Affine Arithmetic Based Methods For Uncertain Power System Analysis


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Affine Arithmetic-Based Methods for Uncertain Power System Analysis


Affine Arithmetic-Based Methods for Uncertain Power System Analysis

Author: Alfredo Vaccaro

language: en

Publisher: Elsevier

Release Date: 2022-04-07


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Affine Arithmetic-Based Methods for Uncertain Power System Analysis presents the unique properties and representative applications of Affine Arithmetic in power systems analysis, particularly as they are deployed for reliability optimization. The work provides a comprehensive foundation in Affine Arithmetic necessary to understand the central computing paradigms that can be adopted for uncertain power flow and optimal power flow analyses. These paradigms are adapted and applied to case studies, which integrate benchmark test systems and full step-by-step procedure for implementation so that readers are able to replicate and modify. The work is presented with illustrative numerical examples and MATLAB computations. - Provides a uniquely comprehensive review of affine arithmetic in both its core theoretical underpinnings and their developed applications to power system analysis - Details the exemplary benefits derived by the deployment of affine arithmetic methods for uncertainty handling in decision-making processes - Clarifies arithmetical complexity and eases the understanding of illustrative methodologies for researchers in both power system and decision-making fields

Interval Methods for Uncertain Power System Analysis


Interval Methods for Uncertain Power System Analysis

Author: Alfredo Vaccaro

language: en

Publisher: John Wiley & Sons

Release Date: 2023-07-25


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Interval Methods for Uncertain Power System Analysis In Interval Methods for Uncertain Power System Analysis, accomplished engineer Dr. Alfredo Vaccaro delivers a comprehensive discussion of the mathematical foundations of range analysis and its application to solving traditional power system operation problems in the presence of strong and correlated uncertainties. The book explores highly relevant topics in the area, from interval methods for uncertainty representation and management to a variety of application examples. The author offers readers the latest methodological breakthroughs and roadmaps to implementing the mathematics discussed within, as well as best practices commonly employed across the industry. Interval Methods for Uncertain Power System Analysis includes examinations of linear and non-linear equations, as well as: A thorough introduction to reliable computing, including discussions of interval arithmetic and interval-based operators Comprehensive explorations of uncertain power flow analysis, including discussions of problem formulation and sources of uncertainty in power flow analysis In-depth examinations of uncertain optimal power flow analysis Fulsome discussions of uncertain small signal stability analysis, including treatments of how to compute eigenvalues of uncertain matrices Perfect for engineers working in power flow and optimal power flow analyses, optimization theory, and computer aided simulation, Interval Methods for Uncertain Power System Analysis will also earn a place in the libraries of researchers and graduate students studying decision making under uncertainty in power systems operation.

Power System Operation with Large Scale Stochastic Wind Power Integration


Power System Operation with Large Scale Stochastic Wind Power Integration

Author: Tao Ding

language: en

Publisher: Springer

Release Date: 2016-09-17


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This book addresses the uncertainties of wind power modeled as interval numbers and assesses the physical modeling and methods for interval power flow, interval economic dispatch and interval robust economic dispatch. In particular, the optimization models are set up to address these topics and the state-of-the-art methods are employed to efficiently solve the proposed models. Several standard IEEE test systems as well as real-world large-scale Polish power systems have been tested to verify the effectiveness of the proposed models and methods. These methods can be further applied to other research fields that are involved with uncertainty.