Low-carbon generation expansion planning considering uncertainty of renewable energy at multi-time scales

With the development of carbon electricity,achieving a low-carbon economy has become a prevailing and inevitable trend.Improving low-carbon expansion generation planning is critical for carbon emission mitigation and a lowcarbon economy.In this paper,a two-layer low-carbon expansion generation planning approach considering the uncertainty of renewable energy at multiple time scales is proposed.First,renewable energy sequences considering the uncertainty in multiple time scales are generated based on the Copula function and the probability distribution of renewable energy.Second,a two-layer generation planning model considering carbon trading and carbon capture technology is established.Specifically,the upper layer model optimizes the investment decision considering the uncertainty at a monthly scale,and the lower layer one optimizes the scheduling considering the peak shaving at an hourly scale and the flexibility at a 15-minute scale.Finally,the results of different influence factors on low-carbon generation expansion planning are compared in a provincial power grid,which demonstrate the effectiveness of the proposed model.

Multi-Time Scale Optimal Scheduling of a Photovoltaic Energy Storage Building System Based on Model Predictive Control

Building emission reduction is an important way to achieve China’s carbon peaking and carbon neutrality goals.Aiming at the problem of low carbon economic operation of a photovoltaic energy storage building system,a multi-time scale optimal scheduling strategy based on model predictive control(MPC)is proposed under the consideration of load optimization.First,load optimization is achieved by controlling the charging time of electric vehicles as well as adjusting the air conditioning operation temperature,and the photovoltaic energy storage building system model is constructed to propose a day-ahead scheduling strategy with the lowest daily operation cost.Second,considering inter-day to intra-day source-load prediction error,an intraday rolling optimal scheduling strategy based on MPC is proposed that dynamically corrects the day-ahead dispatch results to stabilize system power fluctuations and promote photovoltaic consumption.Finally,taking an office building on a summer work day as an example,the effectiveness of the proposed scheduling strategy is verified.The results of the example show that the strategy reduces the total operating cost of the photovoltaic energy storage building system by 17.11%,improves the carbon emission reduction by 7.99%,and the photovoltaic consumption rate reaches 98.57%,improving the system’s low-carbon and economic performance.

Bio-Inspired Optimal Dispatching of Wind Power Consumption Considering Multi-Time Scale Demand Response and High-Energy Load Participation

Bio-inspired computer modelling brings solutions fromthe living phenomena or biological systems to engineering domains.To overcome the obstruction problem of large-scale wind power consumption in Northwest China,this paper constructs a bio-inspired computer model.It is an optimal wind power consumption dispatching model of multi-time scale demand response that takes into account the involved high-energy load.First,the principle of wind power obstruction with the involvement of a high-energy load is examined in this work.In this step,highenergy load model with different regulation characteristics is established.Then,considering the multi-time scale characteristics of high-energy load and other demand-side resources response speed,a multi-time scale model of coordination optimization is built.An improved bio-inspired model incorporating particle swarm optimization is applied to minimize system operation and wind curtailment costs,as well as to find the most optimal energy configurationwithin the system.Lastly,we take an example of regional power grid in Gansu Province for simulation analysis.Results demonstrate that the suggested scheduling strategy can significantly enhance the wind power consumption level and minimize the system’s operational cost.

Multi-time scale analysis of precipitation variation in Guyuan, China:1957-2005

Morlet wavelet transformation is used in this paper to analyze the multi time scale characteristics of pre cipitation data series from 1957 to 2005 in Guyuan region.The results showed that(1) the annual precipitation evo lution process had obvious multi time scale variation characteristics of 15 25 years,7 12 years and 3 6 years,and different time scales had different oscillation energy densities;(2) the periods at smaller time scales changed more frequently,which often nested in a biggish quasi periodic oscillations,so the concrete time domain should be ana lyzed if necessary;(3) the precipitation had three main periods(22 year,9 year and 4 year) and the 22 year period was especially outstanding,and the analysis of this main period reveals that the precipitation would be in a relative high water period until about 2012.

