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{ "item_title" : "Affine Arithmetic-Based Methods for Uncertain Power System Analysis", "item_author" : [" Alfredo Vaccaro", "Antonio Pepiciello "], "item_description" : "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.", "item_img_path" : "https://covers3.booksamillion.com/covers/bam/0/32/390/502/0323905021_b.jpg", "price_data" : { "retail_price" : "180.00", "online_price" : "180.00", "our_price" : "180.00", "club_price" : "180.00", "savings_pct" : "0", "savings_amt" : "0.00", "club_savings_pct" : "0", "club_savings_amt" : "0.00", "discount_pct" : "10", "store_price" : "" } }
Affine Arithmetic-Based Methods for Uncertain Power System Analysis|Alfredo Vaccaro

Affine Arithmetic-Based Methods for Uncertain Power System Analysis

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Overview

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.

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Details

  • ISBN-13: 9780323905022
  • ISBN-10: 0323905021
  • Publisher: Elsevier
  • Publish Date: April 2022
  • Dimensions: 9 x 6 x 0.35 inches
  • Shipping Weight: 0.5 pounds
  • Page Count: 164

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