Next Article in Journal
A Comparative Study of the Fitness and Trueness of a Three-Unit Fixed Dental Prosthesis Fabricated Using Two Digital Workflows
Previous Article in Journal
Crossover Effect in Cement-Based Materials: A Review
Previous Article in Special Issue
The Influence of Capacitance and Inductance Changes on Frequency Response of Transformer Windings
Article Menu

Export Article

Open AccessFeature PaperArticle

Quantifying Power System Operational Reliability

Power Systems Research Group, Department of Electrical and Computer Engineering, University of Saskatchewan, Saskatoon, SK S7N 5A2, Canada
Author to whom correspondence should be addressed.
Appl. Sci. 2019, 9(14), 2777;
Received: 28 April 2019 / Revised: 6 July 2019 / Accepted: 8 July 2019 / Published: 10 July 2019
(This article belongs to the Special Issue Power System Reliability)
PDF [1083 KB, uploaded 10 July 2019]


Rising uncertainty in power systems due to ongoing system and operational changes has led to increasing risks in operating a system in a reliable and economic manner. There are growing reliability concerns with the widely used methods, such as the N-1 criterion, to determine operating reserve requirement during unit commitment, and the economic load dispatch method to allocate regulating margin to respond to disturbances. These deterministic methods do not consider the uncertainty or stochastic nature of power systems and are often inadequate to maintain the required operating reliability of modern power systems. This paper introduces a reliability index, designated as the committed generators’ response risk (CGRR) that can be used to maintain a specified level of operating reliability. A probabilistic method to evaluate the CGRR is presented and validated using a Monte Carlo simulation technique. An application of the new index and the methodology is illustrated using the IEEE Reliability Test System. The CGRR provides a comprehensive operating risk measurement of the committed generation until further assistance is available to support the system, and therefore helps operators in decision making for unit commitment and dispatch of the generating units to meet the projected load in the short future time. View Full-Text
Keywords: power system reliability; operating risk; regulating margin; unit commitment; load dispatch; Monte Carlo simulation power system reliability; operating risk; regulating margin; unit commitment; load dispatch; Monte Carlo simulation

Figure 1

This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).

Share & Cite This Article

MDPI and ACS Style

Nepal, N.; Karki, R. Quantifying Power System Operational Reliability. Appl. Sci. 2019, 9, 2777.

Show more citation formats Show less citations formats

Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Related Articles

Article Metrics

Article Access Statistics



[Return to top]
Appl. Sci. EISSN 2076-3417 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top