Cyber Physical Power Systems State Estimation
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Cyber-Physical Power Systems State Estimation
Cyber-Physical Power System State Estimation updates classic state estimation tools to enable real-time operations and optimize reliability in modern electric power systems. The work introduces and contextualizes the core concepts and classic approaches to state estimation modeling. It builds on these classic approaches with a suite of data-driven models and non-synchronized measurement tools to reflect current measurement trends required by increasingly more sophisticated grids. Chapters outline core definitions, concepts and the network analysis procedures involved in the real-time operation of EPS. Specific sections introduce power flow problem in EPS, highlighting network component modeling and power flow equations for state estimation before addressing quasi static state estimation in electrical power systems using Weighted Least Squares (WLS) classical and alternatives formulations. Particularities of the state estimation process in distribution systems are also considered. Finally, the work goes on to address observability analysis, measurement redundancy and the processing of gross errors through the analysis of WLS static state estimator residuals. - Develops advanced approaches to smart grid real-time monitoring through quasi-static model state estimation and non-synchronized measurements system models - Presents a novel, extended optimization, physics-based model which identifies and corrects for measurement error presently egregiously discounted in classic models - Demonstrates how to embed cyber-physical security into smart grids for real-time monitoring - Introduces new approaches to calculate power flow in distribution systems and for estimating distribution system states - Incorporates machine-learning based approaches to complement the state estimation process, including pattern recognition-based solutions, principal component analysis and support vector machines
Smart Cyber-Physical Power Systems, Volume 2
A practical roadmap to the application of artificial intelligence and machine learning to power systems In an era where digital technologies are revolutionizing every aspect of power systems, Smart Cyber-Physical Power Systems, Volume 2: Solutions from Emerging Technologies shifts focus to cutting-edge solutions for overcoming the challenges faced by cyber-physical power systems (CPSs). By leveraging emerging technologies, this volume explores how innovations like artificial intelligence, machine learning, blockchain, quantum computing, digital twins, and data analytics are reshaping the energy sector. This volume delves into the application of AI and machine learning in power system optimization, protection, and forecasting. It also highlights the transformative role of blockchain in secure energy trading and digital twins in simulating real-time power system operations. Advanced big data techniques are presented for enhancing system planning, situational awareness, and stability, while quantum computing offers groundbreaking approaches to solving complex energy problems. For professionals and researchers eager to harness cutting-edge technologies within smart power systems, Volume 2 proves indispensable. Filled with numerous illustrations, case studies, and technical insights, it offers forward-thinking solutions that foster a more efficient, secure, and resilient future for global energy systems, heralding a new era of innovation and transformation in cyber-physical power networks. Welcome to the exploration of Smart Cyber-Physical Power Systems (CPPSs), where challenges are met with innovative solutions, and the future of energy is shaped by the paradigms of AI/ML, Big Data, Blockchain, IoT, Quantum Computing, Information Theory, Edge Computing, Metaverse, DevOps, and more.
Cyber-Physical Energy and Power Systems
This book discusses recent advances in cyber-physical power systems (CPPS) in the modeling, analysis and applications of smart grid. It introduces a series of models, such as an analysis of interaction between the power grid and the communication network, differential protection in smart distribution systems, data flow for VLAN-based communication in substations, a co-simulation model for investigating the impacts of cyber-contingency and distributed control systems as well as the analytical techniques used in different parts of cyber physical energy systems. It also discusses methods of cyber-attack on power systems, particularly false data injection. The results presented are a comprehensive summary of the authors’ original research conducted over a period of 5 years. The book is of interest to university researchers, R&D engineers and graduate students in power and energy systems.