International Journal of Electrical Power & Energy Systems最新文献

{"title":"Novel Gaussian process method for photovoltaic maximum power point tracking","authors":"Karim Diab ,&nbsp;Ali Wadi ,&nbsp;Mamoun F. Abdel-Hafez ,&nbsp;Ala A. Hussein","doi":"10.1016/j.ijepes.2026.111886","DOIUrl":"10.1016/j.ijepes.2026.111886","url":null,"abstract":"<div><div>Maximum power point tracking (MPPT) in photovoltaic (PV) systems remains challenging under model uncertainty, measurement noise, and changing operating conditions, where conventional methods often require careful tuning or suffer degraded performance. This study investigates whether a Gaussian Process (GP)-based framework can provide accurate and robust MPPT without relying on precise prior system tuning. A novel GP-inspired MPPT algorithm is proposed and experimentally validated using PV modules arranged in three configurations: parallel, series, and series–parallel. The method reformulates the estimation problem within a GP-based state estimation framework and uses Metropolis-Hastings Markov Chain Monte Carlo (MH-MCMC) to infer key hyperparameters, eliminating the need for manual tuning. Its performance is benchmarked against conventional Perturb and Observe (P&amp;O), Adaptive P&amp;O, and Kalman Filter (KF) methods using root mean square error (RMSE), integral time absolute error (ITAE), and convergence behavior. The results show that the proposed GP method matches KF performance under well-tuned conditions. Since the GP infers the tuning parameters, GP ITAE is lower than the KF by a factor of 10 in most experiments. The GP also outperforms traditional P&amp;O and achieves lower ITAE than Adaptive P&amp;O, with convergence in the microsecond-to-millisecond range depending on implementation hardware. These findings demonstrate that the proposed method is a reliable and adaptive MPPT solution for PV systems operating in uncertain and dynamic environments. The novelty of this study lies in integrating Gaussian Process based state estimation with MH-MCMC hyperparameter inference for MPPT, enabling accurate and adaptive tracking without manual tuning of the system or noise parameters.</div></div>","PeriodicalId":50326,"journal":{"name":"International Journal of Electrical Power & Energy Systems","volume":"178 ","pages":"Article 111886"},"PeriodicalIF":5.0,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147854015","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Joint optimization of offshore DC and onshore AC electrical systems for large-scale offshore wind power clusters integration","authors":"Yang Liu ,&nbsp;Cheng Hua ,&nbsp;Ruanming Huang ,&nbsp;Yaoliang Zhu ,&nbsp;Junda Yin","doi":"10.1016/j.ijepes.2026.111904","DOIUrl":"10.1016/j.ijepes.2026.111904","url":null,"abstract":"<div><div>With the scaling and deep-sea development of offshore wind power, offshore wind farm clusters (OWFC) integrate to multiple Point of Common Coupling (PCCs) in the onshore grid through DC transmission. The planning of OWFC integration is impacted by numerous factors arising from the offshore and onshore electrical systems interlinkage. This paper investigates the pivotal elements implicated in onshore and offshore systems interlinkage and elucidates the convoluted challenges inherent to the integration systems planning. A decoupled hierarchical optimization model is formulated to optimize the collection system in each wind farm, the transmission system between wind farms, and the onshore and offshore grid interconnection simultaneously. An engineering case that focuses on the OWFC of Jiangsu Province, China integrating to a modified IEEE 118 node system is discussed to illustrate the effectiveness of the proposed methodology. The case study shows that the proposed methodology not only minimizes the investment costs of offshore electrical systems but also decreases the expansion and operational costs of onshore grids. Furthermore, it augments the flexible regulation capacity for the grid-connection of OWFC, facilitating the efficient consumption of large-scale offshore wind power.