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Abstract With large‐scale renewable energy connected to the distribution network, the traditional method to solve the distribution network voltage/var power optimization model can hardly meet the needs of online optimization of the distribution network. Therefore, a Bayesian optimization eXtreme Gradient Boosting (BO‐XGBoost) based optimization strategy for voltage/var of the distribution network considering the cost of the photovoltaic (PV) power is proposed to improve the solving speed of the optimization model. First, the voltage/var optimization model of the distribution network considering the LCOE of the PV system is established. The optimal reactive power output command data set of the PV generation in the distribution network is obtained by solving the established optimization model. The XGBoost model is used to mine the nonlinear mapping relationship between the state information of the distribution network and the optimal reactive power output of the PV system; then the Bayesian algorithm is used to complete the adaptive optimization of the hyperparameters of the XGBoost model. Finally, the PG&E 69 node power distribution system is used to verify the advantages of the proposed strategy in improving the performance of the XGBoost algorithm, increasing the solving speed of the voltage/var optimization model, and reducing the LCOE of PV generation.

Iron (Fe) and methane (CH4) emissions play crucial roles in the carbon cycling of paddy field ecosystems. However, little is known about the effect and mechanism of Fe transformation on the CH4 emission from paddy fields, especially with different water management methods. In this study, the dynamic changes in CH4 emissions and different forms of Fe and soil organic carbon content were observed in paddy fields under flooded irrigation (FI) and water-saving irrigation (WSI) (including intermittent irrigation (II) and controlled irrigation (CI)). In addition, the structural equation model was used to clarify the response relationship between CH4 emissions and Fe ions in paddy fields. The results indicate that the cumulative CH4 emissions under WSI were reduced by 29.03–61.29%. The reasons are as follows (i) WSI increased the oxidation ability of Fe to CH4 by increasing the soil ferric iron (Fe3+) content in paddy fields; (ii) WSI could reduce the substrate utilization by methanogens by transforming the Fe oxide forms to increase the binding capacity of Fe to dissolved organic carbon, which reduced the CH4 production. In addition, compared with II, CI had higher soil Fe3+ content, Fe-bound organic carbon content, and lower acetate content, so it had lower CH4 production capacity. In summary, WSI promotes the direct oxidation of CH4 by Fe3+ in paddy fields and indirectly reduces CH4 production by facilitating the combination of Fe oxides with the substrates. These findings deepen our understanding of the mechanisms of CH4 emission in paddy fields and provide new insights for research on carbon sequestration and emission reduction in paddy field ecosystems.

With the high ratio of distributed generation (DG) linked to power system via converters, power system stability is degraded in terms of inertia and damping. In recent years, the virtual synchronous generator (VSG) has become a potential solving method to deal with these issues. However, the power coupling problem exists in the traditional VSG control method, which severely impacts the VSG power control performance. The impedance characteristics of the transmission line are closely related to the effect of the power decoupling control of VSGs. To solve the voltage sag and poor robustness issues resulting from traditional virtual impedance control, a virtual complex impedance power decoupling and sharing control strategy for VSGs based on coordinate transformation is proposed. Combining the characteristics of traditional virtual impedance control and virtual power control, the power coupling mechanism in parallel VSGs caused by line impedance is analyzed. The virtual complex impedance control loop is introduced in VSG control to realize the matching of the equivalent line impedance and the precise decoupling of VSG power output. Then the load can be accurately allocated in the light of the proportion of VSG capacity.

Long-term intensive tillage has led to soil environment degradation, reduced fertility, difficulty in increasing maize yield, and low nitrogen (N) use efficiency in the Mollisol region of northeast China. In order to raise maize yield and improve the soil hydrothermal environment, we conducted field experiments to investigate the effects of different tillage practices and straw returning on the soil hydrothermal environment, maize yield, N fertilizer recovery and loss, aiming to increase both the maize yield and N fertilizer recovery rate. Four treatments were established: flat no-tillage with full straw mulching (NM), ridge no-tillage with full straw mulching (RM), rotary tillage with full straw incorporation (RR), and conventional tillage without straw (CK) as the control treatment. The two-year results indicate that both tillage practices and straw returning increased maize yield and the 15N fertilizer recovery rate, accompanied by improvements in the soil water content (SWC) and regulation of soil temperature changes, as compared to the CK treatment. Specifically, the total 15N fertilizer recovery rate of RM was significantly increased by 15.23% and 23.46%, while the 15N fertilizer losses were notably reduced by 14.99% and 25.12%, respectively, compared to the NM and RR treatments. Additionally, the maize yield of RM was significantly increased by 3.10% in 2021 and 1.97% in 2022 compared to RR (P < 0.05), and it increased by 2.06% in 2021 and 0.91% in 2022 compared to NM (P > 0.05). The mean SWC of the 0–100-cm soil layer in RM significantly increased by 7.99% and 5.74% in 2021 and by 8.09%, and 5.50% in 2022 compared to NM and RR treatments during the maize growth seasons. At 60–80 days after sowing (DAS), when the air temperature was higher, the mean soil temperature of RM was significantly lower than that of the NM and RR treatments, by 0.46 ℃ and 0.54 ℃ in 2021 and by 0.31 ℃ and 0.70 ℃ in 2022. However, as the air temperature decreased at 100–140 DAS, the mean soil temperature in RM was significantly increased by 0.69 ℃ and 0.81 ℃ in 2021 and by 0.73 ℃ and 0.94 ℃ in 2022 compared to the NM and RR treatments. Our study indicates that RM treatment is the most suitable tillage practice and straw returning method in the Mollisol region of northeast China.

