top of page

Live Stream Online Family

Public·76 members
Jonathan Campbell
Jonathan Campbell

Computational Methods For Electric Power Systems, Second Edition Crow, Mariesa|| |BEST|


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 behi




computational methods for electric power systems, second edition crow, mariesa||



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).


Computational Methods for Electric Power Systems is an introductory overview of computational methods used for analytical studies in power systems and other engineering and scientific fields. As power systems increasingly operate under stressed conditions, techniques such as computer simulation remain integral to control and security assessment. This volume analyzes the algorithms used in commercial analysis packages and presents salient examples of their implementation that are simple and thorough enough to be reproduced easily. Most of the examples were produced using MATLAB language.


Dr. Mariesa Crow is a professor of electrical engineering at Missouri University of Science and Technology in Rolla. She is director of the Energy Research and Development Center. Her areas of research include: computer-aided analysis of power systems dynamics and security analysis, voltage stability, computational algorithms for analyzing stressed, non-linear, non-continuous systems. Power-electronic applications in bulk power systems (FACTS), and parameter estimation.


Mariesa L. Crow is a professor of electrical engineering at the Missouri University of Science and Technology, Rolla, USA. Dr. Crow is director of the Energy Research and Development Center. Her areas of research include computer-aided analysis of power systems; dynamics and security analysis; voltage stability; computational algorithms for analyzing stressed, non-linear, non-continuous systems; power-electronic applications in bulk power systems (FACTS); and parameter estimation.


Abstract:In the past decade, plug-in (hybrid) electric vehicles (PHEVs) have been widely proposed as a viable alternative to internal combustion vehicles to reduce fossil fuel emissions and dependence on petroleum. Off-peak vehicle charging is frequently proposed to reduce the stress on the electric power grid by shaping the load curve. Time of use (TOU) rates have been recommended to incentivize PHEV owners to shift their charging patterns. Many utilities are not currently equipped to provide real-time use rates to their customers, but can provide two or three staggered rate levels. To date, an analysis of the optimal number of levels and rate-duration of TOU rates for a given consumer demographic versus utility generation mix has not been performed. In this paper, we propose to use the U.S. National Household Travel Survey (NHTS) database as a basis to analyze typical PHEV energy requirements. We use Monte Carlo methods to model the uncertainty inherent in battery state-of-charge and trip duration. We conclude the paper with an analysis of a different TOU rate schedule proposed by a mix of U.S. utilities. We introduce a centralized scheduling strategy for PHEV charging using a genetic algorithm to accommodate the size and complexity of the optimization.Keywords: electric vehicles; economic dispatch; energy management


About

Welcome to the group! You can connect with other members, ge...

Members

bottom of page