Composite Generation and Transmission System Reliability Evaluation including System Health Constraints

The probability of failure at any major load point is a basic but useful index that should be determined first in the reliability study of generation and transmission systems. There is, however, considerable reluctance by system planners to utilize a single risk index to determine the capacity of generating units and transmission network to convey the energy to the major load points. This paper presents an approach designated as system wellbeing analysis, which incorporates the conventional risk index as well as the accepted deterministic criteria identified as being healthy and marginal states. A technique of calculating the well-being indices, together with the effects from factors such as peak load, load factor, load curtailment philosophy and contingency level selection are illustrated by application to an educational test system designated as the RBTS. INTRODUCTION One of the necessary considerations in planning and evaluating composite generation and transmission systems, commonly referred to as bulk power systems, is the system reliability. In fact, it is one important aspect of quality of electricity supply. Bulk power systems reliability is usually maintained very high because bulk power outages affect a large number of customers simultaneously [1]. The basic concern in composite generation and transmission systems is the total problem of assessing the ability of combined generation and transmission systems to supply required and suitable electrical energy to the major system load points. Probability methods are widely used in generating capacity evaluation [2]. On the other hand, transmission system evaluation is mostly based on deterministic criteria and the main principle is maintaining adequate service under most likely outages, but to accept some degradation of performance such as line overloads and station low voltages. The essential drawback of deterministic criteria and techniques is that they do not and can not account for the probabilistic and stochastic nature of system behavior and are not responsive to many of the parameters such as load and risk nature, which actually influence system reliability. Although currently deterministic criteria and techniques are still predominant, however, there is nowadays a widely held recognition that the statistical assessment of past performance and the probabilistic evaluation of future performance have great value in the planning and operation of a power system. This is the natural result of the change of economic, social and political climate in which the electric power industries have been operating during the last few decades. The most 1 School of Electrical & Electronic Engineering, Nanyang Technological University, Singapore 639798