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Computational Methods for Electric Power Systems (Paperback, 3rd edition): Mariesa L. Crow Computational Methods for Electric Power Systems (Paperback, 3rd edition)
Mariesa L. Crow
R1,839 Discovery Miles 18 390 Ships in 10 - 15 working days

Computational Methods for Electric Power Systems introduces computational methods that form the basis of many analytical studies in power systems. The book provides the background for a number of widely used algorithms that underlie several commercial software packages, linking concepts to power system applications. By understanding the theory behind many of the algorithms, the reader can make better use of the software and make more informed decisions (e.g., choice of integration method and step size in simulation packages). This Third Edition contains new material on preconditioners for linear iterative methods, Broyden's method, and Jacobian-free Newton-Krylov methods. It includes additional problems and examples, as well as updated examples on sparse lower-upper (LU) factorization. It also adds coverage of the eigensystem realization algorithm and the double-shift method for computing complex eigenvalues.

Computational Methods for Electric Power Systems (Hardcover, 3rd edition): Mariesa L. Crow Computational Methods for Electric Power Systems (Hardcover, 3rd edition)
Mariesa L. Crow
R4,513 Discovery Miles 45 130 Ships in 10 - 15 working days

Computational Methods for Electric Power Systems introduces computational methods that form the basis of many analytical studies in power systems. The book provides the background for a number of widely used algorithms that underlie several commercial software packages, linking concepts to power system applications. By understanding the theory behind many of the algorithms, the reader can make better use of the software and make more informed decisions (e.g., choice of integration method and step size in simulation packages). This Third Edition contains new material on preconditioners for linear iterative methods, Broyden's method, and Jacobian-free Newton-Krylov methods. It includes additional problems and examples, as well as updated examples on sparse lower-upper (LU) factorization. It also adds coverage of the eigensystem realization algorithm and the double-shift method for computing complex eigenvalues.

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