</div></div>","PeriodicalId":50326,"journal":{"name":"International Journal of Electrical Power & Energy Systems","volume":"178 ","pages":"Article 111904"},"PeriodicalIF":5.0,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147854102","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Physics-Inspired adaptive virtual inertia control for interconnected Multi-Voltage DC microgrids","authors":"Asghar Eskandari ,&nbsp;Reza Noroozian ,&nbsp;Kumars Rouzbehi ,&nbsp;Seyed Hossein Rouhani","doi":"10.1016/j.ijepes.2026.111913","DOIUrl":"10.1016/j.ijepes.2026.111913","url":null,"abstract":"<div><div>In conventional power grids, inertia provided by rotating machines acts as an instantaneous energy storage source and plays a crucial role in maintaining frequency and grid stability. However, in DC micro-grid (DCMGs) based on renewable energy resources, natural inertia is absent. This lack of inertia can lead to voltage instability, poor response to sudden load changes, control challenges, and the need for energy storage systems. In this paper, two islanded DCMGs with different voltage levels are studied, which are interconnected through a bidirectional DC/DC interconnected converter (IC). The proposed power converter, using a novel control method based on physics-inspired Adaptive Virtual Inertia Control (AVIC), is capable of not only accurate power sharing between the two DCMGs but also compensating for the inertia deficiency of the DCMGs, stabilizing the DC voltages on both sides of the DC/DC-IC at their reference values, and mitigating interactions between DCMGs. In addition, a stability analysis and control parameters design are presented. Each DCMG presented in this paper is supplied by four different Distributed Generation (DG) units, Battery Energy Storage Systems (BESS), AC, and DC load units. Simulation results obtained in MATLAB/Simulink and conducted real-time experiments on an OPAL-RT platform demonstrate and validate the effectiveness of the proposed control strategy for DCMG interconnected systems.</div></div>","PeriodicalId":50326,"journal":{"name":"International Journal of Electrical Power & Energy Systems","volume":"178 ","pages":"Article 111913"},"PeriodicalIF":5.0,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147854112","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Risk hedging against extreme weather through LLM-driven power insurance-futures portfolios","authors":"Zhe Wang,&nbsp;Houqi Chen,&nbsp;Xitian Wang,&nbsp;Da Xie","doi":"10.1016/j.ijepes.2026.111880","DOIUrl":"10.1016/j.ijepes.2026.111880","url":null,"abstract":"<div><div>Global climate change has led to frequent extreme weather events, exacerbating supply–demand imbalances and price volatility in power systems. Traditional risk management methods predominantly rely on statistical modeling and single financial instruments, making them inadequate for effectively addressing power shortages and electricity price risks under extreme scenarios. This paper proposes an intelligent financial hedging framework based on Large Language Models (LLMs) that synergistically applies insurance and futures portfolios to electricity markets under extreme weather conditions. First, we construct a CNN-LSTM-Attention prediction model that integrates physical mechanism constraints to achieve medium- to long-term forecasting of power shortages and uncertainty quantification. Second, we design an LLM-driven insurance-futures collaborative decision mechanism, which translates multi-source unstructured information (e.g., insurance clauses and market reports) into quantifiable strategy parameters through semantic understanding, thereby enabling adaptive optimization of insurance coverage and futures positions. Furthermore, we introduce a multi-objective Pareto optimization framework to achieve dynamic balance among risk coverage rate, cost-effectiveness, and return stability. Empirical results using the German electricity market as a case study demonstrate that the proposed framework achieves a 94.8% risk coverage rate under extreme high-temperature scenarios while significantly enhancing the economic efficiency and resilience of the strategy. The research indicates that LLMs can effectively bridge semantic risk identification with quantitative financial allocation, enhancing the intelligence of electricity risk hedging and providing a novel solution for market stability and energy transition under extreme weather.