Wind power generation is subjected to complex and variable meteorological conditions,resulting in intermittent and volatile power generation.Accurate wind power prediction plays a crucial role in enabling the power gr...Wind power generation is subjected to complex and variable meteorological conditions,resulting in intermittent and volatile power generation.Accurate wind power prediction plays a crucial role in enabling the power grid dispatching departments to rationally plan power transmission and energy storage operations.This enhances the efficiency of wind power integration into the grid.It allows grid operators to anticipate and mitigate the impact of wind power fluctuations,significantly improving the resilience of wind farms and the overall power grid.Furthermore,it assists wind farm operators in optimizing the management of power generation facilities and reducing maintenance costs.Despite these benefits,accurate wind power prediction especially in extreme scenarios remains a significant challenge.To address this issue,a novel wind power prediction model based on learning approach is proposed by integrating wavelet transform and Transformer.First,a conditional generative adversarial network(CGAN)generates dynamic extreme scenarios guided by physical constraints and expert rules to ensure realism and capture critical features of wind power fluctuations under extremeconditions.Next,thewavelet transformconvolutional layer is applied to enhance sensitivity to frequency domain characteristics,enabling effective feature extraction fromextreme scenarios for a deeper understanding of input data.The model then leverages the Transformer’s self-attention mechanism to capture global dependencies between features,strengthening its sequence modelling capabilities.Case analyses verify themodel’s superior performance in extreme scenario prediction by effectively capturing local fluctuation featureswhile maintaining a grasp of global trends.Compared to other models,it achieves R-squared(R^(2))as high as 0.95,and the mean absolute error(MAE)and rootmean square error(RMSE)are also significantly lower than those of othermodels,proving its high accuracy and effectiveness in managing complex wind power generation conditions.展开更多
Purely organic room-temperature phosphorescence(RTP)is current hotspot in the research fields of chemistry,biology,materials etc.Herein,we report that photo-thermal double response reversible ultralong RTP flexible el...Purely organic room-temperature phosphorescence(RTP)is current hotspot in the research fields of chemistry,biology,materials etc.Herein,we report that photo-thermal double response reversible ultralong RTP flexible elastic material with multicolor delayed fluorescence,which is constructed by 4-biphenylboronic acid(BOH),polyethylene glycol,2,2-bis(hydroxymethyl)propionic acid,isophorone diamine and isophorone diisocyanate copolymer.Importantly,the supramolecular phosphorescent elastomer not only exhibits extending RTP emission with a lifetime up to 1.21 s,but also gives a visible afterglow of 20 s via encapsulation of BOH unities by the deep cavities of hydroxypropyl-β-cyclodextrin(β-CD-HP)and in situ polymerization.Especially,after doping organic dyes(Fluorescein isothiocyanate,Sulforhodamine 101,Rhodamine B),supramolecular phosphorescent elastomer achieves multicolor delayed fluorescence realized by RTP energy transfer from phosphorescent donor to dye acceptors,which possesses reversible photo-thermal responsiveness and maintains high efficiency in delayed emission even after dozens of cycles.Present research provides a new approach for constructing multicolor delayed fluorescent supramolecular elastomers.展开更多
This paper is devoted to investigate the robust H∞sliding mode load frequency control(SMLFC) of multi-area power system with time delay. By taking into account stochastic disturbances induced by the integration of re...This paper is devoted to investigate the robust H∞sliding mode load frequency control(SMLFC) of multi-area power system with time delay. By taking into account stochastic disturbances induced by the integration of renewable energies,a new sliding surface function is constructed to guarantee the fast response and robust performance, then the sliding mode control law is designed to guarantee the reach ability of the sliding surface in a finite-time interval. The sufficient robust frequency stabilization result for multi-area power system with time delay is presented in terms of linear matrix inequalities(LMIs). Finally,a two-area power system is provided to illustrate the usefulness and effectiveness of the obtained results.展开更多
Ibrutinib is a first-line treatment drug for B-cell malignancies.However,resistance to ibrutinib has been reported due to BTKC481Smutation.Although PROTAC strategy is expected to overcome this clinical resistance,it h...Ibrutinib is a first-line treatment drug for B-cell malignancies.However,resistance to ibrutinib has been reported due to BTKC481Smutation.Although PROTAC strategy is expected to overcome this clinical resistance,it has limitations such as large molecular weight and moderate bioactivity,which restrict its potential clinical application.Herein,we report a new type of potent BTKC481S-targeting PROTAC degrader.Through design,computer-assisted optimization and SAR studies,we have developed a representative BTKC481Sdegrader L6 with a much smaller molecular weight and improved solubility.Notably,L6 demonstrates better BTK degrading activity and lower IC50value in ibrutinib-resistant cell line than the first-generation BTK degrader P13I.Optimization strategy of L6 provides a general approach in the development of PROTACs targeting BTK and other proteins for future study.展开更多
