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CSEE Journal of Power and Energy Systems 2024年第2期10卷 584-592页

作者： Zhi Ding Tianyao Ji Mengshi Li q.h.wu School of Electric Power Engineering South China University of Technology(SCUT)Guangzhou 510641China

In this paper, a novel signal processing method combining mathematical morphology (MM) and Walsh theory is proposed, which uses Walsh functions to control the structuring element (SE) and MM operators. Based on the Walsh-MM method, a scheme for power quality disturbances detection and classification is developed, which involves three steps: denoising, feature extraction and morphological clustering. First, various evolution rules of Walsh function are used to generate groups of SEs for the multiscale Walsh-ordered morphological operation, so the original signal can be denoised. Next, the fundamental wave of the denoised signal is suppressed by hadamard matrix;thus, disturbances can be extracted. Finally, the Walsh power spectrum of the waveform extracted in the previous step is calculated, and the parameters of which are taken by morphological clustering to classify the disturbances. Simulation results reveal the proposed scheme can effectively detect and classify disturbances, and the Walsh-MM method is less affected by noise and only involves simple calculation, which has a potential to be implemented in hardware and more suitable for real-time application.

关键词： hadamard matrix mathematical morphology morphological clustering power quality disturbance Walsh theory

Location of Asymmetric Ground Fault Using Virtual Injected Current Ratio and Two-stage Recovery Strategy in Distribution Networks

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CSEE Journal of Power and Energy Systems 2024年第1期10卷 151-161页

作者： haiting Shan Luliang Zhang q.h.wu Mengshi Li School of Electric Power Engineering South China University of Technology(SCUT)Guangzhou 510641China

Sparse measurements challenge fault location in distribution *** paper proposes a method for asymmetric ground fault location in distribution networks with limited measurements.A virtual injected current vector is formulated to estimate the fault line,which can be reconstructed from voltage sags measured at a few buses using compressive sensing(CS).The relationship between the virtual injected current ratio(VICR)and fault position is deduced from circuit analysis to pinpoint the ***,a two-stage recovery strategy is proposed for improving reconstruction accuracy of the current vector,where two different sensing matrixes are utilized to improve the *** proposed method is validated in IEEE 34 node test *** results show asymmetric ground fault type,resistance,fault position and access of distributed generators(DGs)do not significantly influence performance of our *** addition,it works effectively under various scenarios of noisy measurement and line parameter *** on 134 node test feeders prove the proposed method is also suitable for systems with more complex structure.

关键词： Distribution networks fault location reconstruction accuracy two-stage recovery virtual injected current ratio

Convexification of hybrid AC-DC Optimal Power Flow with Line-Commutated Converters

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CSEE Journal of Power and Energy Systems 2024年第2期10卷 617-628页

作者： hongyuan Liang Zhigang Li J.h.Zheng q.h.wu School of Electric Power Engineering South China University of TechnologyGuangzhou 510641China

Line-commutated converter (LCC)-based high-voltage DC (hVDC) systems have been integrated with bulk AC power grids for interregional transmission of renewable power. The nonlinear LCC model brings additional nonconvexity to optimal power flow (OPF) of hybrid AC-DC power grids. A convexification method for the LCC station model could address such nonconvexity but has rarely been discussed. We devise an equivalent reformulation for classical LCC station models that facilitates second-order cone convex relaxation for the OPF of LCC-based AC-DC power grids. We also propose sufficient conditions for exactness of convex relaxation with its proof. Equivalence of the proposed LCC station models and properties, exactness, and effectiveness of convex relaxation are verified using four numerical simulations. Simulation results demonstrate a globally optimal solution of the original OPF can be efficiently obtained from relaxed model.

关键词： AC-DC power system convex relaxation linecommutated converter optimal power flow second-order cone programming

Estimating Critical Clearing Time of Grid Faults Using DA of State-Reduction Model of Power Systems

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CSEE Journal of Power and Energy Systems 2024年第2期10卷 807-820页

作者： Yang Liu Zhongyang Chen huanjin Yao Lin Yi q.h.wu School of Electric Power Engineering South China University of TechnologyGuangzhou 510640China China Southern Power Grid Research Institute Guangzhou 510663China