</div></div>","PeriodicalId":50326,"journal":{"name":"International Journal of Electrical Power & Energy Systems","volume":"178 ","pages":"Article 111880"},"PeriodicalIF":5.0,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147854111","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Radial basis function neural network-based sliding mode active disturbance rejection control for wind turbine pitch angle","authors":"Tiangui Zhang ,&nbsp;Guishan Yan ,&nbsp;Mingkun Yang ,&nbsp;Xianhang Liu ,&nbsp;Xuewei Wang ,&nbsp;Binbin Hao ,&nbsp;Chao Ai","doi":"10.1016/j.ijepes.2026.111877","DOIUrl":"10.1016/j.ijepes.2026.111877","url":null,"abstract":"<div><div>High-precision pitch angle control of wind turbines is critically important for maximizing wind energy conversion efficiency and ensuring stable grid integration, yet it faces significant challenges due to high-inertia blade dynamics and strong nonlinear disturbances inherent in electro-hydraulic servo pump control (EHA) actuators. To address these challenges, this paper proposes a sliding mode active disturbance rejection control (ADRC) strategy with radial basis function (RBF) neural network compensation. Specifically, a velocity-saturated tracking differentiator is designed to respect safe angular velocity and acceleration limits; the conventional nonlinear state error feedback is replaced by a fast terminal sliding mode law to enhance robustness and convergence; and an RBF neural network with adaptive weight update is employed to online approximate unknown system nonlinearities, while the extended state observer estimates external disturbances in real time. Simulation and experimental results on a ground-based test bench show that, under step command and random external disturbances, the proposed method achieves nearly zero overshoot (0.7°), a steady-state accuracy within ± 0.5°, and a rise time of 11.87 s. In comparison, conventional PID control yields 4.1° overshoot and ± 2° accuracy, while traditional ADRC gives 2.2° overshoot and ± 1.3° accuracy. These results lead to the conclusion that the proposed neural-network-compensated sliding mode ADRC significantly outperforms both PID and conventional ADRC in terms of overshoot reduction, steady-state precision, and disturbance rejection, offering a practical and high-performance solution for hydraulic wind turbine pitch systems under strong nonlinearities and high-inertia conditions.</div></div>","PeriodicalId":50326,"journal":{"name":"International Journal of Electrical Power & Energy Systems","volume":"178 ","pages":"Article 111877"},"PeriodicalIF":5.0,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147854115","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Digital twin-enabled time-frequency-aware dual-graph collaboration for dynamic multi-dimensional risk identification of topology mutations in direct current microgrids","authors":"Chenxi Jia ,&nbsp;Longyue Yang ,&nbsp;Wei Jin ,&nbsp;Jifeng Zhao ,&nbsp;Chuanjin Zhang ,&nbsp;Yutan Li","doi":"10.1016/j.ijepes.2026.111898","DOIUrl":"10.1016/j.ijepes.2026.111898","url":null,"abstract":"<div><div>The large-scale integration of renewable energy exposes direct current microgrids to concealed multi-dimensional dynamic risks induced by topology mutations, yet existing methods inadequately capture frequency-domain features, struggle with dynamic risk propagation modeling, suffer from high sensing latency, and lack physical constraint integration. To address these challenges, this study proposes a digital twin-enabled time–frequency-aware dual-graph collaborative approach for identifying multi-dimensional dynamic risks in direct current microgrids. The method leverages discrete wavelet transform within the digital twin virtual replica to separate trend and transient components, employs a frequency-domain attention mechanism for differentiated feature encoding, and constructs a parallel dual-graph structure comprising a physical topology graph and a dynamic risk propagation graph. An end-to-end dynamic graph neural network framework integrates feature fusion, dual-graph collaboration, and sequence learning to optimize the perception-representation-decision workflow. Experimental results demonstrate that the proposed method achieves 97.9% and 94.8% accuracy on balanced and unbalanced datasets, respectively, with an average sensing latency of 8.125 ms. Under low signal-to-noise ratio conditions, the F1-score decay rate is reduced to 8.3%, and hardware-in-the-loop tests verify an accuracy of 95.3%. This work advances digital twin technology from state mapping to multi-dimensional risk cognition, providing essential technical support for risk-aware decision making in renewable energy-dominated power systems.