The construction of hydrogels with good mechanical properties and phosphorescent properties is full of challenges.Herein,we report a supramolecular phosphorescent hydrogel with long lifetime,high tensile strength and ...The construction of hydrogels with good mechanical properties and phosphorescent properties is full of challenges.Herein,we report a supramolecular phosphorescent hydrogel with long lifetime,high tensile strength and self-healing property,which can be easily constructed through in-situ thermalinitiated polymerization of isocyanatoethyl acrylate-modifiedβ-cyclodextrin(β-CD-DA)and acrylatemodified adamantane(Ad-DA),acrylic acid(AA),followed by the non-covalent association with carbon dots(CNDs).The lifetime of phosphorescent hydrogel can reach 1261 ms at room temperature,and the quantum yield is 11%.Importantly,through the efficient triplet to singlet Förster resonance energy transfer(TS-FRET),the phosphorescent hydrogel shows the good phosphorescence energy transfer property for organic dyes Rhodamine B and Eosin Y with the delayed fluorescence lifetime up to 730 ms and 585 ms as well as the energy transfer efficiency(Φ_(ET))up to 99.9%and 99.3%,respectively.Moreover,owing to the host-vip interactions betweenβ-CD-DA and Ad-DA,the three-dimensional cross-linked network phosphorescent hydrogel can be easily stretched to 18 times of its original length,and can achieve self-healing of the cut surfaces within 30 min.These results will expand the scope of phosphorescent materials and provide new ideas and opportunities for materials science.展开更多
This paper proposes an optimal day-ahead opti-mization schedule for gas-electric integrated energy system(IES)considering the bi-directional energy flow.The hourly topology of electric power system(EPS),natural gas sy...This paper proposes an optimal day-ahead opti-mization schedule for gas-electric integrated energy system(IES)considering the bi-directional energy flow.The hourly topology of electric power system(EPS),natural gas system(NGS),energy hubs(EH)integrated power to gas(P2G)unit,are modeled to minimize the day-ahead operation cost of IES.Then,a second-order cone programming(SOCP)method is utilized to solve the optimization problem,which is actually a mixed integer nonconvex and nonlinear programming issue.Besides,cutting planes are added to ensure the exactness of the global optimal solution.Finally,simulation results demonstrate that the proposed optimization schedule can provide a safe,effective and economical day-ahead scheduling scheme for gas-electric IES.展开更多
Regional photovoltaic(PV) power prediction plays an important role in power system planning and operation. To effectively improve the performance of prediction intervals(PIs) for very short-term regional PV outputs, a...Regional photovoltaic(PV) power prediction plays an important role in power system planning and operation. To effectively improve the performance of prediction intervals(PIs) for very short-term regional PV outputs, an efficient nonparametric probabilistic prediction method based on granulebased clustering(GC) and direct optimization programming(DOP) is proposed. First, GC is proposed to formulate and cluster the sample granules consisting of numerical weather prediction(NWP) and historical regional output data, for the enhanced hierarchical clustering performance. Then, to improve the accuracy of samples' utilization, an unbalanced extension is used to reconstruct the training samples consisting of power time series. After that, DOP is applied to quantify the output weights based on the optimal overall performance. Meanwhile, a balance coefficient is studied for the enhanced reliability of PIs. Finally, the proposed method is validated through multistep PIs based on the numerical comparison of real PV generation data.展开更多
The rapid increase in renewable energy integration brings with it a series of uncertainty to the transmission and distribution systems.In general,large-scale wind and solar power integration always cause short-term mi...The rapid increase in renewable energy integration brings with it a series of uncertainty to the transmission and distribution systems.In general,large-scale wind and solar power integration always cause short-term mismatch between generation and load demand because of their intermittent nature.The traditional way of dealing with this problem is to increase the spinning reserve,which is quite costly.In recent years,it has been proposed that part of the load can be controlled dynamically for frequency regulation with little impact on customers’living comfort.This paper proposes a hybrid dynamic demand control(DDC)strategy for the primary and secondary frequency regulation.In particular,the loads can not only arrest the sudden frequency drop,but also bring the frequency closer to the nominal value.With the proposed control strategy,the demand side can provide a fast and smooth frequency regulation service,thereby replacing some generation reserve to achieve a lower expense.展开更多
This paper proposes a new multi-area framework for unbalanced active distribution network(ADN) state estimation. Firstly, an innovative three-phase distributed generator(DG) model is presented to take the asymmetric c...This paper proposes a new multi-area framework for unbalanced active distribution network(ADN) state estimation. Firstly, an innovative three-phase distributed generator(DG) model is presented to take the asymmetric characteristics of DG three-phase outputs into consideration. Then a feasible method to set pseudo-measurements for unmonitored DGs is introduced. The states of DGs,together with the states of alternating current(AC) buses in ADNs, were estimated by using the weighted least squares(WLS) method. After that, the ADN was divided into several independent subareas. Based on the augmented Lagrangian method, this work proposes a fully distributed three-phase state estimator for the multi-area ADN.Finally, from the simulation results on the modified IEEE123-bus system, the effectiveness and applicability of the proposed methodology have been investigated and discussed.展开更多
