Allen J. Wood

A comprehensive text on the operation and control of power generation and transmission systems In the ten years since Allen J. Wood and Bruce F. Wollenberg presented their comprehensive introduction to the engineering and economic factors involved in operating and controlling power generation systems in electric utilities, the electric power industry has undergone unprecedented change. Deregulation, open access to transmission systems, and the birth of independent power producers have altered the structure of the industry, while technological advances have created a host of new opportunities

This is a significant work in an important area, and one that is receiving growing attention. It has been estimated that many professional meetings currently devote a third or more of their time to questions of power-system reliability. The book digests this research and covers the standard techniques and methods that are currently standard. The presentation employs a minimum of mathematics. The five chapters of this book collect and illustrate techniques that have been applied to the prediction of reliability and availability of the various specific segments of an electric power system. The text emphasizes the numerical procedures employed in making these reliability and availability predictions. Other related criteria that have been put forward in the literature, such as adequacy, dependability, and security, are also introduced and defined as needed and as applied in specific contexts. The book opens with a discussion of reliability and availability applications to transmission and distribution systems, treating independent component outages and their effects on the continuity of supply. It then takes up models for generation planning and proceeds to the area of bulk power supply system reliability evaluation, offering methods for prediction of composite reliability of the generation and transmission systems. A final chapter extends the study into operating reliability assessments concerned with reserve problems: It considers the adequacy of the generating system to meet forecasted loads a short period ahead. The book is the sixth in the Modern Electrical Technology series, edited by Alexander Kusko.

This paper is a continuation of the work started in [1] and is aimed at incorporating a model of the power system load with the generation system model developed previously. Combination of this load and the generation model permits computation of the availability, frequency of occurrence, and mean duration of generation reserve, or margin states. The results of this work are illustrated by continuation of a simple numerical example begun in Part I. The most widely applied of the previously developed techniques for assessing generation system reliability, the loss-of-load and loss-of-capacity methods, assume fixed outage or load duration intervals. The present model, on the other hand, uses an exponential distribution of durations. The reserve margin states developed using the exponential distributions contain data giving both the availability of each margin state and the expected frequency of recurrence. Previous methods yield only the availability of the reserve margin states, or else availability and frequency data for generating capacity states, not considering the load. The method presented and illustrated may be extended t o consider the calculation of operating reliability or the inclusion of the effects of a simple transmission system.

In the planning and design of a high-voltage transmission network it is sometimes desirable to install controllable kilovar ar capacity at several locations to support bus voltages during emergencies. This problem arises when transmission line or generation outages cause bus voltage magnitudes to decrease below desirable limits. The problem of selecting where and how much kilovar capacity is required has many feasible solutions which satisfy the conditions imposed. A method for locating that solution with the minimum total installed capacity is presented. This nonlinear programming problem will be solved by using a linear approximation, solving the linear programming problem, and then correcting the linear approximation through the use of differences between the linear and nonlinear results. The method is illustrated by an application to a portion of a large high-voltage network.