A unified multi-step wind speed forecasting framework based on numerical weather prediction grids and wind farm monitoring data

Wind speed forecasting is the basis of wind farm operation, which provides a reference for the future operation status evaluation of wind farms. For the wind speed forecast of wind turbines in the whole wind farm, a strategy combining unified forecast and single site error correction is proposed in this paper. The unified forecast framework is composed of a unified forecast model and multiple single site error correction models, which combines the forecasted grids of numerical weather prediction (NWP) with the monitoring data of wind farms. The proposed unified forecast model is called spatiotemporal conversion deep predictive network (STC-DPN), which is composed of temporal convolution network (TCN) and 2D convolution long short-term memory network (ConvLSTM). Firstly, the NWP forecasted grids are interpolated to the fan location, and the sequence matrix is composed of the NWP data and the monitored data of each wind turbine according to the time series, which is entered into the TCN network for time sequence feature extraction. Then, the output of the TCN network is converted into a regular spatio-temporal data matrix, which is entered into the ConvLSTM network for joint learning of spatio-temporal features to obtain the wind speed sequence forecasted in the whole wind farm. Finally, an independent TCN-LSTM error correction model is added for each site. Variational modal decomposition (VMD) is used to process data series, and different processing methods are adopted in unified forecast and single site error correction. In the 96 steps forecast test of a wind farm from Jining City, China, the proposed method is superior to several baseline methods and has important practical application value

Adiponectin Protects Against Cerebral Ischemic Injury Through AdipoR1/AMPK Pathways

Excitotoxicity induced by excessive N-methyl-D-aspartate (NMDA) receptor activation underlies the pathology of ischemic injury. Adiponectin (APN) is an adipocyte-derived protein hormone that modulates a number of metabolic processes. APN exerts a wide range of biological functions in the central nervous system. However, the role of APN and its receptors in cerebral ischemia/reperfusion (I/R)-induced injury and the related mechanisms remain to be clarified. Here, we found that APN and APN receptor agonist AdipoRon (APR) were protective against excitotoxicity induced by oxygen and glucose deprivation/reperfusion (OGD/R) and NMDA in primary neurons. Adiponectin receptor 1 (AdipoR1) knockdown reversed the protection conferred by either APN or APR. Moreover, the protective effects offered by both APN and APR were compromised by compound C, an inhibitor of amp-activated protein kinase (AMPK) phosphorylation. Both APN and APR protected the dissipation of the ΔΨm caused by OGD/R. They also up-regulated the PGC-1α expression, which was reversed by compound C. Furthermore, both APN and APR ameliorated but APN knockout aggravated the infarct volume and neurological deficient induced by transient middle cerebral artery occlusion (tMCAO) in vivo. Taken together, these findings show that APN and APR protect against ischemic injury in vitro and in vivo. The protective mechanism is mainly related to AdipoR1-dependent AMPK phosphorylation and PGC-1α up-regulation

A method to prolong lithium-ion battery life during the full life cycle

Extended lifetime of lithium-ion batteries decreases economic costs and environmental burdens in achieving sustainable development. Cycle life tests are conducted on 18650-type commercial batteries, exhibiting nonlinear and inconsistent degradation. The accelerated fade dispersion is proposed to be triggered by the evolution of an additional potential of the anode during cycling as measured vs. Li$^+$/Li. A method to prolong the battery cycle lifetime is proposed, in which the lower cutoff voltage is raised to 3 V when the battery reaches a capacity degradation threshold. The results demonstrate a 38.1% increase in throughput at 70% of their beginning of life (BoL) capacity. The method is applied to two other types of lithium-ion batteries. A cycle lifetime extension of 16.7% and 33.7% is achieved at 70% of their BoL capacity, respectively. The proposed method enables lithium-ion batteries to provide long service time, cost savings, and environmental relief while facilitating suitable second-use applications

Realization of high-dynamic-range broadband magnetic-field sensing with ensemble nitrogen-vacancy centers in diamond