</div></div>","PeriodicalId":50326,"journal":{"name":"International Journal of Electrical Power & Energy Systems","volume":"178 ","pages":"Article 111898"},"PeriodicalIF":5.0,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147826875","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Stability on variable-speed pumped storage plant with full-size converter under fast power control mode in turbine condition: influence laws, deviation recognition, and quantitative evaluation","authors":"Peilin Wu ,&nbsp;Weijia Yang ,&nbsp;Xudong Li ,&nbsp;Zhecheng Wang ,&nbsp;Yiwen Liao ,&nbsp;Huabo Shi ,&nbsp;Yufei Teng","doi":"10.1016/j.ijepes.2026.111910","DOIUrl":"10.1016/j.ijepes.2026.111910","url":null,"abstract":"<div><div>The variable-speed pumped storage plant with full-size converter under fast power control mode is characterized by exceptional power regulation performance. However, its rotational speed and grid frequency decoupling will cause speed instability during small power disturbances under grid-connected operation, which is absent in fixed-speed units. Therefore, this paper investigates the stability of VSPSP with FSC. (1) Influence laws: Analyze influence laws of time constants on stability regions through the state matrix. (2) Deviation recognition: Recognize stability region deviation of simplified and detailed models through the stability margin. (3) Quantitative evaluation: Propose a method considering hydraulic-mechanical-electrical to evaluate the stability performance. This study applies a pumped storage plant as the engineering case, and the following conclusions demonstrate: (1) Reveal the matching laws of time constants to the stability region. (2) The critical stability margin value (<em>m</em>) is calculated to ensure that parameters of the simplified model derived theoretically maintain detailed model stability. In this case, the critical value (<em>m</em>) is 0.21. (3) Achieve favorable selection of governor parameters based on the evaluation method. These conclusions provide recommendations for matching the parameters between the controller and the controlled system for the VSPSP with FSC under the fast power control mode for stability.</div></div>","PeriodicalId":50326,"journal":{"name":"International Journal of Electrical Power & Energy Systems","volume":"178 ","pages":"Article 111910"},"PeriodicalIF":5.0,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147854017","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Distributed event-triggered control of CPLs in 3P-3L converter-based DC microgrids with time-varying delay and mixed noises","authors":"Long Chen ,&nbsp;Xiaojiao Chen ,&nbsp;Liansheng Huang ,&nbsp;Sheng Dou ,&nbsp;Xiuqing Zhang ,&nbsp;Shiying He ,&nbsp;Zejing Wang","doi":"10.1016/j.ijepes.2026.111902","DOIUrl":"10.1016/j.ijepes.2026.111902","url":null,"abstract":"<div><div>To address the challenges arising from the use of novel three-level converters and constant power loads in large-scale scientific DC power systems, this paper proposes a distributed secondary control strategy based on an averaged model and a communication-on-demand mechanism. Information exchange is triggered only when the local error exceeds a predefined threshold. A maximum triggering interval is also introduced to exclude Zeno behavior. To analyze stability, a mode decomposition approach is adopted. Specifically, the secondary control error vector is decomposed into mutually independent average and disagreement modes using the orthogonal eigenvectors of the Laplacian matrix associated with the communication topology. For the disagreement mode, time-varying delays, multiplicative noise, and triggering errors are modeled within a standard stochastic time-delay framework. An appropriate Lyapunov–Krasovskii functional incorporating delay terms is constructed and combined with stochastic differential analysis. Based on this formulation, sufficient conditions are derived to ensure that the disagreement mode remains bounded under disturbances and decays rapidly in a statistical sense, thereby guaranteeing consensus among all nodes. Explicit expressions are derived for the admissible upper bounds on the time delay, the noise intensity, and the secondary control gain. The trade-offs among these parameters are also analyzed in detail. For the average mode, linear matrix inequalities are used to show that the bus voltage can be restored to and maintained at its nominal value. In addition, a charge-averaging-based suppression scheme is proposed to mitigate the midpoint potential imbalance inherent in three-level converters. Comprehensive simulation results validate the theoretical analysis and demonstrate that the proposed strategy improves robustness against time delays and mixed noise.