For agricultural production, improving the rice harvest index (HI) through agricultural management practices is a major means to enhance water and N utilization efficiency and yield. Both irrigation regimes and nitrogen (N) rates are important aspects of agricultural management practices. However, it is unclear how the rice HI is affected by water and N. This study aimed to clarify the mechanism underlying the response of the rice HI to water and N, and to explore the most suitable water-saving and N reduction management practices to ensure yield. A two-year (2021~2022) field experiment was conducted on Mollisols in Northeast China. In this experiment, nine treatments were performed, involving three irrigation regimes (flooded irrigation, controlled irrigation, and “thin-shallow-wet-dry” irrigation) and three N rates (110, 99, and 88 kg/ha). The rice agronomic traits and transfer of photoassimilates under different water and N management practices were observed and studied; rice HI, WUE, and the NUE of rice was calculated and analyzed. The highest HI was achieved under controlled irrigation with a 99 kg/ha N rate, at values of 0.622 and 0.621 in 2021 and 2022, respectively. Controlled irrigation (CI) with an appropriate reduction in the N rate increased the proportion of productive tillers, the transfer rate of dry matter and non-structural carbohydrates (NSCs), the sugar–spikelet ratio, the grain–leaf ratio, and the leaf area index (LAI) during the heading–flowering stage. A subsequent analysis indicated that the main reason for the increase in the HI was the increase in the sugar–spikelet ratio during the heading–flowering stage. A high HI increased the rice yield by increasing the thousand-grain weight. The present study suggested that water-saving irrigation regimes and appropriate N reduction not only led to water and fertilizer resource savings but also improved agronomic characteristics during rice growth and enhanced transport capacity. Thus, these practices improved the rice HI and have enormous potential for increasing yield. Therefore, regulating the rice HI through water and N management methods should be considered an important strategy for improving rice yield.

Soil quality is an indicator of the ability to ensure ecological security and sustainable soil usage. The effects of long-term straw incorporation and different irrigation regimes on the yield and soil quality of paddy fields in cold regions remain unclear. This study established four treatments: controlled irrigation + continuous straw incorporation for 3 years (C3), controlled irrigation + continuous straw incorporation for 7 years (C7), flooded irrigation + continuous straw incorporation for 3 years (F3), and flooded irrigation + continuous straw incorporation for 7 years (F7). Analysis was conducted on the impact of various irrigation regimes and straw incorporation years on the physicochemical characteristics and quality of the soil. The soil quality index (SQI) for rice fields was computed using separate datasets for each treatment. The soil nitrate nitrogen, available phosphorus, soil organic carbon, and soil organic matter contents of the C7 were 93.51%, 5.80%, 8.90%, and 8.26% higher compared to C3, respectively. In addition, the yield of the C7 treatment was 5.18%, 4.89%, and 10.32% higher than those of F3, C3, and F7, respectively. The validity of the minimum data set (MDS) was verified by correlation, Ef and ER, which indicated that the MDS of all treatments were able to provide a valid evaluation of soil quality. The MDS based SQI of C7 was 11.05%, 11.97%, and 27.71% higher than that of F3, C3, and F7, respectively. Overall, long-term straw incorporation combined with controlled irrigation increases yield and soil quality in paddy fields in cold regions. This study provides a thorough assessment of soil quality concerning irrigation regimes and straw incorporation years to preserve food security and the sustainability of agricultural output. Additionally, it offers a basis for soil quality diagnosis of paddy fields in the Northeast China.

Abstract System kinetic inertia is declining due to the rapid replacement of synchronous generators (SG) by renewable power generations (RPG). To maintain grid inertia, this paper proposes a generic synthetic inertia (GSI) scheme for RPGs, enabling inertial response by a supercapacitor (SC) bank integrated with a voltage source inverter (VSI) DC link via a DC/DC converter. A GSI control loop is developed for the DC/DC converter controller to vary the SC voltage along with the grid frequency for power exchange following the SG swing equation. The GSI scheme realizes plug‐and‐play advantage without modifying the RPG original system. Small‐signal stability analysis is carried out to optimize the GSI controller parameters. The performance of the GSI scheme is evaluated using a modified IEEE 39‐bus test system.

To improve nitrogen use efficiency (NUE) during rice cultivation, it is essential to comprehend the morphological and physiological traits of rice roots. However, in high-fertility black soil regions of Northeast China, the effects of combining biochar application with water-saving irrigation (WSI) conditions on rice root development and nitrogen utilization are still unknown. To address this knowledge gap, a combination of field experiments and 15N tracer micro-area investigations was conducted in this study. Four treatments were implemented: (i) controlled irrigation without biochar application (CB0); (ii) controlled irrigation with 2.5 t ha−1 biochar application (CB1); (iii) controlled irrigation with 12.5 t ha−1 biochar application (CB2); and (iv) controlled irrigation with 25 t ha–1 biochar application (CB3). Flooded irrigation conditions without biochar treatment (FB0) were used as the control. The primary objective of this research was to identify the mechanisms by which combined WSI conditions and biochar application affect rice root development and nitrogen utilization. Biochar application enhanced rice root morphological and physiological characteristics. Optimal biochar application increased the longest root length (RL), root volume (RV), root fresh weight (RFW), root active absorption area, root bleeding intensity, and root activity (RA) of rice while also optimizing the root–shoot ratio and facilitating nitrogen absorption by roots. These changes in root morphological and physiological characteristics facilitated the absorption of fertilizer-15N and soil nitrogen by rice roots, ultimately leading to improvements in rice yields and NUEs. Notably, the rice yields, NUE, nitrogen agronomic efficiency (NAE), and nitrogen partial factor productivity (NPFP) of CB2 plants were 16.45%, 39.42%, 24.48%, and 16.45% higher than those of FB0 plants, respectively. These results highlight the effectiveness of biochar application as a strategy to ensure food security and enhance NUE under WSI conditions. Furthermore, this study suggests that the recommended optimal application amount of biochar for the black soil area of Northeast China is 12.5 t ha−1.

The matching of schematic diagrams and physical information of terminal blocks in substation secondary screen cabinets plays a crucial role in the operation and maintenance of substations. To enhance the automation level of this task and reduce labor costs, a method for identifying and matching information of terminal blocks in substation secondary screen cabinets based on artificial intelligence is investigated in this paper. Initially, multi-layer object detection networks, tailored to the characteristics of both the schematic diagrams and the physical entities in substation secondary screen cabinets, are designed for the precise extraction of information. Subsequently, network topologies for both the schematic and physical systems are established using the Neo4j database, which allows for the digital storage of information in the substation secondary screen cabinet systems. Finally, the branch-and-bound method, improved by the application of a multi-modular graph convolutional network (MGCN) and deep Q-network (DQN), is employed to solve the maximum common subgraph (MCS) problem, resulting in the rapid and efficient matching of schematic and physical data.

