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| 1 | Improved Approximate Minimum Degree Ordering Method and Its Application for Electrical Power Network Analysis and Computation显示文摘Electrical power network analysis and computation play an important role in the planning and operation of the power grid,and they are modeled mathematically as differential equations and network algebraic equations.The direct method based on Gaussian elimination theory can obtain analytical results.Two factors affect computing efficiency:the number of nonzero element fillings and the length of elimination tree.This article constructs mapping correspondence between eliminated tree nodes and quotient graph nodes through graph and quotient graph theories.The Approximate Minimum Degree(AMD)of quotient graph nodes and the length of the elimination tree nodes are composed to build an Approximate Minimum Degree and Minimum Length(AMDML)model.The quotient graph node with the minimum degree,which is also the minimum length of elimination tree node,is selected as the next ordering vector.Compared with AMD ordering method and other common methods,the proposed method further reduces the length of elimination tree without increasing the number of nonzero fillings;the length was decreased by about 10%compared with the AMD method.A testbed for experiment was built.The efficiency of the proposed method was evaluated based on different sizes of coefficient matrices of power flow cases. | Jian Guo Hong Liang Songpu Ai Chao Lu Haochen Hua Junwei Cao | 2021 | Tsinghua Science and Technology2021，26，4： | 1 |
| 2 | Multiple Impact Factor Based Accuracy Analysis for Power Quality Disturbance Detection显示文摘Nowadays,power quality problems are affecting people’s daily life and production activities.With an aim to improve disturbance detection accuracy,a novel analysis approach,based on multiple impact factors,is proposed in this paper.First,a multiple impact factors analysis is implemented in which two perspectives,i.e.,the wavelet analysis and disturbance features are simultaneously considered.Five key factors,including wavelet function,wavelet decomposition level,redundant algorithm,event type and disturbance intensity,and start and end moment of disturbance,have been considered.Next,an impact factor based accuracy analysis algorithm is proposed,through which each factor’s potential impact on disturbance location accuracy is investigated.Three transforms,i.e.,the classic wavelet,lifting wavelet and redundant lifting wavelet are employed,and their superiority on disturbance location accuracy is investigated.Finally,simulations are conducted for verification.Through the proposed method,the wavelet based parameters can be validly selected in order to accurately detect power quality disturbance. | Zijing Yang Haochen Hua Junwei Cao | 2023 | CSEE Journal of Power and Energy Systems2023，9，1： | 1 |
| 3 | Energy Sharing and Frequency Regulation in Energy Network via Mixed H_(2)/H_(∞) Control with Markovian Jump显示文摘In this paper,the problem of mixed optimization for energy sharing and frequency regulation in a typical energy network scenario where energy routers(ERs)interconnected AC microgrids(MGs)is investigated.Continuous-time Markov chains are introduced to describe the switching paths in the power dynamics of MGs.Such that the modelling of considered energy network system could be closer to the real-world engineering practice.Advanced parameter estimation techniques are integrated into the proposed method to achieve better modelling accuracy and controlling performance.Based on the parameters of MG power dynamics,the mixed H_(2)/H_(∞) controllers are obtained via stochastic control theory.The feasibility and efficacy of the proposed approach are evaluated in numerical examples. | Haochen Hua Yuchao Qin Zicheng He Liuying Li Junwei Cao | 2021 | CSEE Journal of Power and Energy Systems2021，7，6： | 1 |
| 4 | Performance Modeling for Data Monitoring Services in Smart Grid: A Network Calculus Based Approach显示文摘This paper focuses on solving the modeling issues of monitoring system service performance based on the network calculus theory.First,we formulate the service model of the smart grid monitoring system.Then,we derive the flow arrival curve based on the incremental process related functions.Next,we develop flow arrival curves for the case of the incremental process being a fractional Gaussian process,and then we obtain the generalized Cauchy process.Three technical theorems related to network calculus are presented as our main results.Mathematically,the variance of arrival flow for the continuous time case is derived.Assuming that the incremental process of network flow is a Gaussian stationary process,and given the auto-correlation function of the incremental process with violation probability,the formula of the arrival curve is derived.In addition,the overall flow variance under the discrete time case is explicitly derived.The theoretical results are evaluated in smart grid applications.Simulations indicate that the generalized Cauchy process outperforms the fractional Gaussian process for our considered problem. | Junwei Cao Yuxin Wan Haochen Hua Gang Yang | 2020 | CSEE Journal of Power and Energy Systems2020，6，3： | 1 |
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