bluuebunny/crossref_metadata_2025 huggingface dataset:
Optimal reactive power planning in power transmission system considering FACTS devices and implementing hybrid optimisation approach
Authors: Karmakar Nihar , Bhattacharyya Biplab
Published: February 2021

This study introduces a techno‐economic planning strategy of reactive power (VAr) in power transmission systems. This planning strategy primarily has been focused on reactive power planning (RPP) through operating cost minimisation ensuring cost‐oriented system security. The objective function (operating cost) is blended with four different components viz. cost due to real power loss, VAr generation cost, additional VAr compensation devices cost and line charging cost. FACTS (flexible AC transmission system) devices are installed at weak positions through different echelons to improve the system voltage stability. The authors also implemented the probabilistic hybridisation of crow search algorithm and JAYA to find out the optimal set of controlling parameters related to VAr. Finally, a sharp and minute analysis of the results has been done to validate the proposed strategy under multi‐loading conditions. To understand the efficiency and efficacy the code profiling and simulation has been rendered on IEEE 30 bus and UPSEB 75 bus test system.
Target object detection using chicken social‐based deep belief network with hyperspectral imagery
Authors: Shibi Sherin , Rajagopal Gayathri
Published: February 2021

Target object detection is an important research direction in the area of hyperspectral imaging (HSI) as it aims to detect the anomalies or objects in HSI. Some of the existing target object detection methods are merely suitable for HSI with low resolution as they failed to apply directly in the high‐resolution HSI. Therefore, an effective target detection method named chicken social‐based deep belief network (CS‐based DBN) is proposed to achieve an automatic target object detection framework in the high‐resolution HSI. The proposed CS‐based DBN is developed by integrating the chicken swarm optimisation with the social ski‐driver algorithm. The optimal solution for detecting the target object is revealed through the fitness function, which accepts the minimal error value as the best solution. Moreover, the weights of the DBN classifier are optimally trained based on the proposed algorithm to render an accurate and optimal solution in detecting the target objects. The proposed CS‐based DBN obtained better performance through the facility of stochastic exploration in search space. Moreover, the results achieved using the proposed model in terms of accuracy, specificity, and sensitivity are 0.8950, 0.8940, and 0.9, respectively.
PReLU and edge‐aware filter‐based image denoiser using convolutional neural network
Authors: Thakur Rini Smita , Yadav Ram Narayan , Gupta Lalita
Published: February 2021

Convolutional neural networks (CNNs) based on the discriminative learning model have been widely used for image denoising. In this study, a feed‐forward denoising CNN (DnCNN) with a parametric rectified linear unit (PReLU) is used to improve the denoising performance. PReLU enhances the model fitting of the DnCNN network without affecting computational cost. This network learns the leaky parameter of negative inputs in an activation function and therefore finds a proper slope in a negative direction. The proposed denoising network is based on residual learning, which comprises repeated convolutional and PReLU units along with batch normalisation. Residual learning with batch normalisation accelerates the network training, which can be used for blind Gaussian denoising. In this network, feature maps are processed by principal component analysis and transferred to subsequent convolution layers. An adaptive bilateral filter further processes the output image of the proposed CNN for image smoothening and sharpening. The mean and variance of the Gaussian kernel of adaptive filter vary from pixel to pixel. The performance of this network is analysed on BSD‐68 and Set‐12 datasets, and it exhibits an improvement in peak signal‐to‐noise ratio and structural similarity index metric and visual representation over other state‐of‐the‐art methods.
Bézier curve‐based trajectory planning for autonomous vehicles with collision avoidance
Authors: Zheng Ling , Zeng Pengyun , Yang Wei , Li Yinong , Zhan Zhenfei
Published: February 2021

This study proposes an effective trajectory planning algorithm based on the quartic Bézier curve and dangerous potential field for automatic vehicles. To generate collision‐free trajectories, potential field functions are introduced to evaluate the collision risk of path candidates. However, many studies on artificial potential field approaches primarily focus on static and straight roads, and attach less importance to more complex driving scenarios, such as curving roads. In this study, a novel method based on the Frenet coordinate system is proposed to address such limitations. Moreover, to balance the driving comfortability and the driving safety of the path candidate, the path‐planning problem is converted to an optimisation problem, and sequential quadratic programming algorithm is employed to tackle this task. Another merit of this algorithm is the curvature of the generated path is continuous even at the joints of adjacent sub‐trajectories by utilising several specific properties of the Bézier curve. Furthermore, to execute the generated trajectory, a framework of velocity generation is proposed while vehicle dynamic constraints are considered. Some typical traffic scenarios, including lane‐changing, lane‐keeping, and collision avoidance have been designed to verify the performance of the proposed algorithm, and simulations demonstrate the validity of this method.
Enhanced resonant two‐degree of freedom‐based PID controller for grid‐integrated PV power generating system
Authors: Pal Kanwar , Kumar Shailendra , Singh Bhim , Kandpal Tara C.
Published: February 2021

