This paper presents an evaluation method for the entropy-weighting of wind power clusters that comprehensively evaluates the allocation problems of wind power clusters by considering the correlation between indicators...This paper presents an evaluation method for the entropy-weighting of wind power clusters that comprehensively evaluates the allocation problems of wind power clusters by considering the correlation between indicators and the dynamic performance of weight changes.A dynamic layered sorting allocation method is also proposed.The proposed evaluation method considers the power-limiting degree of the last cycle,the adjustment margin,and volatility.It uses the theory of weight variation to update the entropy weight coefficients of each indicator in real time,and then performs a fuzzy evaluation based on the membership function to obtain intuitive comprehensive evaluation results.A case study of a large-scale wind power base in Northwest China was conducted.The proposed evaluation method is compared with fixed-weight entropy and principal component analysis methods.The results show that the three scoring trends are the same,and that the proposed evaluation method is closer to the average level of the latter two,demonstrating higher accuracy.The proposed allocation method can reduce the number of adjustments made to wind farms,which is significant for the allocation and evaluation of wind power clusters.展开更多
In the face of the pressing environmental issues,the past decade witnessed the booming development of the distributed energy systems(DESs).A notable problem of DESs is the inevitable uncertainty that may make DESs dev...In the face of the pressing environmental issues,the past decade witnessed the booming development of the distributed energy systems(DESs).A notable problem of DESs is the inevitable uncertainty that may make DESs deviate significantly from the deterministically obtained expectations,in both aspects of optimal design and economic operation.It thus necessitates the sensitivity analysis to quantify the impacts of the massive parametric uncertainties.This paper aims to give a comprehensive quantification,and carries out a multi-stage sensitivity analysis on DESs from the perspectives of evaluation criteria,optimal design and economic operation.First,a mathematical model of a DES is developed to present the solutions to the three stages of the DES.Second,the Monte-Carlo simulation is carried out subject to the probabilistic distributions of the energy,technical and economic parameters.Based on the simulation results,the variance-based Sobol method is applied to calculate the individual importance,interactional importance and total importance of various parameters.The comparison of the multi-stage results shows that only a few parameters play critical roles while the uncertainty of most of the massive parameters has little impact on the system performance.In addition,the influence of parameter interactions in the optimal design stage are much stronger than that in the evaluation criteria and operation strategy stages.展开更多
基金supported by the National Natural Science Foundation of China(Grant No.52076038,U22B20112,No.52106238)the Fundamental Research Funds for Central Universities(No.423162,B230201051).
文摘This paper presents an evaluation method for the entropy-weighting of wind power clusters that comprehensively evaluates the allocation problems of wind power clusters by considering the correlation between indicators and the dynamic performance of weight changes.A dynamic layered sorting allocation method is also proposed.The proposed evaluation method considers the power-limiting degree of the last cycle,the adjustment margin,and volatility.It uses the theory of weight variation to update the entropy weight coefficients of each indicator in real time,and then performs a fuzzy evaluation based on the membership function to obtain intuitive comprehensive evaluation results.A case study of a large-scale wind power base in Northwest China was conducted.The proposed evaluation method is compared with fixed-weight entropy and principal component analysis methods.The results show that the three scoring trends are the same,and that the proposed evaluation method is closer to the average level of the latter two,demonstrating higher accuracy.The proposed allocation method can reduce the number of adjustments made to wind farms,which is significant for the allocation and evaluation of wind power clusters.
基金supported by National Natural Science Foundation of China(No.51936003)National Key Research and Development Program of China(No.2018YFB1502904)
文摘In the face of the pressing environmental issues,the past decade witnessed the booming development of the distributed energy systems(DESs).A notable problem of DESs is the inevitable uncertainty that may make DESs deviate significantly from the deterministically obtained expectations,in both aspects of optimal design and economic operation.It thus necessitates the sensitivity analysis to quantify the impacts of the massive parametric uncertainties.This paper aims to give a comprehensive quantification,and carries out a multi-stage sensitivity analysis on DESs from the perspectives of evaluation criteria,optimal design and economic operation.First,a mathematical model of a DES is developed to present the solutions to the three stages of the DES.Second,the Monte-Carlo simulation is carried out subject to the probabilistic distributions of the energy,technical and economic parameters.Based on the simulation results,the variance-based Sobol method is applied to calculate the individual importance,interactional importance and total importance of various parameters.The comparison of the multi-stage results shows that only a few parameters play critical roles while the uncertainty of most of the massive parameters has little impact on the system performance.In addition,the influence of parameter interactions in the optimal design stage are much stronger than that in the evaluation criteria and operation strategy stages.