Research on multi-time scale doubly-fed wind turbine test system based on FPGA+CPU heterogeneous calculation

As the proportion of renewable energy increases, the interaction between renewable energy devices and the grid continues to enhance. Therefore, the renewable energy dynamic test in a power system has become more and more important. Traditional dynamic simulation systems and digital-analog hybrid simulation systems are difficult to compromise on the economy, flexibility and accuracy. A multi-time scale test system of doubly fed induction generator based on FPGA+ CPU heterogeneous calculation is proposed in this paper. The proposed test system is based on the ADPSS simulation platform. The power circuit part of the test system is setup up using the EMT(electromagnetic transient simulation) simulation, and the control part uses the actual physical devices. In order to realize the close-loop testing for the physical devices, the power circuit must be simulated in real-time. This paper proposes a multi-time scale simulation algorithm, in which the decoupling component divides the power circuit into a large time scale system and a small time scale system in order to reduce computing effort. This paper also proposes the FPGA+CPU heterogeneous computing architecture for implementing this multitime scale simulation. In FPGA, there is a complete small time-scale EMT engine, which support the flexibly circuit modeling with any topology. Finally, the test system is connected to an DFIG controller based on Labview to verify the feasibility of the test system.

Psychometric properties of the Chinese version of the Parent Perception of Uncertainty Scale(PPUS)among parents of children with cancer diagnosis

Objective:Parents of children diagnosed with cancer often experience high levels of illness uncertainty.This study evaluated the psychometric properties of the Chinese Version of the Parent Perception of Uncertainty Scale for Childhood Cancer(PPUS-CC)in China's Mainland.Methods:Exploratory factor analysis(EFA)and confirmatory factor analysis(CFA)were performed using study population of 420 parents.The participants were also given the social support questionnaire and assessed using the Self-Rating Anxiety Scale,Zarit Burden Interview,and Self-Rating Depression Scale to test the association with PPUS-CC and obtain the cut-off of the scale.Results:The Chinese version of PPUS-CC includes 14 items,and two factors were extracted by EFA,which could explain the 54.56%variances.The Cronbach'sαof two factors ranged from 0.830 to 0.877.The dimensions of PPUS-CC show statistical association with other scales,and the cut-off is 42.5.Conclusion:The Chinese version of PPUS-CC,as a reliable,valid,and easy-to-use clinical tool,can be adapted in clinical settings as a screening tool to recognize parents with high-risk psychological problems.

Developing a Scale for Measuring Uncertainty in Patients with Unruptured Intracranial Aneurysms Undergoing Endovascular Coiling

A measure called the Uncertainty in Unruptured Intracranial Aneurysm Patients Undergoing Endovascular Coiling Scale (UUIACS) was developed and its validity and reliability were examined. The 49 questions that comprised the original draft of the UUIACS were created based on interview data. Based on data from 172 participants, exploratory and confirmatory factor analyses were conducted. As a result of exploratory factor analysis, the UUIACS e retained 17 items and extracted four factors (“Lack of decision-making cues”, “Lack of information and complexity of information interpretation”, “The ambiguous nature of the disease”, and “The unpredictable living with UIA”). All of the UUIACS items showed adequate internal consistency. Between the UUIAC scale and the Universal Uncertainty in Illness Scale (UUIS), the Health Locus of Control (HLC) scale, and the SF-36v2&reg (Japanese version), positive correlations were found between the UUIACS and UUIS, and the HLC scale at a 1% significance level indicating concurrent validity. According to confirmatory factor analysis, the UUIACS had an acceptable goodness of fit. Given these findings, the UUIACS was judged to have satisfied the criteria for use in a clinical setting, although further investigation was required.

Development of a Scale to Screen Parents with Uncertainty Regarding Their Child with Acute Illness

Parents experience uncertainty when their children become sick. The study aimed to develop a Parents’ Uncertainty regarding their Child with Acute Illness Scale (PUCAS) and to clarify differences in PUCAS scores between groups that were divided according to participants’ demographic characteristics. PUCAS was developed based on interviews, literature review, and a pilot study. We obtained valid responses from 235 parents with children hospitalized due to an acute childhood illness. Exploratory factor analysis narrowed the number of items to 25, divided into the following 5 subscales: unpredictability of the course of the illness, ambiguity about the severity of the illness, ambiguous appropriateness of management, discrepancy of judgement with health care professionals, and lack of information about the causes of the illness. There was satisfactory construct validity and criterion-related validity. Cronbach’s alpha was 0.92 for the overall scale. Participants who used ambulances, those who were not given any reliable diagnosis for their children, and fathers scored significantly higher on the PUCAS. PUCAS has high validity and reliability in measuring uncertainty of parents who have children with acute childhood illness and could be a useful screening tool for parents with high uncertainty in a clinical setting.

