Abstract
Power system restoration following a massive blackout starts with re-energizing Primary Restorative Transmission (PRT) systems at first. As power systems have been gradually enlarged and become more complex, periodical evaluation and reassignment of PRTs are needed. So far it has been decided by try and error approach by corresponding human experts to analyze and evaluate them. This paper presents an intelligent system that finds optimal primary restoration paths using analytic and heuristic knowledge from PSS/E data, and suggests an optimal PRTs depending on the condition of Ferranti effect or a reactive power capability margin of black-start generator. This system was tested in Korea Electric Power system, and showed a promising result.
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