We present a new magnetometry method integrating an ensemble of nitrogen-vacancy (NV) centers in a single-crystal diamond with an extended dynamic range for monitoring the fast changing magnetic-field. The NV-center spin resonance frequency is tracked using a closed-loop frequency locked technique with fast frequency hopping to achieve a 10 kHz measurement bandwidth, thus, allowing for the detection of fast changing magnetic signals up to 0.723 T/s.This technique exhibits an extended dynamic range subjected to the working bandwidth of the microwave source. This extended dynamic range can reach up to 4.3 mT, which is 86 times broader than the intrinsic dynamic range. The essential components for NV spin control and signal processing such as signal generation, microwave frequency control, data processing and readout are integrated in a board-level system. With this platform, we demonstrate broadband magnetometry with an optimized sensitivity of 4.2 nT-Hz-1/2. This magnetometry method has the potential to be implemented in a multichannel frequency locked vector magnetometer suitable for a wide range of practical applications such as magnetocardiography and high-precision current sensors.Comment: 18 pages, 9 figure

Data-driven capacity estimation of commercial lithium-ion batteries from voltage relaxation

Accurate capacity estimation is crucial for the reliable and safe operation of lithium-ion batteries. In particular, exploiting the relaxation voltage curve features could enable battery capacity estimation without additional cycling information. Here, we report the study of three datasets comprising 130 commercial lithium-ion cells cycled under various conditions to evaluate the capacity estimation approach. One dataset is collected for model building from batteries with LiNi$_{0.86}$Co$_{0.11}$Al$_{0.03}$O$_{2}$-based positive electrodes. The other two datasets, used for validation, are obtained from batteries with LiNi$_{0.83}$Co$_{0.11}$Mn$_{0.07}$O$_{2}$-based positive electrodes and batteries with the blend of Li(NiCoMn)O$_{2}$ - Li(NiCoAl)O$_{2}$ positive electrodes. Base models that use machine learning methods are employed to estimate the battery capacity using features derived from the relaxation voltage profiles. The best model achieves a root-mean-square error of 1.1% for the dataset used for the model building. A transfer learning model is then developed by adding a featured linear transformation to the base model. This extended model achieves a root-mean-square error of less than 1.7% on the datasets used for the model validation, indicating the successful applicability of the capacity estimation approach utilizing cell voltage relaxation

The VEGF -634G>C promoter polymorphism is associated with risk of gastric cancer

<p>Abstract</p> <p>Background</p> <p>Both TGF-β1 and VEGF play a critic role in the multiple-step process of tumorgenesis of gastric cancer. Single nucleotide polymorphisms (SNPs) of the <it>TGFB1 </it>and <it>VEGF </it>genes have been associated with risk and progression of many cancers. In this study, we investigated the association between potentially functional SNPs of these two genes and risk of gastric cancer in a US population.</p> <p>Methods</p> <p>The risk associated with genotypes and haplotypes of four <it>TGFB1 </it>SNPs and four <it>VEGF </it>SNPs were determined by multivariate logistic regression analysis in 171 patients with gastric cancer and 353 cancer-free controls frequency-matched by age, sex and ethnicity.</p> <p>Results</p> <p>Compared with the <it>VEGF</it>-634GG genotype, the -634CG genotype and the combined -634CG+CC genotypes were associated with a significantly elevated risk of gastric cancer (adjusted OR = 1.88, 95% CI = 1.24-2.86 and adjusted OR = 1.56, 95% CI = 1.07-2.27, respectively). However, none of other <it>TGFB1 </it>and <it>VEGF </it>SNPs was associated with risk of gastric cancer.</p> <p>Conclusion</p> <p>Our data suggested that the <it>VEGF</it>-634G>C SNP may be a marker for susceptibility to gastric cancer, and this finding needs to be validated in larger studies.</p