The contribution of power because of the nonconventional energy sources is enhancing day by day. This gives rise to power converter connected to the grid for an integration and to utilize the nonconventional energy sources economically and efficiently. However, this causes the distortion in the grid voltages and currents. All advanced high precision operating machines and measuring instruments are sensitive to the harmonics of the grid voltages. Therefore, this work illustrates an improved control to supress the grid voltage and current harmonics caused by an integration of non‐conventional energy source and nonlinear loads. An enhanced resonant two‐degree of freedom proportional–integral–derivative (ER‐2‐DOF‐PID) controller is used to extract fundamental components from load currents. It uses a resonant controller in shunt with PI controller to suppress the multi‐order harmonics and steady state error. A DC‐offset is used in parallel of this combination to suppress the sub‐order harmonics. To suppress the peak overshoot during the load transients and insolation changes, a 2‐DOF‐PID controller is used. The presented control is investigated by developing its model in MATLAB environment and this is validated on a prototype developed in the laboratory. The controller is modelled and investigated for stability analysis using a Bode mathematical tool..
Electric freight trains as distributed energy resources supporting frequency stability in power systems
Authors: Wasilewski Jacek , Skwarski Mateusz
Published: February 2021

The generation structure in the European power systems is continuously changing towards an increasing share of non‐synchronous energy sources. This leads to significant challenges in maintaining frequency stability due to declining system inertia. In this study, a novel concept of demand response very fast active power control (DR VFAPC) capability using in a direct way the braking energy in electric trainsets being in motion is presented. In order to assess the potential to ensure DR VFAPC capability by freight railway carriers and examine the impact of such service on frequency dynamics, a simplified mathematical model of Polish power system representing the frequency regulation process has been developed. The impact of basic characteristics of the freight train transport, as well as the selected power system parameters on the DR VFAPC operation, has been studied. In conclusion, current technical constraints of implementing the presented idea and future works have been discussed.
Adaptive clustering‐based hierarchical layout optimisation for large‐scale integrated energy systems
Authors: Guo Hui , Shi Tianling , Wang Fei , Zhang Lijun , Lin Zhengyu
Published: February 2021

Different energy systems are generally planned and operated independently, which result in the low energy utilisation, weak self‐healing ability and low system reliability. Therefore, an adaptive clustering‐based hierarchical layout optimisation method is proposed for a large‐scale integrated energy system, considering energy balance, transmission losses and construction costs. First, an adaptive clustering partition method based on energy balance and load moments is proposed to determine the optimal location of energy hubs and to allocate each distributed generation and load to different energy hubs, forming multiple regional integrated energy systems adaptively. Then, the proposed hierarchical layout optimisation model is formulated as to find the modified minimum spanning tree of the regional integrated energy system and multi‐regional integrated energy systems, respectively, to construct an economical and reliable interconnection network. Finally, the effectiveness of the optimisation model and strategy is verified by simulations.
Evaluation of power supply capability and quality for traction power supply system considering the access of distributed generations
Authors: Feng Ding , Zhu Hengkai , Sun Xiaojun , Lin Sheng
Published: February 2021

The access of distributed generations (DGs) in the traction power supply system (TPSS) can not only make use of the renewable energy near the railway route, but also improve the condition of weak external power supply. In order to quantify the effect when DGs access TPSS, this study proposes a method for evaluating the power supply capability and quality of TPSS which considers the access of DGs. First, the method fully considers the randomness and uncertainty of the power provided by DGs and that consumed by electrical locomotives. A comprehensive model of TPSS with the access of DGs is built by means of the stochastic model, and then the index system for evaluating the power supply capability and quality of TPSS is formulated. Finally, the Monte Carlo simulation is applied to calculate the probabilistic load flow to obtain the evaluation indices. The proposed method is verified by simulating a typical TPSS in a remote mountain area. The results show that the method can quantify the power supply capability and quality of the system after the access of DGs. It can provide an intuitive conception of the power supply condition for design and operation personnel.
DC voltage control for MMC‐based railway power supply integrated with renewable generation
Authors: Sun Peiliang , Li Kang , Li Yongfei , Zhang Li
Published: February 2021

The full controllable electronic device based railway feeder station offers better power quality and more flexible configurations than conventional transformer based stations. This study investigates a modular multilevel converter (MMC)‐based static frequency converter station with renewable energy access. Wind power generation is coupled into the station via DC link of the back to back converter. The dynamic single‐phase traction load and intermittent renewable generation bring double frequency oscillation and large deviation problems to the DC link voltage. Special design considerations and control schemes are proposed for the MMC to stabilise DC link voltage by controlling the total number of total inserted modules. The proposed control scheme resolves the voltage oscillation issue caused by single‐phase load and reduces the DC link voltage deviation under 10 MW step change. A series of device‐based simulations validate the control scheme which realises a reliable coupling interface for connecting the renewable generation to the DC bus.
Design and evaluation of micro energy network considering P2G‐based storage system using two‐stage stochastic programming
Authors: Liu Wei‐Kang , Wang Dan , Liu Bo , Yu Xiao‐Dan , Jia Hong‐Jie , Wang Wei‐Liang , Song Yunchao
Published: February 2021