This paper proposes a critical clearing time (CCT) estimation method by the domain of attraction (DA) of a state-reduction model of power systems using sum of squares (SOS) programming. By exploiting the property of the Jacobian matrix and the structure of the boundary of the DA, it is found the DA of the state-reduction model and that of the full model of a power system are topological isomorphism. There are one-to-one correspondence relationships between the number of equilibrium points, the type of equilibrium points, and solutions of the two system models. Based on these findings, an expanding interior algorithm is proposed with SOS programming to estimate the DA of the state-reduction model. State trajectories of the full model can be transformed to those of the state-reduction model by orthogonal or equiradius projection. In this way, CCT of a grid fault is estimated with the DA of the state-reduction model. The calculational burden of SOS programming in the DA estimation using the state-reduction model is rather small compared with using the full model. Simulation results show the proposed expanding interior algorithm is able to provide a tight estimation of DA of power systems with higher accuracy and lower time costs.

关键词： Critical clearing time domain of attraction expanding interior algorithm state-reduction model SOS programming

Observability Analysis of Integrated Electricity and heating Systems with Thermal quasi-dynamics in Pipelines

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CSEE Journal of Power and Energy Systems 2024年第3期10卷 1145-1158页

作者： Zhigang Li Wenjian Zheng Junbo Zhao J.h.Zheng q.h.wu School of Electric Power Engineering South China University of TechnologyGuangzhou 510641China Fuzhou Changle District Power Supply Company of State Grid Fujian Electric Power Co. Ltd.Fuzhou 350000China Department of Electrical and Computer Engineering University of ConnecticutStorrsCT 06269USA CSEE IEEE

Observability analysis(OA)is vital to obtaining the available input measurements of state estimation(SE)in an integrated electricity and heating system(IEhS).Considering the thermal quasi-dynamics in pipelines,the measurement equations in heating systems are dependent on the estimated results,leading to an interdependency between OA and *** OA methods require measurement equations be known exactly before SE is performed,and they are not applicable to *** bridge this gap,a scenario-based OA scheme for IEhSs is devised that yields reliable analysis results for a predefined set of time-delay scenarios to cope with this *** its core procedure,the observable state identification and observability restoration are formulated in terms of integer linear *** tests are conducted to demonstrate the validity and superiority of the proposed formulation.

关键词： Integrated electricity and heating system measurement observability analysis state estimation thermal quasi-dynamics

Network Embedding Algorithm for Vulnerability Assessment of Power Transmission Lines Using Integrated Structure and Attribute Information

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CSEE Journal of Power and Energy Systems 2024年第1期10卷 351-360页

作者： Xianglong Lian Tong qian Zepeng Li Xingyu Chen Wenhu Tang q.h.wu School of Electric Power Engineering South China University of TechnologyGuangzhou 510640China

In power systems,failures of vulnerable lines can trigger large-scale cascading failures,and vulnerability assessment is dedicated to locating these lines and reducing the risks of such *** on a structure and attribute network embedding(SANE)algorithm,a novel quantitative vulnerability analysis method is proposed to identify vulnerable lines in this ***,a two-layered random walk network with topological and electrical properties of transmission lines is ***,based on the weighted degree of nodes in the two-layered network,the inter-layer and intra-layer walking transition probabilities are developed to obtain walk ***,a Word2Vec algorithm is applied to obtain lowdimension vectors representing transmission lines,according to obtained walk sequences for calculating the vulnerability index of transmissions ***,the proposed method is compared with three widely used methods in two test *** show the network embedding based method is superior to those comparison methods and can provide guidance for identifying vulnerable lines.

关键词： Network embedding random walk transmission lines vulnerability assessment

Fault Identification in Power Network Based on Deep Reinforcement Learning

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CSEE Journal of Power and Energy Systems 2022年第3期8卷 721-731页

作者： Mengshi Li huanming Zhang Tianyao Ji q.h.wu School of Electric Power Engineering South China University of TechnologyGuangzhou510641China

With the integration of alternative energy and renewables,the issue of stability and resilience of the power network has received considerable *** basic necessity for fault diagnosis and isolation is fault identification and *** conventional intelligent fault identification method needs supervision,manual labelling of characteristics,and requires large amounts of labelled *** enhance the ability of intelligent methods and get rid of the dependence on a large amount of labelled data,a novel fault identification method based on deep reinforcement learning(DRL),which has not received enough attention in the field of fault identification,is investigated in this *** proposed method uses different faults as parameters of the model to expand the scope of fault *** addition,the DRL algorithm can intelligently modify the fault parameters according to the observations obtained from the power network environment,rather than requiring manual and mechanical tuning of *** methodology was tested on the IEEE 14 bus for several scenarios and the performance of the proposed method was compared with that of population-based optimization methods and supervised learning *** obtained results have confirmed the feasibility and effectiveness of the proposed method.