Dear Editor,Animal models,most commonly mice,that lack a protein of interest play an important role in phenotypic and functional studies of a target gene,allowing researchers to answer various biological questions(Cha...Dear Editor,Animal models,most commonly mice,that lack a protein of interest play an important role in phenotypic and functional studies of a target gene,allowing researchers to answer various biological questions(Chaible et al,2010).At pre-sent,a variety of tools act at the DNA or RNA level to enable researchers to model gene function(and thus protein)deficiency,including nucleic acid based RNA interference(EI-bashir et al.,2001),antisense oligonucleotides(Schoch and Miller,2017),and genome editing-based CRISPR-Cas9(Doudna and Charpentier,2014)strategies.However,challenges remain.展开更多
Accurate regional wind power prediction plays an important role in the security and reliability of power systems.For the performance improvement of very short-term prediction intervals(PIs),a novel probabilistic predi...Accurate regional wind power prediction plays an important role in the security and reliability of power systems.For the performance improvement of very short-term prediction intervals(PIs),a novel probabilistic prediction method based on composite conditional nonlinear quantile regression(CCNQR)is proposed.First,the hierarchical clustering method based on weighted multivariate time series motifs(WMTSM)is studied to consider the static difference,dynamic difference,and meteorological difference of wind power time series.Then,the correlations are used as sample weights for the conditional linear programming(CLP)of CCNQR.To optimize the performance of PIs,a composite evaluation including the accuracy of PI coverage probability(PICP),the average width(AW),and the offsets of points outside PIs(OPOPI)is used to quantify the appropriate upper and lower bounds.Moreover,the adaptive boundary quantiles(ABQs)are quantified for the optimal performance of PIs.Finally,based on the real wind farm data,the superiority of the proposed method is verified by adequate comparisons with the conventional methods.展开更多
In this paper,a robust adaptive unscented Kalman filter(RAUKF)is developed to mitigate the unfavorable effects derived from uncertainties in noise and in the model.To address these issues,a robust M-estimator is first...In this paper,a robust adaptive unscented Kalman filter(RAUKF)is developed to mitigate the unfavorable effects derived from uncertainties in noise and in the model.To address these issues,a robust M-estimator is first utilized to update the measurement noise covariance.Next,to deal with the effects of model parameter errors while considering the computational complexity and real-time requirements of dynamic state estimation,an adaptive update method is produced.The proposed method is integrated with spherical simplex unscented transformation technology,and then a novel derivative-free filter is proposed to dynamically track the states of the power system against uncertainties.Finally,the effectiveness and robustness of the proposed method are demonstrated through extensive simulation experiments on an IEEE 39-bus test system.Compared with other methods,the proposed method can capture the dynamic characteristics of a synchronous generator more reliably.展开更多
To enhance the performance of the prediction intervals (PIs), a novel very short-term probabilistic prediction method for wind speed via nonlinear quantile regression (NQR) based on adaptive least absolute shrinkage a...To enhance the performance of the prediction intervals (PIs), a novel very short-term probabilistic prediction method for wind speed via nonlinear quantile regression (NQR) based on adaptive least absolute shrinkage and selection operator (ALASSO) and integrated criterion (IC) is proposed. The ALASSO method is studied for shrinkage of output weights and selection of variables. Furthermore, for the better performance of PIs, composite weighted linear programming (CWLP) is proposed to modify the conventional linear programming cost function of quantile regression (QR), by combining it with Bayesian information criterion (BIC) as an IC to optimize the coefficients of PIs. Then, the multiple fold cross model (MFCM) is utilized to improve the PIs performance. Multistep probabilistic prediction of 15-minute wind speed is performed based on the real wind farm data from the northeast of China. The effectiveness of the proposed approach is validated through the performances' comparisons with conventional methods.展开更多
Economic dispatch problem(EDP)is a fundamental optimization problem in power system operation,which aims at minimizing the total generation cost.In fact,the power grid is becoming a cyber-physical power system(CPPS).T...Economic dispatch problem(EDP)is a fundamental optimization problem in power system operation,which aims at minimizing the total generation cost.In fact,the power grid is becoming a cyber-physical power system(CPPS).Therefore,the quality of communication is a key point.In this paper,considering two important factors,i.e.,time delays and channel noises,a fully distributed consensus based algorithm is proposed for solving EDP.The critical maximum allowable upper bounds of heterogeneous communication delays and self-delays are obtained.It should be pointed out that the proposed algorithm can be robust against the time-varying delays and channel noises considering generator constraints.In addition,even with time-varying delays and channel noises,the power balance of supply and demand is not broken during the optimization.Several simulation studies are presented to validate the correctness and superiority of the developed results.展开更多
