4.6 Article

Design and Implementation of Probabilistic Transient Stability Approach to Assess the High Penetration of Renewable Energy in Korea

Journal

SUSTAINABILITY
Volume 13, Issue 8, Pages -

Publisher

MDPI
DOI: 10.3390/su13084205

Keywords

renewable energy; probabilistic transient stability; transient stability index; cumulative distribution functions (CDF); automatic simulation based on Python

Funding

  1. Human Resources Program in Energy Technology of the Korea Institute of Energy Technology Evaluation and Planning (KETEP) from the Ministry of Trade, Industry & Energy, Republic of Korea [20194010201760]
  2. Korea Electric Power Corporation (KEPCO)
  3. Korea Evaluation Institute of Industrial Technology (KEIT) [20194010201760] Funding Source: Korea Institute of Science & Technology Information (KISTI), National Science & Technology Information Service (NTIS)

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This paper introduces a method of calculating renewable energy capacity based on probabilistic transient stability assessment, as Korea increases its renewable energy output in response to environmental problems. The stability of renewables must be considered, and the method involves four algorithms to calculate renewable energy capacity, validated through a large-scale power system.
Recently, because of the many environmental problems worldwide, Korea is moving to increase its renewable energy output due to the Renewable 3020 Policy. Renewable energy output can change depending on environmental factors. It is for this reason that institutions should consider the instability of renewables when linked to the electric system. This paper describes the methodology of renewable energy capacity calculation based on probabilistic transient stability assessment. Probabilistic transient stability assessment consists of four algorithms: first, to create probabilistic scenarios based on the effective capacity history of renewable energy; second, to evaluate probabilistic transient stability based on transient stability index, interpolation-based transient stability index estimation, reduction-based transient stability index calculation, etc.; third, to implement multiple scenarios to calculate renewable energy capacity using probabilistic evaluation index; and finally, to create a probabilistic transient stability assessment simulator based on Python. This paper calculated renewable energy capacity based on large-scale power system to validate consistency of the proposed paper.

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