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uncertainty modeling of wind power frequency regulation potential considering distributed characteristics of forecast errors

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Protection and Control of Modern Power Systems 2021年第1期6卷 276-288页

作者： Cheng Yan Yi Tang Jianfeng Dai Chenggen Wang Shengjun Wu School of Electrical Engineering Southeast UniversityNanjingChina College of Automation Nanjing University of Posts and TelecommunicationsNanjingChina State Grid Jiangsu Electric Power Co. Ltd.Electric Power Research InstituteNanjingChina

Large-scale integration of wind power generation decreases the equivalent inertia of a power system, and thus makes frequency stability control challenging. However, given the irregular, nonlinear, and non-stationary characteristics of wind power, significant challenges arise in making wind power generation participate in system frequency regulation. Hence, it is important to explore wind power frequency regulation potential and its uncertainty. This paper proposes an innovative uncertainty modeling method based on mixed skew generalized error distribution for wind power frequency regulation potential. The mapping relationship between wind speed and the associated frequency regulation potential is established, and key parameters of the wind turbine model are identified to predict the wind power frequency regulation potential. Furthermore, the prediction error distribution of the frequency regulation potential is obtained from the mixed skew model. Because of the characteristics of error partition, the error distribution model and predicted values at different wind speed sections are summarized to generate the uncertainty interval of wind power frequency regulation potential. Numerical experiments demonstrate that the proposed model outperforms other state-of-the-art contrastive models in terms of the refined degree of fitting error distribution characteristics. The proposed model only requires the wind speed prediction sequence to accurately model the uncertainty interval. This should be of great significance for rationally optimizing system frequency regulation resources and reducing redundant backup.

关键词： Inertial response Primary frequency control Error distribution Mixed skew generalized error distribution uncertainty modeling

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Robustness evaluation of cutting tool maintenance planning for soft ground tunneling projects

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Underground Space 2018年第1期3卷 72-85页

作者： Alena Conrads Markus Scheffer Markus Konig Markus Thewes Inastitute of Tunneling cand Construction Management Ruhr-Universitat BochunGermany Chair of Computing in Engineering Ruhr-Universitit BochunGermany

Tunnel boring machines require extensive maintenance and inspection effort to provide a high *** cutting tools of the cutting wheel must be changed timely upon reaching a critical *** one possible maintenance strategy is to change tools only when it is absolutely necessary,tools can also be changed preventively to avoid further *** different maintenance strategies inﬂuence the maintenance duration and the overall project ***,determine downtime related to a particular mainte-nance strategy is still a challenging *** paper shows an analysis of the robustness to achieve the planned project performance of a maintenance strategy considering uncertainties of wear behavior of the cutting tools.A simulation based analysis is presented,imple-menting an empirical wear prediction *** strategies of maintenance planning are compared by performing a parameter vari-ation study including Monte-Carlo *** maintenance costs are calculated and evaluated with respect to their ***,an improved and robust maintenance strategy has been determined.

关键词： Mechanized tunneling,Maintenance Wear of cutting tools Process simulation Robustness uncertainty modeling

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An Improved CREAM Model Based on DS Evidence Theory and DEMATEL

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Computer modeling in Engineering & Sciences 2024年第3期138卷 2597-2617页

作者： Zhihui Xu Shuwen Shang Yuntong Pu Xiaoyan Su Hong Qian Xiaolei Pan State Key Laboratory of Nuclear Power Safety Monitoring Technology and Equipment Shenzhen518172China School of Automation Engineering Shanghai University of Electric PowerShanghai200090China School of Safety and Management Engineering Hunan Institute of TechnologyHengyang421002China

Cognitive Reliability and Error Analysis Method(CREAM)is widely used in human reliability analysis(HRA).It defines nine common performance conditions(CPCs),which represent the factors thatmay affect human reliability and are used to modify the cognitive failure probability(CFP).However,the levels of CPCs are usually determined by domain experts,whichmay be subjective and ***’smore,the classicCREAMassumes that the CPCs are independent,which is *** the dependence among CPCs will result in repeated calculations of the influence of the CPCs on CFP and lead to unreasonable reliability *** address the issue of uncertain information modeling and processing,this paper introduces evidence theory to evaluate the CPC levels in specific *** address the issue of dependence modeling,the Decision-Making Trial and Evaluation Laboratory(DEMATEL)method is used to process the dependence among CPCs and calculate the relative weights of each CPC,thus modifying the multiplier of the *** detailed process of the proposed method is illustrated in this paper and the CFP estimated by the proposed method is more reasonable.

