Affine Arithmetic-Based Methods for Uncertain Power System Analysis 1st Edition – Ebook Instant Download/Delivery ISBN(s): 9780323905022,0323905021,9780323905039, 032390503X
Product details:
- ISBN-10 : 0323905021
- ISBN-13 : 978-0323905022
- Author:
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
Table of contents:
- Chapter 1: Uncertainty management in power systems
- Chapter 2: Elements of reliable computing
- Chapter 3: Uncertain power flow analysis
- Chapter 4: Uncertain optimal power flow analysis
- Chapter 5: Unified AA-based solution of uncertain PF and OPF problems
- Chapter 6: Uncertain power system reliability analysis
- Chapter 7: Uncertain analysis of multi-energy systems
- Chapter 8: Enabling methodologies for reducing the computational burden in AA-based computing
- Chapter 9: Uncertain voltage stability analysis by affine arithmetic
- Chapter 10: Reliable microgrids scheduling in the presence of data uncertainties