Due to the interaction between the planning and operation of micro energy network, considering the operation optimization can better play the role of micro energy network. But due to the influence of various uncertainties, the deterministic programming solution may be sub‐optimal. In this context, the two‐stage stochastic programming of micro energy network is of great significance. In this paper, from the perspective of electric energy, the closely related P2G, storage system and fuel cell are modeled as a whole, so that the model is simplified to a certain extent. Stochastic scenarios that considers multiple uncertain factors are constructed considering the correlation between electricity demand, wind speed and solar radiation intensity. And a two‐stage stochastic programming model of micro energy network is established. Through the case study, the influence of P2GSS on micro energy network planning under uncertainty environment as well as the difference between stochastic programming and deterministic programming of micro energy network is analyzed. The simulation results show that P2GSS can reduce the economic cost and CO2 emission of micro energy network planning solution. Through the comparison of different planning schemes, it can provides a reference for the planning and construction of the micro‐energy network.
Adaptive fault‐tolerant control of variable pitch system of wind power generator based on clustering‐type fuzzy neural network
Authors: Wang Hongwei , Zhang Qian
Published: February 2021

In view of the faults of the doubly‐fed wind power generator system, the health situations of the system are described by the health factor functions. On this basis, the model reference adaptive fault‐tolerant control method based on clustering‐type fuzzy neural network is proposed. The proposed method can solve the adaptive control issues of wind power generator system with actuator faults, external interference and model uncertainties. The stability and the tracking performance of the system are guaranteed by using Lyapunov stability theorem. Finally, the effectiveness of the proposed method is proved by the fault‐tolerant control of the pitch system of the doubly‐fed wind power generator.
Low carbon oriented power‐to‐gas station and integrated energy system planning with ancillary service provision and wind power integration
Authors: Wang Guibin , Yang Yanrong , Wang Huaizhi , Zhou Bin , Qiu Jing , Zhang Xian
Published: February 2021

This study proposes an integrated energy system (IES) model consisting of natural gas system, electricity system, and power‐to‐gas stations (P2GSes), and then uses a centralised coordinated method to plan the IES. P2GSes can convert excessive renewable energy to natural gas and provide a promising approach to large‐scale energy storage and long‐distance energy transmission in the form of gas. However, considering the carbon emission of natural gas utilisation and high cost of P2G process, new embedded P2GSes will pose a threat to the economic and environment‐friendly operation for the existing integrated energy system. Therefore, a more comprehensive P2G revenue objective, which is comprised of a secondary reserve service model, wind power integration model and carbon trading market participating model, is proposed in this study. The potential of P2GSes to provide the capacity of absorbing wind power and carbon reduction is innovatively and thoroughly evaluated in this study. The effectiveness of the proposed model is verified on an IES containing a coupled 24‐bus electricity and 20‐bus natural gas system. Simulation results show that it is optimal for the P2GSes revenue model to possess both capacities of absorbing wind power and converting the acquired power into natural gas as much as possible.
Passive method for islanding detection using variational mode decomposition
Authors: Thakur Amit Kumar , Singh Shiv P. , Shukla Devesh , Singh Sunil Kumar
Published: February 2021

As the distributed energy resources penetration level increases, the distribution system operator faces a challenging task of unintentional islanding detection. Besides islanding detection schemes are affected due to the presence of different types of distributed generation systems and smart inverters. The presence of these devices hinders the capability of islanding detection schemes. To mitigate these issues, this study proposes a practical methodology of variational mode decomposition‐based energy index for islanding detection. It decomposes the sampled voltage signal at the point of common coupling into four modes/intrinsic mode functions (IMFs). Among these modes/IMFs, the energy index of mode two has been utilised to detect the islanding. It is an entirely intrinsic, adaptive, and variational method. The five bus and practical distribution systems have been modelled using PSCAD/EMTDC software while considering various components' practical aspects. The technique has been tested for the mixed type of distributed generation and various transient events. The test results reveal that the proposed method is capable of discriminating the islanding event from other disturbances.
Fuzzy logic controller for solar power smoothing based on controlled battery energy storage and varying low pass filter
Authors: Atif Ammar , Khalid Muhammad
Published: February 2021

Matching of the colossal energy demand with carbon‐free resources originates a global challenge to produce and innovate advanced energy technologies that generate clean and friendly energy supplies without threatening our environment. Nevertheless, with the increase in the penetration from renewable energy resources like solar and wind farms many technical issues are presented typically; power stability, power quality, and frequency fluctuations. The aforementioned problems stem from the intermittent nature of renewable resources which makes the generated power unpredictable and requires controlling and smoothing before dispatching. Conventionally low pass filter (LPF) is used with a controlled energy storage system to smoothen the fluctuated power due to its simplicity, but a delay problem increases with higher values of the filtering the time constant. This study suggests a smoothing controller‐based fuzzy logic that determines the value of the filtering time constant based on the present solar power ramp rate to avoid the battery overworking, which results in the predetermined configuration of the LPF. The presented simulation results prove the smoothing performance of the proposed controller and compare its performance to the LPF during clear, normal, and cloudy irradiance profiles.
Impact of inverter digital time delay on the harmonic characteristics of grid‐connected large‐scale photovoltaic system
Authors: Liu Jinhong , Molinas Marta
Published: February 2021

