المؤشرات الاحتمالية لأداء نظم توليد و نقل القدرة

Abstract EN

The capacity function in a general flow network has been studied as a pseudo-switching function in the successes of network branches.

In addition, this function has been computed via the algorithm of equivalent branches and the algorithm of minimal cutsets.

These algorithms are manual recently developed techniques that are suitable for computer programming.

Consequently, both algorithms have been utilized in the probabilistic analysis of power generation and transmission networks.

This analysis covers the evaluation of certain general indices that are usually employed for measuring the performance of power systems.

These indices include both the expectation and the standard deviation of the capacity and the demand not served as well as the loss of load probability, all of which are instantaneous indices assuming a constant load.

Moreover, the analysis includes certain average indices, like the expected energy not served (expected unserved energy) and the loss of load expectation, which adopt a more realistic load model allowing stepwise changes in load value during a finite time interval.

In addition, some new indices for measuring the importance of various branches in the network are defined, and methods for their evaluation are explained.

In most cases, the pictorial property of the Karnaugh map has been utilized in the representation of various algebraic relations, and in the classification of causes of loss of load in the different network states.

Finally, the quantitative or qualitative utilization of the indices considered is discussed and several new research topics extending the present work are proposed.