Macrocycle-induced formation of pure organic supramolecular aggregates is a challenge that has attracted considerable attention from researchers in the fields of chemistry,biology,and materials science.In particular,a...Macrocycle-induced formation of pure organic supramolecular aggregates is a challenge that has attracted considerable attention from researchers in the fields of chemistry,biology,and materials science.In particular,aggregation induced by water-soluble cyclodextrins and calixarenes,which are two classic of macrocycles with a hydrophobic cavity and a hydrophilic external surface,has attracted interest because these host molecules can form aggregates with vip molecules via various noncovalent interactions,including hydrophobic interactions,van der Waals forces,hydrogen bonds,and electrostatic interactions.In this review,we focus mainly on some impressive recent progress,both by our group and other groups,on the construction of cyclodextrin-and calixarene-based organic supramolecular aggregates,control of their topological morphology,and their use for biological applications such as molecular recognition and bioimaging,photodynamic therapy,light-harvesting energy transfer,and targeted drug delivery.We also discuss shortcomings of the current reported results and future prospects for the development of multifunctional organic supramolecular aggregates for use in various fields.展开更多
With the increasing demand for power system stability and resilience,effective real-time tracking plays a crucial role in smart grid synchronization.However,most studies have focused on measurement noise,while they se...With the increasing demand for power system stability and resilience,effective real-time tracking plays a crucial role in smart grid synchronization.However,most studies have focused on measurement noise,while they seldom think about the problem of measurement data loss in smart power grid synchronization.To solve this problem,a resilient fault-tolerant extended Kalman filter(RFTEKF)is proposed to track voltage amplitude,voltage phase angle and frequency dynamically.First,a threephase unbalanced network’s positive sequence fast estimation model is established.Then,the loss phenomenon of measurements occurs randomly,and the randomness of data loss’s randomness is defined by discrete interval distribution[0,1].Subsequently,a resilient fault-tolerant extended Kalman filter based on the real-time estimation framework is designed using the timestamp technique to acquire partial data loss information.Finally,extensive simulation results manifest the proposed RFTEKF can synchronize the smart grid more effectively than the traditional extended Kalman filter(EKF).展开更多
This paper develops an adaptive two-stage unscented Kalman filter(ATSUKF)to accurately track operation states of the synchronous generator(SG)under cyber attacks.To achieve high fidelity,considering the excitation sys...This paper develops an adaptive two-stage unscented Kalman filter(ATSUKF)to accurately track operation states of the synchronous generator(SG)under cyber attacks.To achieve high fidelity,considering the excitation system of SGs,a detailed 9~(th)-order SG model for dynamic state estimation is established.Then,for several common cyber attacks against measurements,a two-stage unscented Kalman filter is proposed to estimate the model state and the bias in parallel.Subsequently,to solve the deterioration problem of state estimation performance caused by the mismatch between noise statistical characteristics and model assumptions,a multi-dimensional adaptive factor matrix is derived to modify the noise covariance matrix.Finally,a large number of simulation experiments are carried out on the IEEE 39-bus system,which shows that the proposed filter can accurately track the SG state under different abnormal test conditions.展开更多
With the development of the smart grid,the distribution system operation conditions become more complex and changeable.Furthermore,due to the influence of observation outliers and uncertain noise statistics,it is more...With the development of the smart grid,the distribution system operation conditions become more complex and changeable.Furthermore,due to the influence of observation outliers and uncertain noise statistics,it is more difficult to grasp the dynamic operation characteristics of distribution system.In order to address these problems,by using projection statistics and the noise covariance updating technology based on the Sage-Husa noise estimator,for distribution power system with outliers and uncertain noise statistics,a robust adaptive cubature Kalman filter forecasting-aided state estimation method is proposed based on generalized-maximum likelihood type estimator.Furthermore,an adaptive strategy,which can enhance the filtering accuracy under normal conditions,is presented.In the simulation part,the branch parameters and node load parameters of the test system are appropriately modified to simulate the asymmetry of the three-phase branch parameters and the asymmetry of the three-phase loads.Finally,through simulation experiments on the improved test system,it is verified that the robust forecasting-aided state estimation method,presented in this paper,can effectively perceive the actual operating state of the distribution network in different simulation scenarios.展开更多
Photoredox-catalyzed aminoarylation and thioami-nation of unactivated alkenes have been developed,providing novel synthetic routes to access synthe-tically challenging quaternary carbon-centered benzoindolizidinones a...Photoredox-catalyzed aminoarylation and thioami-nation of unactivated alkenes have been developed,providing novel synthetic routes to access synthe-tically challenging quaternary carbon-centered benzoindolizidinones and trifluoromethylthiolated piperidines using readily available starting materials.Notably,these transformations were enabled by merging amidyl radical generation from N-alkyl benzamides with oxidant incorporation.Density functional theory calculations were performed to understand the reaction mechanism and to rationa-lize the regioselectivities.Moreover,the newly deve-loped catalytic aminoarylation provided a convenient synthetic route for natural product tylophorine and its gem-dimethyl analogues with greatly improved drug-like properties such as enhanced solubility and stability.展开更多
基金funded by the Science and Technology Project of State Grid Corporation of China under Grant No.5108-202218280A-2-299-XG.