The digitally controlled inverter is widely applied to the photovoltaic (PV) plant, however, the effects of inverter digital time delay on the harmonic characteristic of PV system which directly influences the power quality and even the stability of the system, have not been investigated yet. This study investigates the harmonic characteristic of a grid‐connected large‐scale PV system based on the equivalent Norton model of the system with considering the digital time delay of the inverter. According to the system equivalent model, the series harmonic resonance circuit and the parallel harmonic resonance circuit are divided to study the impacts of digital time delay in the cases of the inverter output harmonic exist and the grid voltage harmonic exit, respectively. Then, the harmonic resonance mechanism of a grid‐connected large‐scale PV system is studied and the effects of digital time delay on the harmonic characteristic of system output current is quantitatively analysed by defining the harmonic magnification coefficient. It turns out that frequency and magnitude of harmonic magnification points in the grid‐side current of the system are increased as the digital time delay increases. Reference to the actual 20 MWp grid‐connected PV system, a simulation model is built to verify the theoretical analysis results.
Sub‐synchronous oscillations in wind farms – an overview study of mechanisms and damping methods
Authors: Shi Tong , Nayanasiri Dulika , (Ryan) Li Yunwei
Published: February 2021

Sub‐synchronous oscillation (SSO) causes significant damage and performance degradation in wind farms (WFs). The root causes and mitigation methods of SSO have been identified as a result of many studies. An overview that analysed and summarised those findings in different perspectives helps optimise the existing solutions and to find alternative approaches to mitigate SSO. Therefore, a comprehensive overview of the SSO analysing techniques, mechanisms, and mitigation strategies are presented in this study. This overview is focused on the WFs based on type 3 and 4 wind turbine generators and the WFs connected to high‐voltage DC transmission systems. The dominant SSO modes in each application have been presented along with the identified root cause, influencing factors, and the mitigation methods. Besides that, a comprehensive comparison between the existing mitigation strategies is presented to identify the alternative approaches and improvements. The identified improved methods are presented along with the time and frequency domain simulation results to validate their applicability. Finally, an insight into the future direction of this research is presented along with the conclusions.
Impact of the high share of converter‐interfaced generation on electromechanical oscillations in Continental Europe power system
Authors: Busarello Luigi , Musca Rossano
Published: February 2021

This study investigates the effects of converter‐interfaced generation integration on the dynamic response of the power system of Continental Europe. The system is analysed with a large‐scale dynamic model of the entire synchronous area, considering different instantaneous integration percentages of converter‐interfaced generation across the system. The study focuses on the reduction of the overall available kinetic energy and the impact on frequency dynamics and system oscillations. The dynamic model of the system originally provided by ENTSO‐E is further developed according to a specific methodology, replacing a determined amount of synchronous generation and introducing a corresponding amount of converter‐controlled current sources. The reference incident of a generation loss in Western Europe specified by ENTSO‐E is considered in the analysis. The results of time‐domain simulations and modal analysis show how the integration of non‐synchronous generation affects the frequency dynamics of Western, Central and Eastern Europe, bringing to attention some relevant effects of the spatial distribution of different generation sources within an extensive system as the Continental Europe synchronous area.
Interval–stochastic optimisation for transactive energy management in energy hubs
Authors: Alipour Manijeh , Abapour Mehdi , Tohidi Sajjad
Published: February 2021

With the growing penetration of distributed energy resources and energy hubs, the transactive energy market appears as a modern power market that facilitates coordinated operation and end‐to‐end energy trading. An energy hub can actively participate in the day‐ahead and real‐time markets for fulfilling various goals. This study proposes an interval–stochastic optimisation model based upon the transactive energy methodology for the scheduling of energy hubs in coupled electrical and thermal systems. Transactive energy technology is employed for the energy exchange management among the hub, consumers and the power grid. In the proposed model, the day‐ahead stage's uncertainties are modelled by using interval optimisation to avoid stochastic programming challenges in problems with lots of uncertainties. Further, the stochastic optimisation is employed in the real‐time stage as stochastic programming challenges will be conducted by updating the forecasts. By envisaging the uncertainties quiddity and the most of technical constraints of a hub, the real‐life situation is created. In addition, most of linearised constraints are applied to achieve reliable outcomes in a shorter time. Numerical simulations confirm the effectiveness and applicability of the proposed model.
Output power fluctuations of distributed photovoltaic systems across an isolated power system: insights from high‐resolution data
Authors: Moghbel Moayed , Glenister Simon , Shoeb Md Asaduzzaman , Edwards David , Calais Martina , Shahnia Farhad , Carter Craig , Stephens David , Jones Luke , Trinkl Pierce
Published: February 2021