The comprehensive greenhouse effect depends on the trade-off between greenhouse gas (GHG) emissions and soil organic carbon sequestration (SOCS) of paddy fields. Investigations of the effect of the straw return on GHG emissions and SOCS under different water management regimes help clarify the strategy to alleviate the comprehensive greenhouse effect of paddy fields. Therefore, a two-year field experiment was conducted to investigate the effect of different water and straw management on GHG emissions, SOCS, and rice yield. The greenhouse effect of paddy fields was quantified by calculating the greenhouse gas emission intensity (GHGI) and net greenhouse gas emission (NGHGE). The field experiment included four treatments: CI: controlled irrigation + straw removal; FI: flooded irrigation + straw removal; CI+SR: controlled irrigation + straw return; and FI+SR: flooded irrigation + straw return. The results showed that straw return could increase the SOCS and rice yield of paddy fields under different water management regimes, and the average SOCS and rice yield of CI+SR were higher than FI+SR. Furthermore, compared with FI, FI+SR promoted the GHG emission and increased the average global warming potential by 36.37%, which significantly increased the average GHGI and NGHGE by 19.95% and 22.63%, respectively. However, the global warming potential of CI+SR had no significant difference with FI due to water-saving irrigation could mitigate CH4 emissions, which caused the average GHGI and NGHGE decrease by 22.02% and 38.45%, respectively. Therefore, straw return combined with water-saving irrigation is an effective strategy to alleviate the comprehensive greenhouse effect of paddy fields.

As an important part of photovoltaic (PV) system, the reliability of PV inverter is the key to ensure the safe and reliable operation of PV power generation system. The existing lifetime evaluation methods of PV inverter are restricted by the extraction accuracy of junction temperature profile, and it is impossible to accurately evaluate the service lifetime of PV inverter. This paper, thus, divides the junction temperature profile according to the time scales, defines the concepts of fundamental frequency junction temperature and low frequency junction temperature. Then, this paper reveals the influence mechanism of fundamental frequency and low frequency junction temperature on PV inverter lifetime evaluation, and proposes a PV inverter lifetime evaluation method considering the influence of fundamental frequency and low frequency junction temperature. Finally, based on this method, the lifetime damage of PV inverter under different mission profiles and different sampling periods is studied, and the influence of fundamental frequency and low frequency junction temperature on lifetime evaluation is analyzed, which improves the accuracy of lifetime evaluation of PV inverter. It is helpful to guide the regular maintenance of PV inverter and reduce economic losses.

A novel low voltage ride through control strategy with variable power tracking trajectory is proposed. The voltage fall amplitude is controlled by feedforward, and the tracking trajectory of power point is adjusted to realize the real-time change of the photoelectric cell voltage. On this basis, the output power of the photovoltaic generation system is controlled quickly and efficiently, and the purpose of power balance in the PV inverter is achieved. Through collaborative control of the grid-tied inverters, the output current of grid-tied inverter can meet the active and reactive power requirements of power grid as much as possible without overing the limit. In this way, the maximized support for the voltage recovery of power grid which contains zero voltage ride through is realized. In the non-standard environment, the proposed control strategy is proven to be effective by the simulation results. Compared with traditional LVRT strategy, the proposed strategy in this paper not only realizes the safe and reliable operation, but also improves the economy of photovoltaic power generation system, without any add additional equipment.

In order to solve the problem of long calculation time of insulated gate bipolar transistor (IGBT) junction temperature, the XGBoost machine learning algorithm is used to calculate IGBT junction temperature in the annual damage assessment process. The XGBoost machine learning algorithm can greatly reduce the calculation time of IGBT junction temperature while ensuring the accuracy, which provides conditions for finding the optimal PV system capacity ratio and power limit value by heuristic algorithm such as differential evolution algorithm later. For PV system capacity ratio and power limit, it is necessary to consider the annual damage of the PV inverter, the increase of power generation due to capacity ratio and the power generation loss due to power limit. This paper proposes an optimization goal that considers the above factors, and uses the differential evolution algorithm to obtain the optimal PV system capacity ratio and power limit value.

The current small-signal stability analysis and parameter selection of converters that mimic synchronous generators usually ignore some dynamic characteristics and the changes of steady-state operating points for simplicity. It could only judge the trend of small-signal stability and the analysis result was not accurate enough. Firstly, this paper established a small-signal model that mimics synchronous generators by connecting two isolated converters in parallel, the eigenvalues of the system were calculated and some of their physical meanings were obtained. Following that, in order to demonstrate the relationship of eigenvalues and state variables, the participation factor was calculated. Considering that, there will be some variability of the operating points with the parameters variation. As a function of the system settings, numerous root locus plots were created. For individual eigenvalue close to the real axis, in order to reveal the contribution of different parameters to the oscillation patterns, a separate eigenvalue sensitivity analysis was performed. The rules of the influence are essential to guide the design of parameters and their optimization of isolated converters connected in parallel that mimic synchronous generators.

Classical droop control and virtual impedance methods play crucial roles in improving the system voltage/frequency stability and autonomous power control. Usually, these two methods are often applied as a combination to facilitate load sharing under different line impedance among distributed generators (DGs) in microgrids. They have been developed in two separate concepts, but present strong similarities. In this paper, the comparison of basic droop control and virtual impedance methods is revisited from a new analogy perspective. By combing both of them, a unified multi-degree-of-freedom droop control is proposed with systematic consideration of steady-state power-sharing performance, dynamic performance, and universal applicability of complex line impedance, which is suitable for arbitrary transmission line impedance characteristics. Moreover, this study gives a clear mechanism analysis of virtual inductance to facilitate the P-f & Q-V droop control in complex resistive-inductive microgrid. Finally, the experiment results verify the feasibility of the proposed unified droop control.

