How to evaluate the system reliability through the test data of components is one of the key challenges in the field of reliability.In this study,the authors focus on calculating the Bayesian lower credible limit.Alth...How to evaluate the system reliability through the test data of components is one of the key challenges in the field of reliability.In this study,the authors focus on calculating the Bayesian lower credible limit.Although the approximation methods are widely used in reliability evaluation,how to apply them to the Bayesian context remains to be solved.Some previous studies have attempted to address this issue.However,their approaches might result in instability,and they have imposed significant constraints on component and system structures.A high-order saddlepoint approximation method for high accuracy is proposed,as well as a feasible procedure for determining the saddlepoint method's asymptotic variable.The proposed framework allows us to analyze the components following various posterior distributions without limiting the system structure.Numerical experiments on various systems are presented to demonstrate the effectiveness and accuracy of the proposed method.In comparison,it consistently outperforms other commonly used approximation approaches.展开更多
As a significant clean energy source, natural gas plays an important role in modern energy context. The growing utilization of natural gas brings uncertainties into the power system, which requires an integrated way t...As a significant clean energy source, natural gas plays an important role in modern energy context. The growing utilization of natural gas brings uncertainties into the power system, which requires an integrated way to plan natural gas and power systems. In this paper, the co-planning process is formulated as a mixed integer nonlinear programming problem to address emerging challenges,such as system reliability evaluation, market time line mismatch, market uncertainties, demand response effect,etc. An innovative expansion co-planning(ECP) framework is established in this paper to find the best augmentation plan which comes with the minimum cost.Specifically, to cope with uncertainties in market share,decision analysis is introduced. Meanwhile, the energy conversion efficiency between gas and electricity in the coupled load center is considered in the ECP constraints.Comprehensive case studies are applied to validate the performance of proposed approach.展开更多
基金supported by the National Key Research and Development Program of China under Grant Nos.2021YFA1000300 and 2021YFA1000301the National Natural Science Foundation of China under Grant No.12401354。
文摘How to evaluate the system reliability through the test data of components is one of the key challenges in the field of reliability.In this study,the authors focus on calculating the Bayesian lower credible limit.Although the approximation methods are widely used in reliability evaluation,how to apply them to the Bayesian context remains to be solved.Some previous studies have attempted to address this issue.However,their approaches might result in instability,and they have imposed significant constraints on component and system structures.A high-order saddlepoint approximation method for high accuracy is proposed,as well as a feasible procedure for determining the saddlepoint method's asymptotic variable.The proposed framework allows us to analyze the components following various posterior distributions without limiting the system structure.Numerical experiments on various systems are presented to demonstrate the effectiveness and accuracy of the proposed method.In comparison,it consistently outperforms other commonly used approximation approaches.
基金supported in part by funding from the Faculty of Engineering&Information Technologies,The University of Sydney,under the Mid-career Researcher Development Schemein part by the ARC Discovery Grant(No.DP170103427)in part by the 2015 Science and Technology Project of China Southern Power Grid(No.WYKJ00000027)
文摘As a significant clean energy source, natural gas plays an important role in modern energy context. The growing utilization of natural gas brings uncertainties into the power system, which requires an integrated way to plan natural gas and power systems. In this paper, the co-planning process is formulated as a mixed integer nonlinear programming problem to address emerging challenges,such as system reliability evaluation, market time line mismatch, market uncertainties, demand response effect,etc. An innovative expansion co-planning(ECP) framework is established in this paper to find the best augmentation plan which comes with the minimum cost.Specifically, to cope with uncertainties in market share,decision analysis is introduced. Meanwhile, the energy conversion efficiency between gas and electricity in the coupled load center is considered in the ECP constraints.Comprehensive case studies are applied to validate the performance of proposed approach.
