Fatigue Topology Optimization Design Based on Distortion Energy Theory and Independent Continuous Mapping Method

Fatigue failure is a common failure mode under the action of cyclic loads in engineering applications,which often occurs with no obvious signal.The maximum structural stress is far below the allowable stress when the structures are damaged.Aiming at the lightweight structure,fatigue topology optimization design is investigated to avoid the occurrence of fatigue failure in the structural conceptual design beforehand.Firstly,the fatigue life is expressed by topology variables and the fatigue life filter function.The continuum fatigue optimization model is established with the independent continuous mapping(ICM)method.Secondly,fatigue life constraints are transformed to distortion energy constraints explicitly by taking advantage of the distortion energy theory.Thirdly,the optimization formulation is solved by the dual sequence quadratic programming(DSQP).And the design scheme of lightweight structure considering the fatigue characteristics is obtained.Finally,numerical examples illustrate the practicality and effectiveness of the fatigue optimization method.This method further expands the theoretical application of the ICM method and provides a novel approach for the fatigue optimization problem.

A Data-driven Method for Transient Stability Margin Prediction Based on Security Region

Transient stability assessment(TSA)based on security region is of great significance to the security of power systems.In this paper,we propose a novel methodology for the assessment of online transient stability margin.Combined with a geographic information system(GIS)and transformation rules,the topology information and pre-fault power flow characteristics can be extracted by 2 D computer-vision-based power flow images(CVPFIs).Then,a convolutional neural network(CNN)-based comprehensive network is constructed to map the relationship between the steady-state power flow and the generator stability indices under the anticipated contingency set.The network consists of two components:the classification network classifies the input samples into the credibly stable/unstable and uncertain categories,and the prediction network is utilized to further predict the generator stability indices of the categorized samples,which improves the network ability to distinguish between the samples with similar characteristics.The proposed methodology can be used to quickly and quantitatively evaluate the transient stability margin of a power system,and the simulation results validate the effectiveness of the method.

Application of Game Theory to Basketball

Introduction Game theory is the study of how players interact and how to choose strategies in order to maximize benefits.To a certain extent,game theory can be used to advise decision makers on what decisions to make.The earliest ideas of game theory can be traced back to the 18th century,but the major development of the theory began in the 1920s with the work of mathematician Emile Borel and the

System Strength Assessment Based on Multi-task Learning

Increase in permeability of renewable energy sources(RESs)leads to the prominent problem of voltage stability in power system,so it is urgent to have a system strength evaluation method with both accuracy and practicability to control its access scale within a reasonable range.Therefore,a hybrid intelligence enhancement method is proposed by combining the advantages of mechanism method and data driven method.First,calculation of critical short circuit ratio(CSCR)is set as the direction of intelligent enhancement by taking the multiple renewable energy station short circuit ratio as the quantitative indicator.Then,the construction process of CSCR dataset is proposed,and a batch simulation program of samples is developed accordingly,which provides a data basis for subsequent research.Finally,a multi-task learning model based on progressive layered extraction is used to simultaneously predict CSCR of each RESs connection point,which significantly reduces evaluation error caused by weak links.Predictive performance and anti-noise performance of the proposed method are verified on the CEPRI-FS-102 bus system,which provides strong technical support for real-time monitoring of system strength.

Dynamic Capture Method for Out-of-step Center of Power Grid Based on Measurement Information

This paper dynamically captures the out-of-step center for a bulk power system based on measurement information.First,the position characteristics of the out-of-step center are discussed from the perspective of triangular geometry under different potential and uniform impedance distributions based on a two-machine system.The correlation between the out-of-step center and the oscillation center is analyzed.Second,combined with analytical geometry,it is inferred that the distribution characteristics of the out-of-step center voltage vector ends are a circle or a straight line,and the position of the out-of-step center corresponds to the intersection between the voltage drop of the line and the distribution characteristics;then,the accurate location of the out-of-step center and the determination of the appearance moment is realized.Finally,a dynamic equivalence method for a power grid is proposed based on the electrical parameters of the transmission line,and an alternative iterative correction of equivalent parameters is carried out by trajectory sensitivity,which provides a new way for capturing the out-ofstep center dynamically in a multimachine system.The proposed method is validated using a three-machine system,the IEEE-39 system and the Northwest China Power Grid,and shows potential for online applications.