Despite the continuous advancement of intelligent power substations, the terminal block components within equipment cabinet inspection work still often require loads of personnel. The repetitive documentary works not only lack efficiency but are also susceptible to inaccuracies introduced by substation personnel. To resolve the problem of lengthy, time-consuming inspections, a terminal block component detection and identification method is presented in this paper. The identification method is a multi-stage system that incorporates a streamlined version of You Only Look Once version 7 (YOLOv7), a fusion of YOLOv7 and differential binarization (DB), and the utilization of PaddleOCR. Firstly, the YOLOv7 Area-Oriented (YOLOv7-AO) model is developed to precisely locate the complete region of terminal blocks within substation scene images. The compact area extraction model rapidly cuts out the valid proportion of the input image. Furthermore, the DB segmentation head is integrated into the YOLOv7 model to effectively handle the densely arranged, irregularly shaped block components. To detect all the components within a target electrical cabinet of substation equipment, the YOLOv7 model with a differential binarization attention head (YOLOv7-DBAH) is proposed, integrating spatial and channel attention mechanisms. Finally, a general OCR algorithm is applied to the cropped-out instances after image distortion to match and record the component’s identity information. The experimental results show that the YOLOv7-AO model reaches high detection accuracy with good portability, gaining 4.45 times faster running speed. Moreover, the terminal block component detection results show that the YOLOv7-DBAH model achieves the highest evaluation metrics, increasing the F1-score from 0.83 to 0.89 and boosting the precision to over 0.91. The proposed method achieves the goal of terminal block component identification and can be applied in practical situations.

Cascading overload failures of transmission lines are one of the dominant factors that induce catastrophic blackouts. The reliability risk of cascading overload failures is significantly underestimated in traditional adequacy assessment studies. This paper proposes an evaluation model for the assessment of $N$ - $k$ contingencies as cascading overloading failures. The interactions between outaged lines in the propagation path are revealed with a multi-stage optimization problem. The objective function is to maximize the probability of the propagation path of cascading overload failures. Several linearization techniques are proposed to convert the nonlinear evaluation model to mixed-integer linear programming. A rolling search algorithm is adopted to improve the capability of the proposed model to evaluate high-order contingencies. The case studies on the IEEE 118-bus systems show that the proposed model enables the identification of critical propagation paths with probabilities that are a few orders of magnitude larger than those with the traditional method.

In this paper, a dynamic compensation strategy based on a residual generator was proposed to solve the problem of the power quality of the bus in an isolated AC microgrid. Firstly, the disturbance analysis of power quality problems such as voltage fluctuation, three-phase imbalance, harmonic wave is carried out, and the disturbance current is converted into the time domain function in the dq rotating coordinate system. Secondly, the inverter establishes the state space model under the dq rotation coordinate system. Then, the control structure based on residual generator is proposed, the voltage compensator is solved by model matching method, and the current loop secondary compensator is designed to eliminate the influence of the voltage compensator on the current loop. Thirdly, the residual capacity calculation method of the inverter is analysed, and the residual capacity is used to achieve the power quality collaborative governance on the parallel inverter system with the perturbation allocation method. Finally, the control strategy proposed in this paper is verified by the simulation built in PSCAD/EMTDC, and the results can be effectively applied to the low-level control of microgrid, and the power quality control effect of voltage fluctuation, three-phase unbalance and harmonics is good, which improves the robustness of the system to a certain extent.

The fast and reliable detection of subsynchronous oscillations (SSOs) in wind farms is important for maintaining the stable operation of a power system. This paper presents a novel, SSO detection method for noisy synchrophasor data that considers the issue of detection as a binary classification (SSO and non-SSO) from the perspective of pattern recognition. The proposed algorithm easily implements cycle-based feature extraction from raw data by applying the strong period of the SSO signal, which is distinguished from noisy data. To mitigate the performance reduction of regular classifiers due to the imbalance issue caused by SSO data being substantially less than non-SSO data, a weighted kernel extreme learning machine is constructed as a classifier to implement SSO detection. Experimental studies are carried out on simulation and field data; the results show the effectiveness of the proposed algorithm for SSO detection in the case of a low SNR and of imbalance issues.

In order to explore the long-term variation law of methane (CH4) and nitrous oxide (N2O) emissions from rice fields in cold regions under different straw-returning and irrigation methods, this study set up two irrigation methods, namely, conventional flooding and controlled irrigation, and two straw-returning quantities (0 t·hm−2 and 6 t·hm−2). Based on the field in situ test data, a sensitivity analysis of the main factors of the DNDC model affecting the emissions of CH4 and N2O from rice fields was conducted, and the emission fluxes of CH4 and N2O were calibrated and validated. Under different future climate scenarios (RCP4.5 and RCP8.5), greenhouse gas emissions from rice fields were simulated on a 60-year scale under different straw-returning and irrigation methods using the DNDC model. The results indicate that the DNDC model can effectively simulate the seasonal emission laws of CH4 and N2O from rice fields in cold regions under different straw-returning and irrigation methods. The simulated values have a significant correlation with the measured values (R2 ≥ 0.794, p < 0.05), and the consistency is controlled within 30%. The soil texture, soil organic carbon (SOC) content, annual average temperature, and straw-returning amount are sensitive factors for CH4 emissions from rice fields. The total nitrogen fertilizer application amount and SOC content are sensitive factors for N2O emissions from rice fields. Over the next 60 years, under the two different emission scenarios of RCP4.5 and RCP8.5, straw returning combined with control irrigation has a good coupling effect on the GWP of rice fields, and compared with conventional flooding without straw returning, the GWP of rice fields is reduced by 31.41% and 34.13%, respectively, and the SOC content in 0–20 cm soil layer is increased by 54.69% and 52.80%, respectively. Thus, it can be used as a long-term carbon sequestration and emission reduction tillage model for rice fields in Northeast China. The results of this study can provide a reference for a further regional estimation of greenhouse gas emissions from rice fields using models.