文摘Wind power generation is subjected to complex and variable meteorological conditions,resulting in intermittent and volatile power generation.Accurate wind power prediction plays a crucial role in enabling the power grid dispatching departments to rationally plan power transmission and energy storage operations.This enhances the efficiency of wind power integration into the grid.It allows grid operators to anticipate and mitigate the impact of wind power fluctuations,significantly improving the resilience of wind farms and the overall power grid.Furthermore,it assists wind farm operators in optimizing the management of power generation facilities and reducing maintenance costs.Despite these benefits,accurate wind power prediction especially in extreme scenarios remains a significant challenge.To address this issue,a novel wind power prediction model based on learning approach is proposed by integrating wavelet transform and Transformer.First,a conditional generative adversarial network(CGAN)generates dynamic extreme scenarios guided by physical constraints and expert rules to ensure realism and capture critical features of wind power fluctuations under extremeconditions.Next,thewavelet transformconvolutional layer is applied to enhance sensitivity to frequency domain characteristics,enabling effective feature extraction fromextreme scenarios for a deeper understanding of input data.The model then leverages the Transformer’s self-attention mechanism to capture global dependencies between features,strengthening its sequence modelling capabilities.Case analyses verify themodel’s superior performance in extreme scenario prediction by effectively capturing local fluctuation featureswhile maintaining a grasp of global trends.Compared to other models,it achieves R-squared(R^(2))as high as 0.95,and the mean absolute error(MAE)and rootmean square error(RMSE)are also significantly lower than those of othermodels,proving its high accuracy and effectiveness in managing complex wind power generation conditions.
基金financially supported by the National Natural Science Foundation of China(No.22131008)。
文摘Purely organic room-temperature phosphorescence(RTP)is current hotspot in the research fields of chemistry,biology,materials etc.Herein,we report that photo-thermal double response reversible ultralong RTP flexible elastic material with multicolor delayed fluorescence,which is constructed by 4-biphenylboronic acid(BOH),polyethylene glycol,2,2-bis(hydroxymethyl)propionic acid,isophorone diamine and isophorone diisocyanate copolymer.Importantly,the supramolecular phosphorescent elastomer not only exhibits extending RTP emission with a lifetime up to 1.21 s,but also gives a visible afterglow of 20 s via encapsulation of BOH unities by the deep cavities of hydroxypropyl-β-cyclodextrin(β-CD-HP)and in situ polymerization.Especially,after doping organic dyes(Fluorescein isothiocyanate,Sulforhodamine 101,Rhodamine B),supramolecular phosphorescent elastomer achieves multicolor delayed fluorescence realized by RTP energy transfer from phosphorescent donor to dye acceptors,which possesses reversible photo-thermal responsiveness and maintains high efficiency in delayed emission even after dozens of cycles.Present research provides a new approach for constructing multicolor delayed fluorescent supramolecular elastomers.
基金supported in part by the National Natural Science Foundation of China(61673161)the Natural Science Foundation of Jiangsu Province of China(BK20161510)+2 种基金the Fundamental Research Funds for the Central Universities of China(2017B13914)the 111 Project(B14022)the Priority Academic Program Development of Jiangsu Higher Education Institutions(PAPD)
文摘This paper is devoted to investigate the robust H∞sliding mode load frequency control(SMLFC) of multi-area power system with time delay. By taking into account stochastic disturbances induced by the integration of renewable energies,a new sliding surface function is constructed to guarantee the fast response and robust performance, then the sliding mode control law is designed to guarantee the reach ability of the sliding surface in a finite-time interval. The sufficient robust frequency stabilization result for multi-area power system with time delay is presented in terms of linear matrix inequalities(LMIs). Finally,a two-area power system is provided to illustrate the usefulness and effectiveness of the obtained results.
基金supported by the National Natural Science Foundation of China(Nos.82125034,81773567)National Major Scientific and Technological Project(Nos.2020YFE0202200,2021YFA1300200 and 2021YFA1302100)Shuimu Tsinghua Scholar。
文摘Ibrutinib is a first-line treatment drug for B-cell malignancies.However,resistance to ibrutinib has been reported due to BTKC481Smutation.Although PROTAC strategy is expected to overcome this clinical resistance,it has limitations such as large molecular weight and moderate bioactivity,which restrict its potential clinical application.Herein,we report a new type of potent BTKC481S-targeting PROTAC degrader.Through design,computer-assisted optimization and SAR studies,we have developed a representative BTKC481Sdegrader L6 with a much smaller molecular weight and improved solubility.Notably,L6 demonstrates better BTK degrading activity and lower IC50value in ibrutinib-resistant cell line than the first-generation BTK degrader P13I.Optimization strategy of L6 provides a general approach in the development of PROTACs targeting BTK and other proteins for future study.
基金National Natural Science Foundation of China(NNSFC,No.22131008)the Haihe Laboratory of Sustainable Chemical Transformations for financial support.
