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Springer Nature Inspired Optimization for Electrical Power Systems

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Description

This comprehensive guide explores nature-inspired optimization methods applied to complex electrical power system challenges, including economical load dispatch, demand supply management in microgrids, levelized energy pricing, load frequency control, congestion management, and reactive power management in radial distribution systems. Electrical power systems present significant computational obstacles due to massive dimensions, nonlinearity, non-convexity, and discontinuity in objective functions, combined with numerous equality and inequality constraints. This Springer publication addresses these challenges by presenting practical optimization algorithms and techniques specifically designed to solve real-world power system problems efficiently and effectively.

Key Features

Nature-inspired optimization methods tailored for complex electrical power system applications and challenges.

Covers economical load dispatch, demand supply management in microgrids, and levelized energy pricing strategies.

Addresses load frequency control, congestion management, and reactive power management in radial distribution systems.

Springer publication designed for engineers solving nonlinear and non-convex power system optimization problems.

Practical algorithms handle large-scale systems with multiple equality and inequality constraints.

Product Specifications

Format
paperback
Domain
Amazon UK
Release Date
08 April 2021
Listed Since
12 March 2021

Barcode

No barcode data available

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