Deployment of distributed energy resources has rapidly increased during the last few years. The uptake of renewable energy and especially photovoltaic (PV) systems are of interest to utilities in remote and rural areas where the use of conventional power generation is costly. Investigating the effects of such PV systems on isolated power systems at different penetration levels is a relevant research topic. This study reports on the data acquisition system deployed in a remote town in Western Australia and presents some of the findings and observations extracted from the captured real data. It highlights the maximum PV output variations and investigates the underlying factors. The impact of the PV systems on the voltage across the network is also analysed in this study. The studies show that inverter tripping events have led to larger PV output variations in shorter intervals while the cloud movements have contributed to variations in longer intervals.
Takagi–Sugeno fuzzy sampled‐data model‐based less conservative stability criterion for a Francis hydropower unit's governing system
Authors: Ma Teng , Wang Bin , Zhang Zhe , Ai Bo
Published: February 2021

In this study, the stability analysis and controller design of a hydropower unit's governing system (HUGS) were studied based on a Takagi–Sugeno (T–S) fuzzy model and constant sampled‐data control. First, according to the T–S fuzzy theory, the non‐linear Francis hydro‐turbine governing system under rigid water hammer is linearised and then the approximate linear system was obtained. Second, a fuzzy sampled‐data controller was designed in the case of periodic sampling, and the closed‐loop sampling system was discretised. After constructing the Lyapunov function and using the forward difference method, the stabilisation condition was given with less conservatism in a symmetrical linear matrix inequality form. Finally, the numerical simulation results showed that under four different sampling periods, the HUGS can quickly achieve stability and that it has different stability performance. In addition, the superiority of the controller was verified in comparison with traditional proportional–integral–derivative control and fuzzy control techniques.
Zero bus load flow method for the integration of renewable DGs by mixed‐discrete particle swarm optimisation‐based fuzzy max–min approach
Authors: Barik Soumyabrata , Das Debapriya , Bansal Ramesh C.
Published: February 2021

This study proposes an approach to determine the optimal placement and sizing of renewable distributed generations (DGs) and shunt capacitor in the distribution network (DN) with a pre‐defined energy contract strategy with the main grid by using fuzzy integrated mixed‐discrete particle swarm optimisation (MDPSO) based method. The proposed pre‐defined contract strategies are implemented in this study using the modified Newton–Raphson (NR) load flow method with the concept of the zero bus. The modifications in the Jacobian matrix in the NR load flow method is developed. MDPSO method is adopted to take care of both the continuous and the discrete variables, to determine the proper locations and the sizes of renewable DGs and shunt capacitor by reducing the active power loss, improving the voltage profile, and reducing the annual costs of the DGs. The multi‐objective optimisation is solved by using the fuzzy max–min‐based technique. The proposed method of DG placement is tested on 69 bus DN for three different scenarios. The results obtained from the proposed multi‐objective method are also compared with the weighted sum approach for different combinations.
Double‐stage grid‐integrated SPV system under weak distribution grid
Authors: Kumar Abhishek , Jain Rashmi , Singh Bhim , Kewat Seema
Published: February 2021

This study presents a three‐phase four‐wire grid‐tied solar photovoltaic (SPV) energy conversion system with a reduced ordered generalised integrator frequency locked loop (ROGI‐FLL) based control for the extraction of fundamental grid voltages. The reference grid currents are extracted by using the proposed filtered‐s least mean square (FsLMS) current control for voltage source converter (VSC) switching. This VSC is capable of performing multifunctions like compensating harmonics of non‐linear loads, the grid currents balancing, mitigation of neutral current and it stabilises the DC link voltage. The SPV array generates the active power for feeding loads and to the grid. Matlab environment is used to develop the model of the proposed scheme and simulation results of the system are validated with test results on a developed prototype. Test results have shown the good responses at different environmental conditions. Moreover, a comparative study is performed with ROGI‐FLL controller and other controls at the grid voltages unbalancing, DC offset and the grid voltages distortion conditions. This FsLMS‐based control has shown fast convergence, less oscillations and low settling time as compared with other controls at load unbalancing. Simulated and test results have satisfied the objective of this system and it meets the IEEE‐519 standard.
Stochastic planning of islanded microgrids with uncertain multi‐energy demands and renewable generations
Authors: Jithendranath Jayachandranath , Das Debapriya
Published: February 2021

Islanded microgrids (IMGs) are embedded power networks with distributed energy resources (DERs) providing a reliable and flexible energy option for off‐grid customers. This work addresses the planning model of renewable‐based IMGs feeding multi‐energy demands considering investment and emission related objectives. The proposed solution is to determine the optimal mix and sizing of various energy sources in IMG, including renewables; for multiple energy demands. This study also presents a hybrid‐scenario and Monte Carlo approach to gauge the uncertainty involved in multi‐energy demands, i.e. electrical, heating, and cooling loads; together with correlation among wind and solar generations. The spatial interdependence among renewable generations is implemented using copula; that generates a synthetic set of stochastic correlated data. The combined load scenarios for multi‐energy demands and renewable samples are implemented with the proposed hybrid approach in the formulated stochastic planning model. In this work, the formulated problem is proposed to solve using meta‐heuristic multi‐objective ant lion optimiser algorithm, that is validated on the test system. The superiority of the proposed approach is highlighted in comparison with other multi‐objective optimisers. The multi‐energy dispatch between associated sources and loads were simulated to show how the obtained capacity can suffice the seasonal multi‐energy demands of a typical day considered.
Enhanced efficient and sensitive SERS sensing via controlled Ag‐nanoparticle‐decorated 3D flower‐like ZnO hierarchical microstructure
Authors: Wang Jun , Ning Aifeng
Published: February 2021

