead to remaining (incorrect) intensity cues, which subjects most likely used for relative distance estimation. The experiments revealed that both examined normalization methods have consequential drawbacks. These drawbacks might in parts explain conflicting findings regarding the effectiveness of binaural cues for relative distance estimation in the literature.
Aspects géotechniques et énergétiques des géostructures thermoactives : application à un cas d’étude réel
Authors: Di Donna Alice , Emeriault Fabrice , Demongodin Lionel , Gobichon Jean-François
Published: February 2021

La technologie des géostructures énergétiques consiste à adapter les structures géotechniques, comme les pieux de fondation, les parois moulées ou les tunnels, afin de les transformer en échangeurs de chaleur avec le sol. De fait, ce sont des systèmes géothermiques à basse enthalpie, avec le gros avantage de réduire les coûts initiaux d’installation grâce à l’utilisation des structures géotechniques qui seraient réalisées dans tous les cas. Les échanges de chaleur entre la géostructure et le sol induisent des variations de température cycliques sur les deux, et l’efficacité du système doit répondre à la fois à des critères énergétiques (bonne production de chaleur ou de froid) et géotechniques-structurels (analyse des contraintes et déformations thermiques du sol et de la structure en béton), qui dépendent fortement des conditions locales du site accueillant la construction. Il s’agit donc d’un système complexe avec un comportement dépendant de différents phénomènes thermiques, hydrauliques et mécaniques, éventuellement couplés, à la fois dans le sol et dans la structure. Dans un premier temps, une vue globale des différents aspects qui jouent un rôle important dans le comportement géotechnique et énergétique des géostructures thermoactives est présentée, depuis l’échelle de l’élément de sol jusqu’à celle de l’ouvrage. Ensuite, un cas récent d’application de la technologie aux parois moulées de la gare Jules Ferry de Rennes, en France, est décrit et analysé. D’abord, les premières mesures des Tests de Réponse Thermique Opérationnels (T.R.T.O.) réalisés sur le site d’étude sont discutées. Ensuite, l’analyse porte sur les résultats de la modélisation thermo-hydraulique (TH) par éléments finis du cas d’étude et la comparaison avec les mesures in situ. Le modèle numérique permet de reproduire correctement les données expérimentales quand un écoulement souterrain est pris en compte. Les résultats montrent une bonne efficacité énergétique de la technologie qui se confirme très prometteuse.
Central Odontogenic Fibroma: characteristics and management
Authors: Bennabi Sabrina , Lesclous Philippe , Cloitre Alexandra
Published: February 2021

Introduction: Central Odontogenic Fibroma (COF) is a rare benign odontogenic tumour of the jaws. Until its recent change in classification by the WHO in 2017, this entity has gone without an agreed upon definition for many years. For this reason, COF would remain largely unknown to practitioners. Corpus: The pedagogical objectives of this article are, through a systematic review of the literature using the PRISMA methodology, to list the epidemiological, aetiological, clinical, radiological, histological, therapeutic and prognostic characteristics of COF. All the data collected made it possible to establish a COF management summary for practitioners in order to optimize it. Conclusion: Based on the 135 cases listed, it appears that surgical enucleation is the treatment of choice for COF. The recurrence rate is low and malignant transformation has never been reported. However, regular clinical and radiological follow-up of patients over several years seems to be a justified precaution.
Status of renewable energy in Cameroon
Authors: Kidmo Dieudonné Kaoga , Deli Kodji , Bogno Bachirou
Published: February 2021

Globally, the continuous increase of energy consumption coupled with the depletion of the limited fossil fuel sources and their negative impacts on the environment, has shifted focus towards renewables for a sustainable development. For the last fifteen years, the world has enjoyed renewables generation capacity increases in a double-digit Terawatt-hours range. Although renewables consumption is fast developing in Asia Pacific, Europe and North America, significant coordination efforts are required among stakeholders in sub-Saharan Africans countries such as Cameroon. In 2018, the total final energy consumption in Cameroon was 7.41 Mtoe, 74.22% of which was from biomass, 18.48% from fossil fuels and 7.30% from electricity. Furthermore, 6977 GWh of electricity was produced, 78.29% of which from the major electricity operator (ENEO S.A. Cameroon) and 21.71% from independent producers (GLOBELEQ, ALTAAQA Sinohydro China and AGGREKO). More than three quarter of electricity produced were consumed by industry (57.04%) and residential (20.74%) sectors. The country's installed electricity generation capacity rose to 1402 MW, 56.15% of which was from hydropower, 43.84% from fossil fuels (17.55% from natural gas and 26.29% from oil) and 0.01% from solar photovoltaic. The promotion of renewable energy is an important part of Cameroon's plan to increase energy security and provide job opportunities to the country. Yet, the lack of proactive and long-term renewable energy policy and laws, in addition to less attention paid to renewable energy training and research, financing mechanisms, and unaffordable costs of renewable energy technologies to the poor population are amongst present issues hindering the development of renewable energy in the country. Hence, this paper aims to highlight the present status of renewable energy exploitation and development in Cameroon.