With the high proportion of new energy access in power distribution networks, the operation of distribution networks becomes more uncertain and complex. The mechanism on how to extract features that embody the full perspective of the distribution network from the diverse and varying conditions is of great significance to master the operating property of distribution networks under the high proportion of new energy. This study investigates the portrait construction of power distributions. A data-driven method of portrait construction for a distribution network based on a cloud model is proposed. First, the indexes describing the operation of the medium voltage distribution network (MVDN) and low-voltage station area (LVSA) are established. By means of statistics, fuzzy label templates are provided for the indexes. Then, based on the daily monitoring power grid data, the operation index is calculated to form the collected samples, and the reverse cloud generator is used as the data-driven method to process the samples, and the fuzzy model of cloud parameter representation is obtained. Finally, the fuzzy distance between the obtained fuzzy model and the label template is calculated, and the scores of operation indexes are obtained, thus forming a portrait method of distribution network operation behavior. Taking the IEEE 33 distribution network and real distribution network as examples and taking the LVSA as an example, it is verified that this method can effectively construct the distribution network operation portrait.

Appropriate irrigation schedules could minimize the existing imbalance between agricultural water supply and crop water requirements (ETc), which is severely impacted by climate change. In this study, different hydrological years (a wet year, normal year, dry year, and an extremely dry year) in Heilongjiang Province were calculated by hydrological frequency methods. Then, the single crop coefficient method was used to calculate the maize ETc, based on the daily meteorological data of 26 meteorological stations in Heilongjiang Province from 1960 to 2020. Afterward, the CROPWAT model was used to calculate the effective precipitation (Pe) and irrigation water requirement (Ir), and formulate the irrigation schedules of maize in Heilongjiang Province under different hydrological years. The results showed that ETc and Ir decreased first and then increased from west to east. The Pe and crop water surplus deficit index increased first and then decreased from west to east in Heilongjiang Province. Meanwhile, the average values of the Ir in were 171.14 mm, 232.79 mm, 279.08 mm, and 334.47 mm in the wet year, normal year, dry year, and extremely dry year, respectively. Heilongjiang Province was divided into four irrigation zones according to the Ir of different hydrological years. Last, the irrigation quotas for the wet year, normal year, dry year, and extremely dry year were 0~180 mm, 20~240 mm, 60~300 mm, and 80~430 mm, respectively. This study provides reliable support for maize irrigation practices in Heilongjiang Province, China.

As a widely implemented irrigation regime for paddy fields, water-saving irrigation (WSI) is capable of ensuring water resource security and improving nitrogen use efficiency (NUE). Higher gaseous nitrogen losses (GNL) lead to a low recovery rate of basal nitrogen, and this is the primary reason that restricts further improvements in the NUE under WSI. The deep placement of nitrogen fertilizer (DPN) is considered an efficient agricultural management measure to reduce GNL. However, the effects of WSI combined with the deep placement of basal nitrogen fertilizer on NUE, GNL, and rice yield in paddy fields remain largely unknown. In this study, a 2-year field experiment was conducted to measure GNL (N2O emissions and NH3 volatilization), NUE, and rice yield. Four treatments were utilized: (i) conventional flooding irrigation + broadcast of nitrogen fertilizer (110 kg N hm−2, CFN); (ii) water-saving irrigation + deep placement of basal nitrogen fertilizer (110 kg N hm−2, WSN); (iii) water-saving irrigation + deep placement of basal nitrogen fertilizer (99 kg N hm−2, WSN1); (iv) water-saving irrigation + deep placement of basal nitrogen fertilizer (88 kg N hm−2, WSN2). The results showed that the GNL in paddy fields under treatment ranged from 5.29 to 10.67 kg hm−2. Deep placement of basal nitrogen fertilizer mitigated the GNL of the paddy fields under WSI. The GNL of CFN was significantly higher than those of WSN1 and WSN2 by 26.9% and 54.0% in 2021 and 14.4% and 23.3% in 2022, respectively (p < 0.05). Under WSI, the deep placement of basal nitrogen fertilizer reduced the GNL primarily via the reduction of NH3 volatilization. NH3-N of CFN was higher than those treatments under WSI. The rice yield of CFN was significantly lower than those of WSN and WSN1 by 22.4% and 21.6% in 2021 and 4.6% and 1.5% in 2022, respectively. (p < 0.05). Moreover, the NUE of each treatment under WSI was higher than that of CFN. These changes exhibited similar trends in 2021 and 2022. These results demonstrated that deep placement of basal nitrogen fertilizer is an effective practice to ensure food and environmental security under WSI.

Mapping the Intelligent Electronic Devices (IEDs) output interface address description datasets to the intelligent recorder is the groundwork for the recorder to accurately collect IEDs' operation information. These datasets, which are also intelligent recorder configuration datasets, are included in the Substation Configuration Description (SCD) file of an intelligent substation. The mainstream mapping method is manually mapping these datasets based on output interface Chinese description texts. When the number of IEDs is extremely large, the manual operation often takes a huge amount of time, together with the higher labor cost. And since the Chinese description texts have a certain degree of irregularity, it also poses a problem for the automatic mapping of the datasets. Aiming at this problem, this paper proposes an automatic mapping method of IEDs configuration datasets based on a deep learning framework-Dynamic Convolutional Neural Network (DCNN). Firstly, it uses the word representation model Word2vec to vectorize words in Chinese description texts as well as their semantics relationships. Then word vectors will be imported in the DCNN, which, based on its multilayer abstract learning characteristics of typical sample features, can perform semantic law mining and automatic mapping. The configuration datasets of intelligent recorder will be automatically mapped based on the Chinese descriptions mapping result. The Practical example shows that the Chinese description texts classification method based on the Dynamic Convolutional Neural Network model has strong semantic analysis ability and high classification accuracy, which effectively improves the accuracy of automatic mapping of intelligent recorder configuration data.

UV LED has been widely used in various fields such as medical disinfection and biochemical detection, especially in UV curing. Compared with traditional high-voltage mercury lamp, UV LED shows large differences both in the spectral power distribution and irradiance, which may cause up to 20% error in calibration. A 365 nm UV LED source has been developed and measured, which is made of UV LEDs, temperature control module, integrating sphere, circuit and monitoring module. The experiment results indicate that the irradiance of about 884 mW/cm2 meets the actual requirements of the curing industry, and the stability of 1.0% (15 min) and uniformity of 1.6% are in compliance with the calibration regulation.