Various sizes and morphologies of noble metal/zinc oxide hybrid materials have promising applications in surface‐enhanced Raman scattering (SERS). Generally, organic agents used during the synthesis of metal nanoparticles will inexorably induce organic pollution on the surface of SERS substrate, resulting in a negative effect on detection sensitivity. Herein, a stable and clean 3D flower‐like ZnO/Ag hierarchical microstructure SERS substrate was designed and fabricated via a simple photocatalytic method. This synthetic strategy does not involve usage of any organic agents, which ensures the cleanness and free of impurities interferences. As anticipated, the as‐fabricated 3D flower‐like ZnO/Ag SERS substrates with high surface‐to‐volume ratio increased numerous hot spots, and exhibited excellent detection sensitivity to Rhodamine 6G. A linear relationship between the Raman intensity and the concentration of Rhodamine 6G ranging from 10−11 to 10−4 M was realised. This work demonstrated a performance‐enhanced SERS sensor based on microflower‐like ZnO@Ag hybrids, which provides a potential method to develop highly sensitive and stable SERS sensor for organic molecules detection.
Dielectric performance of magnetic nanoparticles‐based ester oil
Authors: Khan Qasim , Singh Vineet , Ahmad Furkan , Khan Asfar Ali
Published: February 2021

Nanotechnology has been applied in the electrical industry for the enhancement of insulation properties. The compactness of the electrical machines has resulted in the requirement and creation of next‐generation insulating fluid with inflated dielectric properties. In this study, the magnetic nanoparticles are used in different concentrations to form stable nanofluids comprising ester‐based oils and two different electrode structures. The host fluids are synthetic ester oil and rapeseed oil, and magnetic nanoparticles used are iron (II, III) oxide, cobalt (II, III) oxide, and iron phosphide. Furthermore, the breakdown tests are analysed using Weibull statistical distribution.
Deep learning–based surface contamination severity prediction of metal oxide surge arrester in power system
Authors: Das Arup Kumar , Dalai Sovan , Chatterjee Biswendu
Published: February 2021

This paper presents an advanced technique based on cross‐Stockwell transform (XST) and sparse autoencoder to predict the surface contamination severity of metal oxide surge arrester (MOSA) employing leakage current signal. Generally, MOSAs in power system network are exposed to different environmental conditions where its condition may degrade due to accumulation of pollutants, which may cause premature failure of it. Hence, system reliability can get affected. Therefore, monitoring the surface condition of MOSA is very important. In this proposed technique, MOSA leakage current signals of different surface contamination severity have been cross‐correlated with leakage current recorded at the clean surface in joint time‐frequency plane through XST, which is an extended version of ST. Thereafter, sparse autoencoder, a deep learning framework, has been applied to extract potential deep feature from leakage current‐converted XST matrices. The extracted deep features have been classified through different classifiers. It has been observed that the proposed technique yields satisfactory accuracy regarding the estimation of surface contamination severity of MOSA. Therefore, the proposed method can be implemented to monitor the surface condition of MOSA, and it may be applied for topologically similar problems.
Investigating the impact of missing data imputation techniques on battery energy management system
Authors: Pazhoohesh Mehdi , Allahham Adib , Das Ronnie , Walker Sara
Published: February 2021

Effective control of energy storage system (ESS), supplying an ancillary service to a grid, requires effective and critical calculation of state‐of‐charge (SoC). Charging and discharging values from battery operations are essential in calculating the efficiency and performance of a storage system. This information can also be a key to understand and forecast peak demand performance. Missing data is a real problem in any operations system, and it appears to be more common within powers systems due to sensor and/or network malfunctioning problems. Missing data imputation techniques have evolved in power systems research using smart meter data, but little research has gone into understanding how missing data can be best handled within storage management systems. This paper builds on a year's worth of charging and discharging data collected from a real 6MW/10MWh lithium‐ion storage battery deployed on the distribution network at Leighton Buzzard, UK. Using R Studio version (1.3.959‐1) open‐source software, eight selected imputation techniques were applied in identifying the best suited technique in replacing various missing data amounts and patterns. Findings from the study open up avenues for discussion and debate in identifying an appropriate imputation technique within the storage management context. The study also provides a pioneering lead in understanding the importance of decomposition in evaluating the right imputation technique.
The MUSE Extremely Deep Field: The cosmic web in emission at high redshift
Authors: Bacon R. , Mary D. , Garel T. , Blaizot J. , Maseda M. , Schaye J. , Wisotzki L. , Conseil S. , Brinchmann J. , Leclercq F. , Abril-Melgarejo V. , Boogaard L. , Bouché N. F. , Contini T. , Feltre A. , Guiderdoni B. , Herenz C. , Kollatschny W. , Kusakabe H. , Matthee J. , Michel-Dansac L. , Nanayakkara T. , Richard J. , Roth M. , Schmidt K. B. , Steinmetz M. , Tresse L. , Urrutia T. , Verhamme A. , Weilbacher P. M. , Zabl J. , Zoutendijk S. L.
Published: February 2021

