{"title":"Semi-Implicit Continuous Newton Method for Power Flow Analysis","authors":"Ruizhi Yu;Wei Gu;Yijun Xu;Shuai Lu;Suhan Zhang","doi":"10.17775/CSEEJPES.2024.05770","DOIUrl":null,"url":null,"abstract":"As an effective emulator of ill-conditioned power flow, continuous Newton methods (CNMs) have been extensively investigated using explicit and implicit numerical integration algorithms. However, explicit CNMs often suffer from non-convergence due to their limited stability region, while implicit CNMs require additional iterative loops to solve nonlinear equations. To address this, we propose a semi-implicit version of CNM. We formulate the power flow equations as a set of differential algebraic equations (DAEs), and solve the DAEs with the stiffly accurate Rosenbrock type method (SARM). The proposed method succeeds the numerical robustness from the implicit CNM framework while prevents the iterative solution of nonlinear systems, hence revealing higher convergence speed and computation efficiency. We develop a novel 4-stage, 3rd-order hyper-stable SARM with an embedded 2nd-order formula for adaptive step size control. This design enhances convergence through damping adjustment. Case studies on ill-conditioned systems verify the alleged performance. An algorithm extension for MATPOWER is made available on Github for benchmarking.","PeriodicalId":10729,"journal":{"name":"CSEE Journal of Power and Energy Systems","volume":"11 4","pages":"1957-1961"},"PeriodicalIF":5.9000,"publicationDate":"2025-03-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11006441","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"CSEE Journal of Power and Energy Systems","FirstCategoryId":"5","ListUrlMain":"https://ieeexplore.ieee.org/document/11006441/","RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ENERGY & FUELS","Score":null,"Total":0}
引用次数: 0
Abstract
As an effective emulator of ill-conditioned power flow, continuous Newton methods (CNMs) have been extensively investigated using explicit and implicit numerical integration algorithms. However, explicit CNMs often suffer from non-convergence due to their limited stability region, while implicit CNMs require additional iterative loops to solve nonlinear equations. To address this, we propose a semi-implicit version of CNM. We formulate the power flow equations as a set of differential algebraic equations (DAEs), and solve the DAEs with the stiffly accurate Rosenbrock type method (SARM). The proposed method succeeds the numerical robustness from the implicit CNM framework while prevents the iterative solution of nonlinear systems, hence revealing higher convergence speed and computation efficiency. We develop a novel 4-stage, 3rd-order hyper-stable SARM with an embedded 2nd-order formula for adaptive step size control. This design enhances convergence through damping adjustment. Case studies on ill-conditioned systems verify the alleged performance. An algorithm extension for MATPOWER is made available on Github for benchmarking.
期刊介绍:
The CSEE Journal of Power and Energy Systems (JPES) is an international bimonthly journal published by the Chinese Society for Electrical Engineering (CSEE) in collaboration with CEPRI (China Electric Power Research Institute) and IEEE (The Institute of Electrical and Electronics Engineers) Inc. Indexed by SCI, Scopus, INSPEC, CSAD (Chinese Science Abstracts Database), DOAJ, and ProQuest, it serves as a platform for reporting cutting-edge theories, methods, technologies, and applications shaping the development of power systems in energy transition. The journal offers authors an international platform to enhance the reach and impact of their contributions.