Computing Safety Margins of a Generation Rejection Scheme: A Framework for Online Implementation

Daham Min, Seog Joo Kim, Sangsoo Seo, Young Hwan Moon, Kai Sun, Joe H. Chow, Kyeon Hur

Research output: Contribution to journalArticlepeer-review

4 Citations (Scopus)

Abstract

This paper develops an analytical method for assessing the safety margins of a generation rejection scheme (GRS) reliably. It also presents a practical framework for implementing the proposed method integrated with energy management system and synchrophasor data in power grid operations. By employing a concept of virtual load connected to the critical generation bus of the single machine equivalent of the real-time operations case, we calculate, similar to transfer analysis, the allowable power to the virtual load in MW after tripping the pre-planned number of generation units and thus determine the required rejected power for the GRS initiating scenario. This virtual loading can be interpreted as the safety margin of the designed GRS to ensure its stabilizing operation. This research further develops a computationally efficient technique for refining the safety margin potentially with the measured synchrophasor data to improve the robustness of the GRS in practice. Understanding the safety margin is envisioned to help investigate and identify other practical options than tripping generators for protecting the system integrity. Accuracy and efficacy are demonstrated for real Korea power system cases.

Original languageEnglish
Pages (from-to)2337-2346
Number of pages10
JournalIEEE Transactions on Smart Grid
Volume9
Issue number3
DOIs
Publication statusPublished - 2018 May

Bibliographical note

Funding Information:
Manuscript received May 4, 2016; revised October 13, 2016; accepted November 22, 2016. Date of publication December 5, 2016; date of current version April 19, 2018. This work was supported by the Basic Science Research Program through the National Research Foundation of Korea funded by the Ministry of Education, Science and Technology under Grant 2016R1D1A1B03930582. Paper no. TSG-00604-2016.

Publisher Copyright:
© 2016 IEEE.

All Science Journal Classification (ASJC) codes

  • Computer Science(all)

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