文摘The construction of hydrogels with good mechanical properties and phosphorescent properties is full of challenges.Herein,we report a supramolecular phosphorescent hydrogel with long lifetime,high tensile strength and self-healing property,which can be easily constructed through in-situ thermalinitiated polymerization of isocyanatoethyl acrylate-modifiedβ-cyclodextrin(β-CD-DA)and acrylatemodified adamantane(Ad-DA),acrylic acid(AA),followed by the non-covalent association with carbon dots(CNDs).The lifetime of phosphorescent hydrogel can reach 1261 ms at room temperature,and the quantum yield is 11%.Importantly,through the efficient triplet to singlet Förster resonance energy transfer(TS-FRET),the phosphorescent hydrogel shows the good phosphorescence energy transfer property for organic dyes Rhodamine B and Eosin Y with the delayed fluorescence lifetime up to 730 ms and 585 ms as well as the energy transfer efficiency(Φ_(ET))up to 99.9%and 99.3%,respectively.Moreover,owing to the host-vip interactions betweenβ-CD-DA and Ad-DA,the three-dimensional cross-linked network phosphorescent hydrogel can be easily stretched to 18 times of its original length,and can achieve self-healing of the cut surfaces within 30 min.These results will expand the scope of phosphorescent materials and provide new ideas and opportunities for materials science.
基金This work was supported in part by the National Natural Science Foundation of China under Grants 61673161 and 51807134and in part by the program of fundamental research of the Siberian Branch of Russian Academy of Sciences and carried out within the framework of the research project III.17.3.1,Reg.No.AAAA-A17-117030310442-8.
文摘This paper proposes an optimal day-ahead opti-mization schedule for gas-electric integrated energy system(IES)considering the bi-directional energy flow.The hourly topology of electric power system(EPS),natural gas system(NGS),energy hubs(EH)integrated power to gas(P2G)unit,are modeled to minimize the day-ahead operation cost of IES.Then,a second-order cone programming(SOCP)method is utilized to solve the optimization problem,which is actually a mixed integer nonconvex and nonlinear programming issue.Besides,cutting planes are added to ensure the exactness of the global optimal solution.Finally,simulation results demonstrate that the proposed optimization schedule can provide a safe,effective and economical day-ahead scheduling scheme for gas-electric IES.
基金supported by the National Natural Science Foundation of China (No. 62073121)the National Key R&D Program of China “Technology and application of wind power/photovoltaic power prediction for promoting renewable energy consumption”(No. 2018YFB0904200)eponymous Complement S&T Program of State Grid Corporation of China (No. SGLNDKOOKJJS1800266)。
文摘Regional photovoltaic(PV) power prediction plays an important role in power system planning and operation. To effectively improve the performance of prediction intervals(PIs) for very short-term regional PV outputs, an efficient nonparametric probabilistic prediction method based on granulebased clustering(GC) and direct optimization programming(DOP) is proposed. First, GC is proposed to formulate and cluster the sample granules consisting of numerical weather prediction(NWP) and historical regional output data, for the enhanced hierarchical clustering performance. Then, to improve the accuracy of samples' utilization, an unbalanced extension is used to reconstruct the training samples consisting of power time series. After that, DOP is applied to quantify the output weights based on the optimal overall performance. Meanwhile, a balance coefficient is studied for the enhanced reliability of PIs. Finally, the proposed method is validated through multistep PIs based on the numerical comparison of real PV generation data.
基金supported by the Engineering Research Center Program of the National Science Foundationthe Department of Energy of USA under NSF Award Number EEC-1041877the CURENT Industry Partnership Program.
文摘The rapid increase in renewable energy integration brings with it a series of uncertainty to the transmission and distribution systems.In general,large-scale wind and solar power integration always cause short-term mismatch between generation and load demand because of their intermittent nature.The traditional way of dealing with this problem is to increase the spinning reserve,which is quite costly.In recent years,it has been proposed that part of the load can be controlled dynamically for frequency regulation with little impact on customers’living comfort.This paper proposes a hybrid dynamic demand control(DDC)strategy for the primary and secondary frequency regulation.In particular,the loads can not only arrest the sudden frequency drop,but also bring the frequency closer to the nominal value.With the proposed control strategy,the demand side can provide a fast and smooth frequency regulation service,thereby replacing some generation reserve to achieve a lower expense.
基金supported by National Natural Science Foundation of China(No.51277052)
文摘This paper proposes a new multi-area framework for unbalanced active distribution network(ADN) state estimation. Firstly, an innovative three-phase distributed generator(DG) model is presented to take the asymmetric characteristics of DG three-phase outputs into consideration. Then a feasible method to set pseudo-measurements for unmonitored DGs is introduced. The states of DGs,together with the states of alternating current(AC) buses in ADNs, were estimated by using the weighted least squares(WLS) method. After that, the ADN was divided into several independent subareas. Based on the augmented Lagrangian method, this work proposes a fully distributed three-phase state estimator for the multi-area ADN.Finally, from the simulation results on the modified IEEE123-bus system, the effectiveness and applicability of the proposed methodology have been investigated and discussed.
文摘Dear Editor,Animal models,most commonly mice,that lack a protein of interest play an important role in phenotypic and functional studies of a target gene,allowing researchers to answer various biological questions(Chaible et al,2010).At pre-sent,a variety of tools act at the DNA or RNA level to enable researchers to model gene function(and thus protein)deficiency,including nucleic acid based RNA interference(EI-bashir et al.,2001),antisense oligonucleotides(Schoch and Miller,2017),and genome editing-based CRISPR-Cas9(Doudna and Charpentier,2014)strategies.However,challenges remain.