We report the discovery of diffuse extended Lyαemission from redshift 3.1 to 4.5, tracing cosmic web filaments on scales of 2.5−4 cMpc. These structures have been observed in overdensities of Lyαemitters in the MUSE Extremely Deep Field, a 140 h deep MUSE observation located in theHubbleUltra-Deep Field. Among the 22 overdense regions identified, five are likely to harbor very extended Lyαemission at high significance with an average surface brightness of 5 × 10−20erg s−1cm−2arcsec−2. Remarkably, 70% of the total Lyαluminosity from these filaments comes from beyond the circumgalactic medium of any identified Lyαemitter. Fluorescent Lyαemission powered by the cosmic UV background can only account for less than 34% of this emission atz ≈ 3 and for not more than 10% at higher redshift. We find that the bulk of this diffuse emission can be reproduced by the unresolved Lyαemission of a large population of ultra low-luminosity Lyαemitters (< 1040erg s−1), provided that the faint end of the Lyαluminosity function is steep (α ⪅ −1.8), it extends down to luminosities lower than 1038 − 1037erg s−1, and the clustering of these Lyαemitters is significant (filling factor < 1/6). If these Lyαemitters are powered by star formation, then this implies their luminosity function needs to extend down to star formation rates < 10−4 M⊙yr−1. These observations provide the first detection of the cosmic web in Lyαemission in typical filamentary environments and the first observational clue indicating the existence of a large population of ultra low-luminosity Lyαemitters at high redshift.
Discovery of CH2CHCCH and detection of HCCN, HC4N, CH3CH2CN, and, tentatively, CH3CH2CCH in TMC-1
Authors: Cernicharo J. , Agúndez M. , Cabezas C. , Marcelino N. , Tercero B. , Pardo J. R. , Gallego J. D. , Tercero F. , López-Pérez J. A. , de Vicente P.
Published: February 2021

We present the discovery in TMC-1 of vinyl acetylene, CH2CHCCH, and the detection, for the first time in a cold dark cloud, of HCCN, HC4N, and CH3CH2CN. A tentative detection of CH3CH2CCH is also reported. The column density of vinyl acetylene is (1.2 ± 0.2) × 1013 cm−2, which makes it one of the most abundant closed-shell hydrocarbons detected in TMC-1. Its abundance is only three times lower than that of propylene, CH3CHCH2. The column densities derived for HCCN and HC4N are (4.4 ± 04) × 1011 cm−2 and (3.7 ± 0.4) × 1011 cm−2, respectively. Hence, the HCCN/HC4N abundance ratio is 1.2 ± 0.3. For ethyl cyanide we derive a column density of (1.1 ± 0.3) × 1011 cm−2. These results are compared with a state-of-the-art chemical model of TMC-1, which is able to account for the observed abundances of these molecules through gas-phase chemical routes.
Improved design of InGaP/GaAs//Si tandem solar cells
Authors: Torres-Jaramillo Santiago , Bernal-Correa Roberto , Morales-Acevedo Arturo
Published: February 2021

Optimizing any tandem solar cells design before making them experimentally is an important way of reducing development costs. Hence, in this work, we have used a complete analytical model that includes the important effects in the depletion regions of the III-V compound cells in order to simulate the behavior of two and four-terminal InGaP/GaAs//Si tandem solar cells for optimizing them. The design optimization procedure is described first, and then it is shown that the expected practical efficiencies at 1 sun (AM1.5 spectrum) for both two and four-terminal tandem cells can be around 40% when the appropriate thickness for each layer is used. The optimized design for both structures includes a double MgF2/ZnS anti-reflection layer (ARC). The results show that the optimum thicknesses are 130 (MgF2) and 60 nm (ZnS), respectively, while the optimum InGaP thickness is 220 nm and GaAs optimum thickness is 1800 nm for the four-terminal tandem on a HIT silicon solar cell (with total tandem efficiency around 39.8%). These results can be compared with the recent record experimental efficiency around 35.9% for this kind of solar cells. Therefore, triple junction InGaP/GaAs//Silicon tandem solar cells continue being very attractive for further development, using high efficiency HIT silicon cell as the bottom sub-cell.
Lumbalgie
Authors: Borgmann Gerrit
Published: February 2021

