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{ "item_title" : "Predictive Modelling for Energy Management and Power Systems Engineering", "item_author" : [" Ravinesh Deo", "Pijush Samui", "Sanjiban Sekhar Roy "], "item_description" : "Predictive Modeling for Energy Management and Power Systems Engineering introduces readers to the cutting-edge use of big data and large computational infrastructures in energy demand estimation and power management systems. The book supports engineers and scientists who seek to become familiar with advanced optimization techniques for power systems designs, optimization techniques and algorithms for consumer power management, and potential applications of machine learning and artificial intelligence in this field. The book provides modeling theory in an easy-to-read format, verified with on-site models and case studies for specific geographic regions and complex consumer markets.", "item_img_path" : "https://covers4.booksamillion.com/covers/bam/0/12/817/772/0128177721_b.jpg", "price_data" : { "retail_price" : "150.00", "online_price" : "150.00", "our_price" : "150.00", "club_price" : "150.00", "savings_pct" : "0", "savings_amt" : "0.00", "club_savings_pct" : "0", "club_savings_amt" : "0.00", "discount_pct" : "10", "store_price" : "" } }
Predictive Modelling for Energy Management and Power Systems Engineering|Ravinesh Deo

Predictive Modelling for Energy Management and Power Systems Engineering

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Overview

Predictive Modeling for Energy Management and Power Systems Engineering introduces readers to the cutting-edge use of big data and large computational infrastructures in energy demand estimation and power management systems. The book supports engineers and scientists who seek to become familiar with advanced optimization techniques for power systems designs, optimization techniques and algorithms for consumer power management, and potential applications of machine learning and artificial intelligence in this field. The book provides modeling theory in an easy-to-read format, verified with on-site models and case studies for specific geographic regions and complex consumer markets.

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Details

  • ISBN-13: 9780128177723
  • ISBN-10: 0128177721
  • Publisher: Elsevier
  • Publish Date: September 2020
  • Dimensions: 9.25 x 7.5 x 1.12 inches
  • Shipping Weight: 2.07 pounds
  • Page Count: 552

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