{"title":"Transient stability quantification of power systems with inverter-based resources via Koopman operator based machine learning approach","authors":"","doi":"10.1016/j.epsr.2024.111035","DOIUrl":null,"url":null,"abstract":"<div><p>Increased integration of inverter-based resources alters the response of large-scale power systems to contingency events. The resulting loss of control actuation and rotating inertia causes the system operating point to move substantially in a short period of time following severe disturbances. To ensure system reliability, it is essential to develop efficient <em>global</em> stability assessment tools. Toward this end, Lyapunov’s direct method has received considerable attention due to their rigorous mathematical foundation and fast stability screening. However, most existing approaches in this category are limited in application and cannot readily be extended to practical large-scale power systems. In this work, we propose a data-driven method based on <em>Koopman operator theory</em> for constructing a Lyapunov function and estimating the corresponding region of attraction (ROA). To achieve this, we employ a coordinate transformation enabled by deep neural networks. This approach addresses persistent challenges of existing direct methods in finding proper Lyapunov functions for contemporary power systems. Once the ROA is estimated, the resulting method can rapidly screen the stability of an arbitrary initial operating point without simulating the state trajectory. A numerical case study is presented using a reduced-order model of the North American Western Interconnection with battery energy storage.</p></div>","PeriodicalId":50547,"journal":{"name":"Electric Power Systems Research","volume":null,"pages":null},"PeriodicalIF":3.3000,"publicationDate":"2024-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S0378779624009210/pdfft?md5=38dd4b5637fc05b46647e59b1a1a91a5&pid=1-s2.0-S0378779624009210-main.pdf","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Electric Power Systems Research","FirstCategoryId":"5","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0378779624009210","RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ENGINEERING, ELECTRICAL & ELECTRONIC","Score":null,"Total":0}
引用次数: 0
Abstract
Increased integration of inverter-based resources alters the response of large-scale power systems to contingency events. The resulting loss of control actuation and rotating inertia causes the system operating point to move substantially in a short period of time following severe disturbances. To ensure system reliability, it is essential to develop efficient global stability assessment tools. Toward this end, Lyapunov’s direct method has received considerable attention due to their rigorous mathematical foundation and fast stability screening. However, most existing approaches in this category are limited in application and cannot readily be extended to practical large-scale power systems. In this work, we propose a data-driven method based on Koopman operator theory for constructing a Lyapunov function and estimating the corresponding region of attraction (ROA). To achieve this, we employ a coordinate transformation enabled by deep neural networks. This approach addresses persistent challenges of existing direct methods in finding proper Lyapunov functions for contemporary power systems. Once the ROA is estimated, the resulting method can rapidly screen the stability of an arbitrary initial operating point without simulating the state trajectory. A numerical case study is presented using a reduced-order model of the North American Western Interconnection with battery energy storage.
期刊介绍:
Electric Power Systems Research is an international medium for the publication of original papers concerned with the generation, transmission, distribution and utilization of electrical energy. The journal aims at presenting important results of work in this field, whether in the form of applied research, development of new procedures or components, orginal application of existing knowledge or new designapproaches. The scope of Electric Power Systems Research is broad, encompassing all aspects of electric power systems. The following list of topics is not intended to be exhaustive, but rather to indicate topics that fall within the journal purview.
• Generation techniques ranging from advances in conventional electromechanical methods, through nuclear power generation, to renewable energy generation.
• Transmission, spanning the broad area from UHV (ac and dc) to network operation and protection, line routing and design.
• Substation work: equipment design, protection and control systems.
• Distribution techniques, equipment development, and smart grids.
• The utilization area from energy efficiency to distributed load levelling techniques.
• Systems studies including control techniques, planning, optimization methods, stability, security assessment and insulation coordination.