关键词： Artificial intelligence deep q network deep reinforcement learning fault diagnosis fault identification parameter identification power network

Stochastic Economic Dispatch Considering the Dependence of Multiple Wind Farms Using Multivariate Gaussian Kernel Copula

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CSEE Journal of Power and Energy Systems 2022年第5期8卷 1352-1362页

作者： Yantai Lin Tianyao Ji Yuzi Jiang q.h.wu School of Electric Power Engineering South China University of TechnologyGuangzhou 510641China

Wind farms usually cluster in areas with abundant wind ***,spatial dependence of wind speeds among nearby wind farms should be taken into account when modeling a power system with large-scale wind power *** paper proposes a novel non-parametric copula method,multivariate Gaussian kernel copula(MGKC),to describe the dependence structure of wind speeds among multiple wind *** speed scenarios considering the dependence among different wind farms are sampled from the MGKC by the quasi-Monte Carlo(qMC)method,so as to solve the stochastic economic dispatch(SED)problem,for which an improved meanvariance(MV)model is established,which targets at minimizing the expectation and risk of fuel cost *** this model,confidence interval is applied in the wind speed to obtain more practical dispatch solutions by excluding extreme scenarios,for which the quantile-copula is proposed to construct the confidence interval *** studies are carried out on a modified IEEE 30-bus power system with wind farms integrated in two areas,and the results prove the superiority of the MGKC in formulating the dependence among different wind farms and the superiority of the improved MV model based on quantilecopula in determining a better dispatch solution.

关键词： Multivariate Gaussian kernel copula quasi-Monte Carlo quantile-copula stochastic economic dispatch

Dispatchable Region for Active Distribution Networks Using Approximate Second-order Cone Relaxation

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CSEE Journal of Power and Energy Systems 2023年第6期9卷 1999-2007页

作者： Zhigang Li Wenjing huang J.h.Zheng q.h.wu School of Electric Power Engineering South China University of TechnologyGuangzhou 510640China

Uncertainty in distributed renewable generation threatens the security of power distribution *** concept of dispatchable region is developed to assess the ability of power systems to accommodate renewable generation at a given operating *** DC and linearized AC power flow equations are typically used to model dispatchable regions for transmission systems,these equations are rarely suitable for distribution *** achieve a suitable trade-off between accuracy and efficiency,this paper proposes a dispatchable region formulation for distribution networks using tight convex *** cone relaxation is adopted to reformulate AC power flow equations,which are then approximated by a polyhedron to improve ***,an efficient adaptive constraint generation algorithm is employed to construct the proposed dispatchable *** studies on distribution systems of various scales validate the computational efficiency and accuracy of the proposed method.

关键词： Dispatchable region distribution system renewable power generation second-order cone relaxation uncertainty

Constructing an Energy Function for Power Systems with DFIGWT Generation Based on a Synchronous-generator-mimicking Model

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CSEE Journal of Power and Energy Systems 2022年第1期8卷 64-75页

作者： Yang Liu Chenying Xu Zehui Lin Kaishun Xiahou q.h.wu the School of Electric Power Engineering South China University of TechnologyGuangzhou 510640China

In this paper we construct an energy function for multi-machine power systems with doubly-fed induction generator-based wind turbine(DFIGWT)according to a synchronous-generator-mimicking(SGM)model of the *** SGM model is proposed to approximate the dynamics of a *** to the modelling of a synchronous generator(SG),the internal dynamics of a DFIGWT are also described with differential equations of newly constructed virtual rotor angle and internal electromotive force(EMF)in the SGM ***,the power flow of a DFIGWT is expressed by nonlinear functions of its virtual rotor angle and internal *** SGM model bridges the gap between the irregular and complex modelling of DFIGWTs and the well-developed energy function construction techniques for SG *** on the SGM model,a numerical energy function is constructed for power systems with DFIGWT *** theoretical analysis and numerical studies were undertaken to validate that the proposed energy function satisfies the necessary conditions for an energy function of a power system.

关键词： DFIGWT energy function multi-machine power systems synchronous-generator-mimicking model