Model Uncertainty Representation for a Convection-Allowing Ensemble Prediction System Based on CNOP-P

Formulating model uncertainties for a convection-allowing ensemble prediction system(CAEPS)is a much more challenging problem compared to well-utilized approaches in synoptic weather forecasting.A new approach is proposed and tested through assuming that the model uncertainty should reasonably describe the fast nonlinear error growth of the convection-allowing model,due to the fast developing character and strong nonlinearity of convective events.The Conditional Nonlinear Optimal Perturbation related to Parameters(CNOP-P)is applied in this study.Also,an ensemble approach is adopted to solve the CNOP-P problem.By using five locally developed strong convective events that occurred in pre-rainy season of South China,the most sensitive parameters were detected based on CNOP-P,which resulted in the maximum variations in precipitation.A formulation of model uncertainty is designed by adding stochastic perturbations into these sensitive parameters.Through comparison ensemble experiments by using all the 13 heavy rainfall cases that occurred in the flood season of South China in 2017,the advantages of the CNOP-P-based method are examined and verified by comparing with the well-utilized stochastically perturbed physics tendencies(SPPT)scheme.The results indicate that the CNOP-P-based method has potential in improving the under-dispersive problem of the current CAEPS.

A Multi-time Scale Tie-line Energy and Reserve Allocation Model Considering Wind Power Uncertainties for Multi-area Systems

Continued expansion of the power grid and the increasing proportion of wind power centralized integration leads to requirements in sharing both energy and reserves among multiple areas under a hierarchical control structure,which successively requires a correction between schedule plans within multi-time scale.In order to address this problem,this paper develops an information integration method integrating complicated relationships among fuel cost,total thermal power output,reserve capacity,owned reserves and expectations of load shedding and wind curtailment,into three types of time-related relationship curves・Furthermore,a multi-time scale tieline energy and reserves allocation model is proposed,which contains two levels in the control structure,two time scales in dispatch sequence and multiple areas integrated within wind farms as scheduling objects・The efficiency of the proposed method is tested in a 9-bus test system and IEEE 118-bus system.The results show that a cross-regional control center is able to approach the optimal scheduling results of the whole system with the integrated uploaded relationship curves.The proposed model not only relieves energy and reserve shortages in partial areas but also allocates them to more urgent need areas in a high effectivity manner in both day-ahead and intraday time scales.

Multi-time scale dynamics in power electronics-dominated power systems

Electric power infrastructure has recently undergone a comprehensive transformation from electromagnetics to semiconductors. Such a development is attributed to the rapid growth of power electronic converter applications in the load side to realize energy conservation and on the supply side for renewable generations and power transmissions using high voltage direct current transmission. This transformation has altered the fundamental mechanism of power system dynamics, which demands the establishment of a new theory for power system control and protection. This paper presents thoughts on a theoretical framework for the coming semiconducting power systems.

Uncertainties of landslide susceptibility prediction:influences of different study area scales and mapping unit scales

This study aims to investigate the effects of different mapping unit scales and study area scales on the uncertainty rules of landslide susceptibility prediction(LSP).To illustrate various study area scales,Ganzhou City in China,its eastern region(Ganzhou East),and Ruijin County in Ganzhou East were chosen.Different mapping unit scales are represented by grid units with spatial resolution of 30 and 60 m,as well as slope units that were extracted by multi-scale segmentation method.The 3855 landslide locations and 21 typical environmental factors in Ganzhou City are first determined to create spatial datasets with input-outputs.Then,landslide susceptibility maps(LSMs)of Ganzhou City,Ganzhou East and Ruijin County are pro-duced using a support vector machine(SVM)and random forest(RF),respectively.The LSMs of the above three regions are then extracted by mask from the LSM of Ganzhou City,along with the LSMs of Ruijin County from Ganzhou East.Additionally,LSMs of Ruijin at various mapping unit scales are generated in accordance.Accuracy and landslide suscepti-bility indexes(LSIs)distribution are used to express LSP uncertainties.The LSP uncertainties under grid units significantly decrease as study area scales decrease from Ganzhou City,Ganzhou East to Ruijin County,whereas those under slope units are less affected by study area scales.Of course,attentions should also be paid to the broader representativeness of large study areas.The LSP accuracy of slope units increases by about 6%–10%compared with those under grid units with 30 m and 60 m resolution in the same study area's scale.The significance of environmental factors exhibits an averaging trend as study area scale increases from small to large.The importance of environmental factors varies greatly with the 60 m grid unit,but it tends to be consistent to some extent in the 30 m grid unit and the slope unit.