A New Method of Reference Signals Calculation for Switching Compensator

This paper is under in-depth investigation due to suspicion of possible plagiarism on a high similarity indexThe switching compensation devices, such as active power filters and static var generator, are growing rapidly for power quality improvement. The current reference signals is one of the important factor affecting the responsible speed and compensation effect. In this paper, a new strategy for reference signals calculation is present based on Current’s Physical Components. Through the orthogonal decomposition of the load current by the CPC power theory, the reference current, for various compensation objectives of switching compensation devices, can be calculated by the combination of the orthogonal current components. It is demonstrated that this strategy can be used for various compensation goals of limited switching compensation devices and changing the compensation objectives on-line according to the power grids. The validity of the developed strategy is verified by the simulation results

High-frequency isolated variable frequency speed regulation sensorless vector control in mine

In the coal mine's medium and high voltage and limited occasions, the frequency converter is connected to the power grid by power frequency transformer. Most of the controlled motors are controlled by open-loop control, which has the problems of narrow working space, complex structure and poor robustness of motor control. In order to solve the above problems, a speed sensorless vector control strategy based on high frequency isolated variable frequency speed regulation topology is proposed. This paper analyzes the topology and power transmission of the main circuit of high-frequency isolated variable frequency speed regulation in mine. The input three-phase power frequency AC power supply is rectified into DC power supply through an uncontrollable rectification link. The pulsating DC power supply is smoothed and filtered to obtain a stable DC power supply. The DC power supply is transformed through high-frequency isolation (DC-DClevel). Then, through the three-phase inverter stage, the DC power supply is converted into AC power supply with adjustable voltage and frequency. In order to reduce IGBT switching loss, save the overall cost and reduce the complexity of its overall structure, the three-phase rectifier stage adopts a diode uncontrolled rectification strategy. The equal pulse width modulation (EPWM) strategy is adopted for the high-frequency isolated DC-DC stage. The speed sensorless vector control strategy is adopted in the three-phase inverter stage. In this control strategy, the model reference adaptive system (MRAS) is used to estimate the speed of the asynchronous motor. A 0.75 kW three-phase asynchronous motor is used as the tested motor to verify the speed sensorless vector control strategy of high-frequency isolated variable frequency speed regulation for mine. The results show the following points. ① The voltage fluctuation of the DC bus on both sides of the high-frequency isolation DC-DC level is less than 10 V and the high-frequency square wave voltage is equal. The voltage waveforms of the primary single-phase inverter square wave and the high-frequency transformer coupled square wave are smooth and the overall steady-state performance is good. ② The three-phase inverter voltage and current waveform sine degree are good. The waveform is symmetrical and smooth. The three-phase inverter level stability performance is good, which meets the requirements of motor operation. ③ With the increase of time, the excitation current change is stable. The torque current responds quickly at startup. The torque current is large at the start-up stage, which can generate large torque. ④ The speed fluctuation of the motor is small in the stable phase. The waveforms of acceleration and deceleration phases tend to be a linear function, and the motor can start and stop smoothly. When the motor is just started, the maximum torque can reach more than 5 times of the stable torque, and the motor can be started quickly to work

Multi-Sensor Fusion and Error Compensation of Attitude Measurement System for Shaft Boring Machine

To ensure that the shaft boring machine (SBM) runs along the pre-designed axis steadily, the role of the attitude measurement system is essential, but its accuracy and reliability cannot be guaranteed. Currently, there is no effective technology to meet the actual requirements, and there is a lack of relevant theoretical research in this field. Through further study of the attitude analysis method and multi-sensor fusion technology, this paper presents a dual coordinate method, which can be used to describe the attitude characteristics of the SBM. Moreover, this paper discusses the relationships between the attitude changes and the values of the angle as well as displacement and analyzes the implementation complexity and computational efficiency of related algorithms in software and hardware. According to the working characteristics of the SBM, the hardware design and the reasonable layout of the attitude measurement system are provided. Based on multi-sensor data, this paper puts forward an improved method combining a complementary filter with an extended Kalman filter (EKF) for attitude estimation and error compensation. The simulation experiments of different working processes verify the steady-state response and dynamic response performance of the method. Experimental results show that the dual coordinate method and the proposed filter are more suitable for attitude estimation of the SBM compared to other methods