With the intensive integration of photovoltaic (PV) sources into the low-voltage distribution networks (LVDN), the nodal voltage limit violations and fluctuation problem cause concerns on the safety operation of a power system. The intermittent, stochastic, and fluctuating characteristics of PV output power leads to the frequent and fast fluctuation of nodal voltages. To address the voltage limit violation and fluctuation problem, this paper proposes a distributed nodal voltage regulation method based on photovoltaic reactive power and on-load tap changer transformers (OLTC). Using the local Q/V (Volt/Var) feedback controller derived from the grid sensitivity matrix, the voltage magnitude information is adopted to adjust the output of PV systems. Moreover, in order to share the burden of voltage regulation among distributed PV systems, a weighted distributed reactive power sharing algorithm is designed to achieve the voltage regulation according to the rated reactive power. Theoretical analysis is provided to show the convergence of the proposed algorithm. Additionally, the coordination strategy for distributed PV systems and OLTC is provided to reduce the reactive power outputs of PV systems. Five simulation case studies are designed to show the effectiveness of the proposed voltage regulation strategy, where the voltage regulation and proportional reactive power sharing can be achieved simultaneously.

Climate change refers to the statistically significant changes in the mean and dispersion values of meteorological factors. Characterizing potential evapotranspiration (ET0) and its climatic causes will contribute to the estimation of the atmospheric water cycle under climate change. In this study, based on daily meteorological data from 26 meteorological stations in Heilongjiang Province from 1960 to 2019, ET0 was calculated by the Penman–Monteith formula, linear regression method and the Mann–Kendall trend test were used to reveal the seasonal and inter-annual changing trend of ET0. The sensitivity-contribution rate method was used to clarify the climatic factors affecting ET0. The results showed that: (1) From 1960 to 2019, the maximum temperature (Tmax), minimum temperature (Tmin) and average temperature (Tmean) showed an increasing trend, with climate tendency rate of 0.22 °C per decade (10a), 0.49 °C/(10a), 0.36 °C/(10a), respectively. The relative humidity (RH), wind speed (U) and net radiation (Rn) showed a decreasing trend, with a climate tendency rate of −0.42%/(10a), −0.18 m/s/(10a), −0.08 MJ/m2/(10a), respectively. (2) ET0 showed a decreasing trend on seasonal and inter-annual scales. Inter-annually, the average climate tendency rate of ET0 was −8.69 mm/(10a). seasonally, the lowest climate tendency rate was −6.33 mm/(10a) in spring. (3) ET0 was negatively sensitive to Tmin, and RH, while positively sensitive to Tmax, TmeanU and Rn, its sensitivity coefficient of U was the highest, which was 1.22. (4) The contribution rate of U to ET0 was the highest on an inter-annual scale as well as in spring and autumn, which were −8.96%, −9.79% and −13.14%, respectively, and the highest contribution rate to ET0 were Rn and Tmin in summer and winter, whose contribution rates were −4.37% and −11.46%, respectively. This study provides an understanding on the response of evapotranspiration to climatic change and further provides support on the optimal allocation of regional water resource and agricultural water management under climate change.

Crop water production function models (WPFMs) are required methods to study the relationships between yield and water consumption under regulated deficit irrigation (RDI). In this study, a pot experiment was established to study the effect of water deficit during both individual growth stages and across two consecutive growth stages of rice on yield, water consumption, and water use efficiency (WUE) in 2017 and 2018. Light, medium, and severe water deficits were set as 80~90%, 70~80%, and 60~70% of saturated soil moisture content, respectively. The accuracies of five WPFMs were tested based on the experimental results. The results showed that yields and WUE of a light water deficit were higher than those of medium and severe water deficits at each growth stage. The yields and WUE of light drought stress treatments in the flowering and milky stages were higher than the saturated soil moisture control by 4~7.4% and 5.3~20.6%, respectively. Water consumption decreased with increasing water deficit across two consecutive growth stages. The Minhas model had the highest simulation accuracy of the five WPFMs, with relatively lower AE, RMSE, Cv, CRM, and higher R2, which were 0.0002, 0.0634, 6.9965, 0.0002, and 0.9951 in 2017 and 0.0110, 0.0760, 8.9882, 0.0131, and 0.9923 in 2018, respectively. The sensitivity indices for the Minhas model more accurately reflected the sensitivity of rice yield to water deficit at different growth stages in 2017 and 2018, compared with the Jensen model, Stewart model, Blank model, and Singh model. Rice yield was most sensitive to water deficit at the jointing and booting stage. The results indicate that the Minhas model is the most suitable WPFM for guiding rice irrigation practices in cold and black soil regions of China.

Straw incorporation has a variety of impacts on greenhouse gas (GHG) emissions. However, few studies have focused on the effects of multi-year straw incorporation. In this study, a field experiment was established to study the effects of straw incorporation and water-saving irrigation on GHG emissions in the cold region of Northeast China. The following four treatments were included: (i) controlled irrigation (CI) with 1-year straw incorporation (C1), (ii) controlled irrigation with 5-year straw incorporation (C5), (iii) flooded irrigation (FI) with 1-year straw incorporation (F1), and (iv) flooded irrigation with 5-year straw incorporation (F5). The fluxes of N2O, CO2, and CH4 were measured by the static chamber–gas chromatography method, and their global warming potential (GWP) and greenhouse gas intensity (GHGI) in units of CO2-equivalent at the 100-year scale were calculated. The results showed that the 5-year straw incorporation reduced N2O emissions but increased CH4 emissions. Compared with C1 and F1, C5 and F5 reduced N2O emissions by 73.1% and 44.9%, respectively, while increasing the CH4 emissions by 101.7 and 195.8%, respectively. Under different irrigation regimes, CI reduced CH4 emissions by 50.4–79.7% while increasing CO2 emissions by 8.2–44.9% compared with FI. The contribution of N2O and CO2 emissions were relatively high at the mature and milk stages, respectively, with a range of 16–54% and 41–52% for the treatments. In contrast, CH4 emissions were mainly manifested at the tillering stage, with a contribution of 36–58% for the treatments. Affected by higher CH4 emissions in FI, the GWP of CI was 1.4–47.6% lower than FI. In addition, the yield of CI was 10.0–11.5% higher than FI, which resulted in a GHGI of 11.5–52.4% lower than FI, with C5 being the lowest. The irrigation regime of CI combined with 5-year straw incorporation was an effective agronomic measure to increase yield and reduce GHG emissions from paddy fields in the cold region of Northeast China.