</div></div>","PeriodicalId":50326,"journal":{"name":"International Journal of Electrical Power & Energy Systems","volume":"178 ","pages":"Article 111902"},"PeriodicalIF":5.0,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147854114","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Robust disturbance suppression and time-delay tolerant analysis for load frequency control systems with electric vehicles and battery energy storage","authors":"Jing He ,&nbsp;Yilun Cai ,&nbsp;Chong Liu ,&nbsp;Zongfang Ma","doi":"10.1016/j.ijepes.2026.111908","DOIUrl":"10.1016/j.ijepes.2026.111908","url":null,"abstract":"<div><div>The integration of renewables and load fluctuations intensifies power system disturbances, while communication delays challenge load frequency control. Traditional synchronous generator-based systems respond inadequately to such fluctuations. Furthermore, existing analysis methods lack synergy between Lyapunov–Krasovskii functional construction and inequality estimation, underutilizing delay and state information and thus yielding conservative criteria. To address these issues, this paper proposes a new delayed load frequency control model with coordinated frequency regulation by the electric vehicle aggregator and the battery energy storage system to enhance the disturbance suppression ability, in which the battery energy storage system is modeled based on the <span><math><mrow><mi>Δ</mi><mi>SOC</mi></mrow></math></span> feedback droop control, which precisely characterizes the actual operation. Then, by effectively coordinating the Lyapunov–Krasovskii functional with the inequality and incorporating more system and delay information, less conservative criteria for robust disturbance suppression and time-delay tolerance analysis are proposed. Finally, the validity and superiority of the proposed method are verified through Hardware-in-the-Loop real-time simulations and virtual simulations, with results demonstrating that it achieves smaller <span><math><msub><mrow><mi>H</mi></mrow><mrow><mi>∞</mi></mrow></msub></math></span> performance index and larger admissible delay upper bounds.</div></div>","PeriodicalId":50326,"journal":{"name":"International Journal of Electrical Power & Energy Systems","volume":"178 ","pages":"Article 111908"},"PeriodicalIF":5.0,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147854014","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A rapid assessment method of total supply capability in urban medium voltage distribution networks","authors":"Huijun Wang ,&nbsp;Qianzhi Zhang ,&nbsp;Jianmin Zhang ,&nbsp;Shousheng Zhao ,&nbsp;Naizheng Jin ,&nbsp;Chuangxin Guo","doi":"10.1016/j.ijepes.2026.111895","DOIUrl":"10.1016/j.ijepes.2026.111895","url":null,"abstract":"<div><div>Accurate assessment of Total Supply Capacity (TSC) is crucial for the planning of urban medium-voltage distribution networks (UMVDNs). However, due to the increasing complexity of feeder interconnections led by integration of numerous circuit breakers and switching stations, existing TSC assessment methods suffer from limited accuracy and low computational efficiency. To better handle the trade-off between accuracy and computational efficiency, this paper proposes a rapid TSC assessment method based on an equivalent two-layer topological model and a linearized model of UMVDNs. First, we propose an equivalent two-layer topological model to divide the UMVDNs into a substation layer and a feeder cluster layer with the aim of reducing the dimensions for network reconfiguration. Second, the power supply constraints of each layer are analyzed separately and coupled to formulate a mixed-integer nonlinear programming model (MINLP), where the TSC of UMVDNs can be evaluated under both transformer and feeder N–1 contingencies for more accurate results. We further linearize the original MINLP problem by a mixed-integer linear programming (MILP) model, which can be efficiently solved by the branch-and-bound method. Finally, we validate our proposed rapid TSC assessment method in a real meshed UMVDN system adopted from Shaoxing City, China, which contains more than 300 tie-lines and 140 loads. The simulation results show better accuracy and computational efficiency compared to the benchmark TSC assessment methods. Moreover, we quantitatively analyze the key factors of TSC and provide suggestions for optimal capacity planning of UMVDNs.</div></div>","PeriodicalId":50326,"journal":{"name":"International Journal of Electrical Power & Energy Systems","volume":"178 ","pages":"Article 111895"},"PeriodicalIF":5.0,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147854103","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}