Der nachstehende Fall beschreibt die Akupunkturbehandlung bei einem Patienten mit anhaltender Lumbalgie und rezidivierender Schmerzausstrahlung in die Beine (v. a. rechts). Schmerzen bestanden intermittierend seit ca. 10 Jahren, in den letzten 6 Monaten war es zu einer spürbaren Beschwerdezunahme gekommen. Parallel dazu hatte der Patient die Einnahme von NSAR stetig gesteigert, wobei der Therapieeffekt nicht mehr ausreichte, um beschwerdefrei zu werden. Bei Beginn der Akupunktur läuft eine physiotherapeutische Behandlung.
Ausbildung zum Wirbelsäulenchirurgen: Ausbildungskonzepte der EANS
Authors: Thomé Claudius
Published: February 2021

Die Wirbelsäulenchirurgie macht etwa 50 % der neurochirurgischen Eingriffe aus und nimmt dementsprechend eine große Rolle in der neurochirurgischen Ausbildung innerhalb Europas ein, wobei nach wie vor jedoch ausgeprägte regionale Unterschiede vorhanden sind. Im Durchschnitt führen neurochirurgische AssistentInnen 700 Wirbelsäuleneingriffe eigenständig, supervidiert oder assistiert während ihrer Facharztausbildung durch und knapp die Hälfte der NeurochirurgInnen streben eine Subspezialisierung in spinaler Chirurgie an.

Im Zentrum des Ausbildungskonzeptes der EANS steht der Trainingskurs, der aus vier Modulen in einem 4-Jahreszyklus besteht. Das spinale Modul weist identische Inhalte zu den Basiskursen von DWG und Eurospine auf und ist als äquivalent zum Basiszertifikat akzeptiert. In Kombination mit rein praktischen Basiskursen kann ein EANS Specialist of Neurosurgery Diploma erworben werden. Eine weitere Subspezialisierung in Wirbelsäulenchirurgie kann über Advanced und Subspecialty Courses erzielt werden, wobei letztere zusammen mit Eurospine veranstaltet werden. Ergänzt wird das Ausbildungskonzept der EANS durch derzeit in Überarbeitung befindliche E-Learning-Inhalte. Finanziell unterstützte EANS-Observerships sind aktuell zahlenmäßig begrenzt. Hier wäre eine Erweiterung oder idealerweise die Etablierung von europaweiten Fellowship-Programmen anzustreben.
A Review of Heterolytic Synthesis Methodologies for Organotri- and Organotetrasulfane Synthesis
Authors: Hunter Roger , Ali Doaa , Amer Yasien , Petersen Wade F. , Kaschula Catherine H.
Published: February 2021

It has been ten years since the last comprehensive review on polysulfanes, and during the intervening period, organodi-, organotri- and organotetrasulfanes have featured prominently in both the chemistry and biology literature. This timely update presents both a mechanistic and historical account of synthesis methodology available for organotri- and organotetrasulfanes involving heterolytic S–S bond formation.
Wideband Absorbance in Ears with Retraction Pockets and Cholesteatomas: A Preliminary Study
Authors: Aithal Sreedevi , Aithal Venkatesh , Kei Joseph , Anderson Shane
Published: February 2021

Abstract Objectives The objective of this study was to describe wideband absorbance (WBA) findings in patients with cholesteatomas and retraction pockets (RPs). Design In this prospective study, tympanometry, audiometry, and wideband tympanometry
(WBT) were performed on 27 ears with an RP (eight with epitympanic RP and 19 ears with mesotympanic RP), 39 ears with a cholesteatoma (23 ears with epitympanic and 16 ears with mesotympanic cholesteatomas [MCs]), and 49 healthy ears serving as controls. Results Mean WBA at
ambient pressure (WBAamb) of both experimental groups was reduced significantly between 0.8 and 5 kHz relative to the control group. The difference between mean WBAamb and mean WBA at tympanometric peak pressure (WBATPP) was greater for the RP (0.12‐0.16
between 0.5 and 1.5 kHz) than for the cholesteatoma group (0.03‐0.11 between 0.6 and 3 kHz). Mean WBAamb of both epitympanic RP (ERP) and epitympanic cholesteatoma (EC) subgroups was significantly lower than that of the control group. Mean WBATPP
of the ERP subgroup attained normal levels as per the control group, while mean WBATPP of EC subgroup was significantly lower than that of the control group at 0.8 to 1.5 kHz and 4 to 5 kHz. In contrast, both mesotympanic RP and MC subgroups demonstrated similar mean
WBAamb and WBATPP values. No significant differences in WBAamb and WBATPP results between the RP and cholesteatomas groups were observed. Receiver operating characteristic (ROC) analyses indicated that the area under the ROC curve for distinguishing
between the RP and cholesteatomas groups ranged from 0.44 to 0.60, indicating low accuracy in separating the two groups. Conclusion While it is not possible to distinguish between the RP and cholesteatomas groups based on the WBAamb and WBATPP results,
it is potentially feasible to differentiate between the EC and ERP conditions. Further study using a large clinical sample is recommended to determine the sensitivity and specificity of the WBA test to identify the EC and ERP conditions.