基金This work was supported by the National Key R&D Program of China“Technology and Application of Wind Power/Photovoltaic Power Prediction for Promoting Renewable Energy Consumption”(No.2018YFB0904200)Complement S&T Program of State Grid Corporation of China(No.SGLNDKOOKJJS1800266).
文摘Accurate regional wind power prediction plays an important role in the security and reliability of power systems.For the performance improvement of very short-term prediction intervals(PIs),a novel probabilistic prediction method based on composite conditional nonlinear quantile regression(CCNQR)is proposed.First,the hierarchical clustering method based on weighted multivariate time series motifs(WMTSM)is studied to consider the static difference,dynamic difference,and meteorological difference of wind power time series.Then,the correlations are used as sample weights for the conditional linear programming(CLP)of CCNQR.To optimize the performance of PIs,a composite evaluation including the accuracy of PI coverage probability(PICP),the average width(AW),and the offsets of points outside PIs(OPOPI)is used to quantify the appropriate upper and lower bounds.Moreover,the adaptive boundary quantiles(ABQs)are quantified for the optimal performance of PIs.Finally,based on the real wind farm data,the superiority of the proposed method is verified by adequate comparisons with the conventional methods.
基金supported by the National Natural Science Foundation of China(No.62073121)the National Natural Science Foundation of China-State Grid Joint Fund for Smart Grid(No.U1966202)the Six Talent Peaks High Level Project of Jiangsu Province(No.2017-XNY-004)。
文摘In this paper,a robust adaptive unscented Kalman filter(RAUKF)is developed to mitigate the unfavorable effects derived from uncertainties in noise and in the model.To address these issues,a robust M-estimator is first utilized to update the measurement noise covariance.Next,to deal with the effects of model parameter errors while considering the computational complexity and real-time requirements of dynamic state estimation,an adaptive update method is produced.The proposed method is integrated with spherical simplex unscented transformation technology,and then a novel derivative-free filter is proposed to dynamically track the states of the power system against uncertainties.Finally,the effectiveness and robustness of the proposed method are demonstrated through extensive simulation experiments on an IEEE 39-bus test system.Compared with other methods,the proposed method can capture the dynamic characteristics of a synchronous generator more reliably.
基金the National Key R&D Program of China(Technology and application of wind power/photovoltaic power prediction for promoting renewable energy consumption,2018YFB0904200)eponymous Complement S&T Program of State Grid Corporation of China(SGLNDKOOKJJS1800266)。
文摘To enhance the performance of the prediction intervals (PIs), a novel very short-term probabilistic prediction method for wind speed via nonlinear quantile regression (NQR) based on adaptive least absolute shrinkage and selection operator (ALASSO) and integrated criterion (IC) is proposed. The ALASSO method is studied for shrinkage of output weights and selection of variables. Furthermore, for the better performance of PIs, composite weighted linear programming (CWLP) is proposed to modify the conventional linear programming cost function of quantile regression (QR), by combining it with Bayesian information criterion (BIC) as an IC to optimize the coefficients of PIs. Then, the multiple fold cross model (MFCM) is utilized to improve the PIs performance. Multistep probabilistic prediction of 15-minute wind speed is performed based on the real wind farm data from the northeast of China. The effectiveness of the proposed approach is validated through the performances' comparisons with conventional methods.
基金supported by the National Natural Science Foundation of China(No.61833008)the National Natural Science Foundation of China-State Grid Joint Fund for Smart Grid(No.U1966202)the Six Talent Peaks High Level Project of Jiangsu Province(No.2017-XNY-004).
文摘Economic dispatch problem(EDP)is a fundamental optimization problem in power system operation,which aims at minimizing the total generation cost.In fact,the power grid is becoming a cyber-physical power system(CPPS).Therefore,the quality of communication is a key point.In this paper,considering two important factors,i.e.,time delays and channel noises,a fully distributed consensus based algorithm is proposed for solving EDP.The critical maximum allowable upper bounds of heterogeneous communication delays and self-delays are obtained.It should be pointed out that the proposed algorithm can be robust against the time-varying delays and channel noises considering generator constraints.In addition,even with time-varying delays and channel noises,the power balance of supply and demand is not broken during the optimization.Several simulation studies are presented to validate the correctness and superiority of the developed results.