关键词： Human reliability analysis CREAM uncertainty modeling dependence Dempster-Shafer evidence theory DEMATEL

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Risk Models for the Prize Collecting Steiner Tree Problems with Interval Data

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Acta Mathematicae Applicatae Sinica 2014年第1期30卷 1-26页

作者： Eduardo lvarez-Miranda Alfredo Candia-Vjar Xu-jin CHEN Xiao-dong HU Bi LI Industrial Management Department Universidad de TalcaChile DEI University of BolognaItaly Academy of Mathematics and Systems Science CAS

Given a connected graph G=（V,E）with a nonnegative cost on each edge in E,a nonnegative prize at each vertex in V,and a target set V′V,the Prize Collecting Steiner Tree（PCST）problem is to find a tree T in G interconnecting all vertices of V′such that the total cost on edges in T minus the total prize at vertices in T is *** PCST problem appears frequently in practice of operations *** the problem is NP-hard in general,it is polynomial-time solvable when graphs G are restricted to series-parallel *** this paper,we study the PCST problem with interval costs and prizes,where edge e could be included in T by paying cost xe∈[c e,c＋e]while taking risk（c＋e xe）/（c＋e c e）of malfunction at e,and vertex v could be asked for giving a prize yv∈[p v,p＋v]for its inclusion in T while taking risk（yv p v）/（p＋v p v）of refusal by *** establish two risk models for the PCST problem with interval *** given budget upper bound on constructing tree T,one model aims at minimizing the maximum risk over edges and vertices in T and the other aims at minimizing the sum of risks over edges and vertices in *** propose strongly polynomial-time algorithms solving these problems on series-parallel graphs to *** study shows that the risk models proposed have advantages over the existing robust optimization model,which often yields NP-hard problems even if the original optimization problems are polynomial-time solvable.

关键词： uncertainty modeling prize collecting Steiner tree interval data series-parallel graphs polynomial-time solvability

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3D Single Object Tracking with Multi-View Unsupervised Center uncertainty Learning

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CAAI Artificial Intelligence Research 2023年第1期2卷 45-54页

作者： Chengpeng Zhong Hui Shuai Jiaqing Fan Kaihua Zhang Qingshan Liu School of Computer Science Nanjing University of Information Science and TechnologyNanjing 210044China School of Computer Science and Technology Nanjing University of Aeronautics and AstronauticsNanjing 211106China

Center point localization is a major factor affecting the performance of 3D single object *** clouds themselves are a set of discrete points on the local surface of an object,and there is also a lot of noise in the ***,directly regressing the center coordinates is not very *** methods usually use volumetric-based,point-based,and view-based methods,with a relatively single *** addition,the sampling strategies commonly used usually result in the loss of object information,and holistic and detailed information is beneficial for object *** address these challenges,we propose a novel Multi-view unsupervised center uncertainty 3D single object Tracker(MUT).MUT models the potential uncertainty of center coordinates localization using an unsupervised manner,allowing the model to learn the true *** projecting point clouds,MUT can obtain multi-view depth map features,realize efficient knowledge transfer from 2D to 3D,and provide another modality information for the *** also propose a former attraction probability sampling strategy that preserves object *** using both holistic and detailed descriptors of point clouds,the tracker can have a more comprehensive understanding of the tracking *** results show that the proposed MUT network outperforms the baseline models on the KITTI dataset by 0.8%and 0.6%in precision and success rate,respectively,and on the NuScenes dataset by 1.4%,and 6.1%in precision and success rate,*** code is made available at https://***/abchears/***.

关键词： 3D single object tracking uncertainty modeling multi-view feature holistic and detailed descriptor

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A review of uncertain factors and analytic methods in long-term energy system optimization models

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Global Energy Interconnection 2023年第4期6卷 450-466页

作者： Siyu Feng Hongtao Ren Wenji Zhou School of Business East China University of Science and TechnologyShanghai 200237P.R.China School of Applied Economics Renmin University of ChinaBeijing 100872P.R.China International Institute for Applied Systems Analysis Schlossplatz 1Laxenburg A-2361Austria

A larger number of uncertain factors in energy systems influence their *** to the complexity of energy system modeling,incorporating uncertainty analysis to energy system modeling is essential for future energy system planning and resource *** study focusses on long-term energy system optimization *** important uncertain parameters in the model are analyzed and divided into policy,economic,and technical *** study specifically addresses the challenges related to carbon emission reduction and energy *** involves collecting and organizing relevant research on uncertainty analysis of long-term energy *** energy system uncertainty modeling methods and their applications from the literature are summarized in this ***,important uncertainty factors and uncertainty modeling methods for long-term energy system modeling are discussed,and future research directions are proposed.

关键词： Long-term energy system optimization models Uncertain factors uncertainty modeling

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