Advances in the study of uncertainty quantification of large-scale hydrological modeling system

The regional hydrological system is extremely complex because it is affected not only by physical factors but also by human dimensions.And the hydrological models play a very important role in simulating the complex system.However,there have not been effective methods for the model reliability and uncertainty analysis due to its complexity and difficulty.The uncertainties in hydrological modeling come from four important aspects：uncertainties in input data and parameters,uncertainties in model structure,uncertainties in analysis method and the initial and boundary conditions.This paper systematically reviewed the recent advances in the study of the uncertainty analysis approaches in the large-scale complex hydrological model on the basis of uncertainty sources.Also,the shortcomings and insufficiencies in the uncertainty analysis for complex hydrological models are pointed out.And then a new uncertainty quantification platform PSUADE and its uncertainty quantification methods were introduced,which will be a powerful tool and platform for uncertainty analysis of large-scale complex hydrological models.Finally,some future perspectives on uncertainty quantification are put forward.

Spatial Scale Effects of Water Erosion Dynamics:Complexities, Variabilities, and Uncertainties

Severe water erosion is notorious for its harmful effects on land-water resources as well as local societies. The scale effects of water erosion, however, greatly exacerbate the difficulties of accurate erosion evaluation and hazard control in the real world. Analyzing the related scale issues is thus urgent for a better understanding of erosion variations as well as reducing such erosion. In this review article, water erosion dynamics across three spatial scales including plot, watershed, and regional scales were selected and discussed. For the study purposes and objectives, the advantages and disadvantages of these scales all demonstrate clear spatial-scale dependence. Plot scale studies are primarily focused on abundant data collection and mechanism discrimination of erosion generation, while watershed scale studies provide valuable information for watershed management and hazard control as well as the development of quantitatively distributed models. Regional studies concentrate more on large-scale erosion assessment, and serve policymakers and stakeholders in achieving the basis for regulatory policy for comprehensive land uses. The results of this study show that the driving forces and mechanisms of water erosion variations among the scales are quite different. As a result, several major aspects contributing to variations in water erosion across the scales are stressed: differences in the methodologies across various scales, different sink-source roles on water erosion processes, and diverse climatic zones and morphological regions. This variability becomes more complex in the context of accelerated global change. The changing climatic factors and earth surface features are considered the fourth key reason responsible for the increased variability of water erosion across spatial scales.

Stability Criteria for Large－Scale Linear Systems with Structured Uncertainties

The robust stability analysis for large scale linear systems with structured time varying uncertainties is investigated in this paper.By using the scalar Lyapunov functions and the properties of M matrix and nonnegative matrix,stability robustness measures are proposed.The robust stability criteria obtained are applied to derive an algebric criterion which is expressed directly in terms of plant parameters and is shown to be less conservative than the existing ones.A numerical example is given to demonstrate the stability criteria obtained and to compare them with the previous ones.

Decentralized robust stabilization of discrete-time fuzzy large-scale systems with parametric uncertainties: a LMI method

Decentralized robust stabilization problem of discrete-time fuzzy large-scale systems with parametric uncertainties is considered. This uncertain fuzzy large-scale system consists of N interconnected T-S fuzzy subsystems, and the parametric uncertainties are unknown but norm-bounded. Based on Lyapunov stability theory and decentralized control theory of large-scale system, the design schema of decentralized parallel distributed compensation （DPDC） fuzzy controllers to ensure the asymptotic stability of the whole fuzzy large-scale system is proposed. The existence conditions for these controllers take the forms of LMIs. Finally a numerical simulation example is given to show the utility of the method proposed.

Accuracy assessments and uncertainty analysis of spatially explicit modeling for land use/cover change and urbanization:A case in Beijing metropolitan area

Spatially explicit modeling plays a vital role in land use/cover change and urbanization research as well as resources management;however,current models lack proper validation and fail to incorporate uncertainty into the formulation of model predictions.Consequently,policy makers and the general public may develop opinions based on potentially misleading research,which fails to allow for truly informed decisions.Here we use an uncertainty strategy of spatially explicit modeling combined with the series statistic of Kappa index for location and quantity to estimate the uncertainty of future predications and to determine model accuracy.We take the Beijing metropolitan area as an example to demonstrate the uncertainty in extrapolations of predictive land use change and urban sprawl with spatially explicit modeling at multiple resolutions.The sensitivity of scale effects is also discussed.The results show that an improvement in specification of location is more helpful in increasing accuracy as compared to an improvement in the specification of quantity at fine spatial resolutions.However,the spatial scale has great effects on modeling accuracy and correct due to chance tends to increase as resolution becomes coarser.The results allow us to understand the uncertainty when using spatially explicit models for land-use change or urbanization estimates.