Understanding future changes in water supply and requirement under climate change is of great significance for long-term water resource management and agricultural planning. In this study, daily minimum temperature (Tmin), maximum temperature (Tmax), solar radiation (Rad), and precipitation for 26 meteorological stations under RCP4.5 and RCP8.5 of MIRCO5 for the future period 2021–2080 were downscaled by the LARS-WG model, daily average relative humidity (RH) was estimated using the method recommended by FAO-56, and reference crop evapotranspiration (ET0), crop water requirement (ETc), irrigation water requirement (Ir), effective precipitation (Pe), and coupling degree of ETc and Pe (CD) for soybean during the growth period were calculated by the CROPWAT model in Heilongjiang Province, China. The spatial and temporal distribution of these variables and meteorological factors were analyzed, and the response of soybean water supply and requirement to climate change was explored. The result showed that the average Tmin, Tmax, and Rad under RCP4.5 and RCP8.5 increased by 0.2656 and 0.5368 °C, 0.3509 and 0.5897 °C, and 0.0830 and 0.0465 MJ/m², respectively, while the average RH decreased by 0.0920% and 0.0870% per decade from 2021 to 2080. The annual average ET0, ETc, Pe, and Ir under RCP4.5 for 2021–2080 were 542.89, 414.35, 354.10, and 102.44 mm, respectively, and they increased by 1.92%, 1.64%, 2.33%, and −2.12% under the RCP8.5, respectively. The ranges of CD under RCP4.5 and RCP8.5 were 0.66–0.95 and 0.66–0.96, respectively, with an average value of 0.84 for 2021–2080. Spatially, the CD showed a general trend of increasing first and then decreasing from west to east. In addition, ET0, ETc, and Pe increased by 9.55, 7.16, and 8.77 mm per decade, respectively, under RCP8.5, while Ir decreased by 0.65 mm per decade. Under RCP4.5 and RCP8.5, ETc, Pe, and Ir showed an overall increasing trend from 2021 to 2080. This study provides a basis for water resources management policy in Heilongjiang Province, China.

Water-saving irrigation is recognized as an effective agricultural management due to water security and environmental protection problems. In Northeast China, an increasing number of paddy fields are shifting from conventional irrigation to water-saving irrigation. However, there is limited knowledge regarding the carbon (C) budget of paddy fields after implementing water-saving irrigation in Northeast China. A 2-year consecutive field study was performed from 2018 to 2019 using three different irrigation regimes (conventional irrigation (FI), controlled irrigation (CI), and intermittent irrigation (II)) and two nitrogen (N) fertilization levels (110 and 165 kg N ha−1) in a paddy field of Northeast China. The present study aimed to quantify the net ecosystem C budget (NECB) and net global warming potential (net GWP) after the implementation of water-saving irrigation in Northeast China. Both CI and II enhanced the C sequestration capacity of this paddy field. The net primary productivity (NPP) under CI and II was higher than FI by 18–38% and 11–33%, respectively, when the same N fertilization level was applied. The NECB ranged from 1151 to 2663 kg C ha−1, indicating that all treatments acted as net C sinks. II increased the NECB through increasing NPP, which exceeded increased removal of harvest and C mineralized losses. Under II, the NECB was significantly higher than FI and CI when the same N fertilization level was applied (p < 0.05). The net GWP under II and CI was significantly lower than FI (p < 0.05). The net GWP under II was lower than CI when the N fertilization level was 165 kg N ha−1, but no significant differences were detected. These results demonstrated that the II with 165 kg N ha−1 of paddy fields strongly decreased net GWP in Northeast China to combat global climate change.

With the continuous increase in wind power penetration, doubly fed wind turbines can quickly respond to changes in grid frequency, and have particularly important inertia-response characteristics. This article starts with the excitation control principle of a doubly fed induction generator, compares the transient frequency characteristics of the synchronous generator under fault, and proposes that the doubly fed induction generator can control the speed or active power of the generator through excitation. It proves the unique “active power transient frequency characteristics” of doubly fed induction generators. Under different wind speeds, the inertia response capability of the wind turbine is quantified, and the degrees of influence of the inertia time constant and frequency characteristic slope of the doubly fed induction generator on the transient change process are analyzed. Finally, simulation and experiments verify the correctness of the above theory, which provides a basis for significantly improving the transient stability of the power system and realizing the controllability of the transient stability of the power system.

Predicting the impact of future climate change on food security has important implications for sustainable food production. The 26 meteorological stations’ future climate data in the study area are assembled from four global climate models under two representative concentration pathways (RCP4.5 and RCP8.5). The future maize yield, actual crop evapotranspiration (ETa), and water use efficiency (WUE) were predicted by calibrated AquaCrop model under two deficit irrigation (the regulated deficit irrigation (RDI) at jointing stage(W1), filling stage(W2)), and full irrigation (W3) during the three periods (2021–2040, 2041–2060, and 2061–2080). The result showed that the maize yields under W1, W2, and W3 of RCP4.5 were 2.8%, 2.9%, and 2.5% lower than those in RCP8.5, respectively. In RCP8.5, the yield of W3 was 1.9% and 1.4% higher than W1 and W2, respectively. Under the RCP4.5, the ETa of W1, W2, and W3 was 481.32 mm, 484.94 mm, and 489.12 mm, respectively. Moreover, the ETa of W1 was significantly lower than W2 under the RCP4.5 and RCP8.5 (p > 0.05). In conclusion, regulated deficit irrigation at the maize jointing stage is recommended in the study area when considering WUE.