基金National Natural Science Foundation of China,Grant/Award Numbers:21807038,21772099,21861132001China Postdoctoral Science Foundation,Grant/Award Number:2019M651006。
文摘Macrocycle-induced formation of pure organic supramolecular aggregates is a challenge that has attracted considerable attention from researchers in the fields of chemistry,biology,and materials science.In particular,aggregation induced by water-soluble cyclodextrins and calixarenes,which are two classic of macrocycles with a hydrophobic cavity and a hydrophilic external surface,has attracted interest because these host molecules can form aggregates with vip molecules via various noncovalent interactions,including hydrophobic interactions,van der Waals forces,hydrogen bonds,and electrostatic interactions.In this review,we focus mainly on some impressive recent progress,both by our group and other groups,on the construction of cyclodextrin-and calixarene-based organic supramolecular aggregates,control of their topological morphology,and their use for biological applications such as molecular recognition and bioimaging,photodynamic therapy,light-harvesting energy transfer,and targeted drug delivery.We also discuss shortcomings of the current reported results and future prospects for the development of multifunctional organic supramolecular aggregates for use in various fields.
基金supported in part by the National Natural Science Foundation of China under Grant 62203395in part by the Natural Science Foundation of Henan under Grant 242300421167in part by the China Postdoctoral Science Foundation under Grant 2023TQ0306.
文摘With the increasing demand for power system stability and resilience,effective real-time tracking plays a crucial role in smart grid synchronization.However,most studies have focused on measurement noise,while they seldom think about the problem of measurement data loss in smart power grid synchronization.To solve this problem,a resilient fault-tolerant extended Kalman filter(RFTEKF)is proposed to track voltage amplitude,voltage phase angle and frequency dynamically.First,a threephase unbalanced network’s positive sequence fast estimation model is established.Then,the loss phenomenon of measurements occurs randomly,and the randomness of data loss’s randomness is defined by discrete interval distribution[0,1].Subsequently,a resilient fault-tolerant extended Kalman filter based on the real-time estimation framework is designed using the timestamp technique to acquire partial data loss information.Finally,extensive simulation results manifest the proposed RFTEKF can synchronize the smart grid more effectively than the traditional extended Kalman filter(EKF).
基金supported by the National Natural Science Foundation of China(No.62073121)the National Natural Science Foundation of China-State Grid Joint Fund for Smart Grid(No.U1966202)+1 种基金the Six Talent Peaks High Level Project of Jiangsu Province(No.2017-XNY-004)the Natural Sciences and Engineering Research Council(NSERC)of Canada。
文摘This paper develops an adaptive two-stage unscented Kalman filter(ATSUKF)to accurately track operation states of the synchronous generator(SG)under cyber attacks.To achieve high fidelity,considering the excitation system of SGs,a detailed 9~(th)-order SG model for dynamic state estimation is established.Then,for several common cyber attacks against measurements,a two-stage unscented Kalman filter is proposed to estimate the model state and the bias in parallel.Subsequently,to solve the deterioration problem of state estimation performance caused by the mismatch between noise statistical characteristics and model assumptions,a multi-dimensional adaptive factor matrix is derived to modify the noise covariance matrix.Finally,a large number of simulation experiments are carried out on the IEEE 39-bus system,which shows that the proposed filter can accurately track the SG state under different abnormal test conditions.
基金partially supported by the National Natural Science Foundation of China under Grant 62073121partially supported by National Natural Science Foundation of China-State Grid Joint Fund for Smart Grid under Grant U1966202partially supported by Six Talent Peaks High Level Project of Jiangsu Province under Grant 2017-XNY-004.
文摘With the development of the smart grid,the distribution system operation conditions become more complex and changeable.Furthermore,due to the influence of observation outliers and uncertain noise statistics,it is more difficult to grasp the dynamic operation characteristics of distribution system.In order to address these problems,by using projection statistics and the noise covariance updating technology based on the Sage-Husa noise estimator,for distribution power system with outliers and uncertain noise statistics,a robust adaptive cubature Kalman filter forecasting-aided state estimation method is proposed based on generalized-maximum likelihood type estimator.Furthermore,an adaptive strategy,which can enhance the filtering accuracy under normal conditions,is presented.In the simulation part,the branch parameters and node load parameters of the test system are appropriately modified to simulate the asymmetry of the three-phase branch parameters and the asymmetry of the three-phase loads.Finally,through simulation experiments on the improved test system,it is verified that the robust forecasting-aided state estimation method,presented in this paper,can effectively perceive the actual operating state of the distribution network in different simulation scenarios.
基金This study was funded by the National“973”grant from the Ministry of Science and Technology(grant no.2011CB965300)National Natural Science Foundation of China(grant nos.21232001 and 21302106)+1 种基金National Science and Technology Major Project(grant no.2018ZX09711001)Tsinghua University Initiative Scientific Research Program.
文摘Photoredox-catalyzed aminoarylation and thioami-nation of unactivated alkenes have been developed,providing novel synthetic routes to access synthe-tically challenging quaternary carbon-centered benzoindolizidinones and trifluoromethylthiolated piperidines using readily available starting materials.Notably,these transformations were enabled by merging amidyl radical generation from N-alkyl benzamides with oxidant incorporation.Density functional theory calculations were performed to understand the reaction mechanism and to rationa-lize the regioselectivities.Moreover,the newly deve-loped catalytic aminoarylation provided a convenient synthetic route for natural product tylophorine and its gem-dimethyl analogues with greatly improved drug-like properties such as enhanced solubility and stability.