Astronomical time scale of the Turonian constrained by multiple paleoclimate proxies

One of the clocks that record the Earth history is(quasi-) periodic astronomical cycles.These cycles influence the climate that can be ultimately stored in sedimentary rocks.By cracking these(quasi-) periodic sedimentation signals,high resolution astronomical time scale(ATS) can be obtained.Paleoclimate proxies are widely used to extract astronomical cycles.However different proxies may respond differently to astronomical signals and nonastronomical noises including tectonics,diagenesis,and measurement error among others.Astronomical time scale constructed based on a single proxy where its signal-to-noise ratio is low may have uncertainty that is difficult to evaluate but can be revealed by utilizing other proxies.Here,we test eight astronomical age models using two astrochro no logical methods from four paleoclimate proxies(i.e.,color reflection L~* and b~*,natural gamma radiation,and bulk density) from the Turonian to the Coniacian of the Cretaceous Period at the Demerara Rise in the equatorial Atlantic.The two astrochronological methods are time calibration using long eccentricity bandpass filtering(E1 bandpass) and tracking the long eccentricity from evolutive harmonic analysis(tracking EHA).The statistical mean and standard deviation of four age models from the four proxies are calculated to construct one integrated age model with age uncertainty in each method.Results demonstrate that extracting astronomical signals from multiple paleoclimate proxies is a valid method to estimate age model uncertainties.Anchored at the Cenomanian/Turonian boundary with an age of 93.9 ± 0.15 Ma from biostratigraphy,the ages for CC11/CC12(calcareous nannofossil zones),Turonian/Coniacian(CC12/CC13),CC13/CC14,and Coniacian/Santonian boundaries are 91.25±0.20 Ma,89.87±0.20 Ma,86.36±0.33 Ma,and 86.03±0.32 Ma in E1 bandpass method,compared with 91.17±0.36 Ma,89.74±0.38 Ma,86.13±1.31 Ma,and 85.80±1.33 Ma respectively in tracking EHA method.These results are consistent with previous studies within error and provide a reliable estimation of uncertainties of the ages.

Uncertainty analysis and visualization of geological subsurface and its application in metro station construction

To visualize and analyze the impact of uncertainty on the geological subsurface,on the term of the geological attribute probabilities(GAP),a vector parameters-based method is presented.Perturbing local data with error distribution,a GAP isosurface suite is first obtained by the Monte Carlo simulation.Several vector parameters including normal vector,curvatures and their entropy are used to measure uncertainties of the isosurface suite.The vector parameters except curvature and curvature entropy are visualized as line features by distributing them over their respective equivalent structure surfaces or concentrating on the initial surface.The curvature and curvature entropy presented with color map to reveal the geometrical variation on the perturbed zone.The multiple-dimensional scaling(MDS)method is used to map GAP isosurfaces to a set of points in lowdimensional space to obtain the total diversity among these equivalent probability surfaces.An example of a bedrock surface structure in a metro station shows that the presented method is applicable to quantitative description and visualization of uncertainties in geological subsurface.MDS plots shows differences of total diversity caused by different error distribution parameters or different distribution types.

基于灵敏度对比分析SCALE 6.1自带库与CENDL-TMSR-V1数据库

为满足钍基熔盐堆物理设计和钍铀燃料循环物理分析对核数据的需求,中国核数据中心研制了一套钍铀燃料循环专用数据库CENDL-TMSR-V1。本文利用SCALE程序,针对熔盐堆开展了SCALE 6.1自带数据库和CENDL-TMSR-V1库对比分析。结果显示,针对1 GWt钍增殖熔盐堆,利用两个数据库的238群数据计算的不同燃耗下k eff最大差异约1200 pcm。结合核数据对k eff的灵敏度分析显示,其差异主要由石墨的核数据不同引起的。宏观检验结果显示,CENDL-TMSR-V1库中石墨数据更合理。同时,基于CENDL-TMSR-V144群协方差数据,计算得到核数据对初始时刻k eff总不确定度为1.03%,约为SCALE 6.1自带44群协方差数据库计算结果的2倍,其差异主要由233 U、232 Th等核素的协方差数据不同导致。