Understanding the methods leading to rice yield increase is vital for sustainable agricultural development. Improving the harvest index (HI) is an important way to increase rice yield. To explore the effects of different water and nitrogen management modes on the rice HI in the black soil region of Northeast China, a field experiment was conducted in 2019 (Y1) and 2020 (Y2). Two irrigation methods, conventional flooding irrigation (FI) and controlled irrigation (CI), were established in the experiment, and four nitrogen application levels (0 kg/ha, 85 kg/ha, 110 kg/ha, and 135 kg/ha) were set during the entire growth period, named N0, N1, N2, and N3. The dry matter weight and the rice yield at the maturity stage were determined, and the HI was then calculated. The results showed that different irrigation modes and nitrogen application levels had significant effects on the rice HI. Under different irrigation modes with the same nitrogen application level during the two years, the comparison regular of HI was consistent. In Y1 and Y2, the HI of FN0 was 3.36% and 5.02% higher than that of CN0 (p < 0.05), and the HI of CN1 was 0.31% and 2.43% higher than that of FN1 (p > 0.05). The HI under CI was significantly higher than that under FI under N2 and N3 (p < 0.05), the HI of CN2 was 4.21% and 4.97% higher than that of FN2, and the HI of FN3 was 13.12% and 20.34% higher than that of CN3. In addition, during the two-year experiment, the HI first increased and then decreased with an increase in the nitrogen application rate under FI and CI. Under the FI treatments, the HI of N1 was the highest, and that of N2 was the highest under the CI treatments. A variance analysis showed that the irrigation pattern and nitrogen application level had significant interactions on the rice HI (p < 0.01), and the appropriate water and N management mode could increase rice the HI by 26.89%. The experimental results showed that the HI of the 110 kg/ha nitrogen application rate under CI was the highest, reaching 0.574 and 0.572, respectively, in two years. This study provides a data reference and theoretical support for realizing water savings, nitrogen reduction, and sustainable agricultural development in the black soil region of Northeast China.

Agricultural irrigation depends heavily on freshwater resources. Under the context of increasingly severe water shortages, studying the relationship among crop water requirements (ETc), actual crop evapotranspiration (ETa), irrigation water requirements (Ir), yield, and water use efficiency (WUE) would be beneficial to improve the agricultural application of irrigation water. Based on the daily data of 26 meteorological stations in Heilongjiang Province from 1960 to 2015, this study used the calibrated AquaCrop model to calculate the ETc, ETa, Ir, and yield of maize (Zea mays L.) in different hydrological years (extremely dry years, dry years, normal years, and wet years) along with WUE to evaluate the mass of yield produced per unit mass of crop evapotranspiration (ET) under rainfed and irrigated scenarios. The results showed that ETc and ETa decreased first and then increased from the west to the east during the four types of hydrological years. Ir exhibited a decreasing trend from the west to the east. Compared with the irrigation scenario, the rainfed scenario’s average yield only decreased by 2.18, 0.55, 0.03, and 0.05 ton/ha, while the WUE increased by 0.32, 0.4, 0.33, and 0.21 kg/m3 in the extremely dry years, dry years, normal years, and wet years, respectively. The results indicated that in the normal and wet years, the WUE was high in the central regions, and irrigation did not significantly increase yield; further, we determined that irrigation should not be considered in these two hydrological years in Heilongjiang Province. In the extremely dry and dry years, irrigation was necessary because it increased the yield, even though the WUE decreased. This study provides a theoretical basis for studying the regional irrigation schedule in Heilongjiang Province.

With the increasing penetration level of wind turbine generators (WTGs) integrated into the power system, the WTGs are enforced to aid network and fulfill the low voltage ride through (LVRT) requirements during faults. To enhance LVRT capability of permanent magnet synchronous generator (PMSG)-based WTG connected to the grid, this paper presents a novel coordinated control scheme named overspeed-while-storing control for PMSG-based WTG. The proposed control scheme purely regulates the rotor speed to reduce the input power of the machine-side converter (MSC) during slight voltage sags. Contrarily, when the severe voltage sag occurs, the coordinated control scheme sets the rotor speed at the upper-limit to decrease the input power of the MSC at the greatest extent, while the surplus power is absorbed by the supercapacitor energy storage (SCES) so as to reduce its maximum capacity. Moreover, the specific capacity configuration scheme of SCES is detailed in this paper. The effectiveness of the overspeed-while-storing control in enhancing the LVRT capability is validated under different levels of voltage sags and different fault types in MATLAB/Simulink.

Maternal age has significantly increased among Chinese women, thereby posing risk of pregnancy-related complications. Preeclampsia is a leading cause of maternal and perinatal morbidity and mortality, and coagulation analysis in conjunction with clinical signs and symptoms are generally used for its diagnosis with limited efficacy. Sonoclot coagulation analyzer is effective in assessing coagulation function used during cerebral surgery and cardiovascular surgery. However, its use has not been explored in preeclampsia. Here, we investigated the potential use of Sonoclot in diagnosing preeclampsia in obstetrics cases. Subjects meeting the screening criteria were divided either into a test group or a control group, according to whether they were preeclamptic or not. We recorded the Sonoclot-derived coagulation and the routine coagulation parameters including platelet function (PF), activated clotting time (ACT) and clot rate (CR), prothrombin time (PT), activated partial thromboplastin time (APTT), thrombin time (TT), fibrinogen (FIB), and platelet count. Regression analysis was done on the relevant parameters to assess the feasibility of Sonoclot analyzer in preeclampsia diagnosis. In parallel, changes in preeclampsia lncRNAs was also evaluated. Significant differences were recorded in PT and ACT between the two groups. In the monovariant logistic regression, PT and ACT appeared to be reliable predictor variables. In the multinomial logistic regression, a total of five regression steps were performed with decreasing AIC values. The K-fold cross validation resulted in an accuracy rate (ACC) of 77.5%, a false positive rate of 16.4%, and a false negative rate of 33.2%. lncRNAs ANRIL and HOXD-AS1 were found deregulated. Our findings indicate that Sonoclot may be useful for diagnosis of preeclampsia in obstetrics.