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A Monte Carlo simulation-based decision support system for reliability analysis of Taiwan’s power system: Framework and empirical study

Hsiang-Hua Yu, Kuo-Hao Chang, Hsin-Wei Hsu and Robert Cuckler

Energy, 2019, vol. 178, issue C, 252-262

Abstract: Taiwan aims to greatly increase renewable energy generation by 2025; as such, an important topic is whether to increase the statutory planning reserve margin (PRM) to overcome high share of Variable Renewable Energy (VRE). Therefore, in this research, the goal is to investigate the use of loss of load expectation (LOLE) as a risk measure to provide insights into how the available power capacity, at a national level, can fail to meet the customer load. A Monte-Carlo-simulation-based framework was proposed to enable fast calculation of the LOLE. Considering a general national power system that consists various sources of renewable and conventional power, the proposed framework allows for a scenario-based calculation under the realistic situation that various conventional energy sources can be ramped up to dynamically meet losses of load. To make the methodology more user-friendly and applicable to power systems, a decision support system was developed. Moreover, a reliability analysis of Taiwan’s power system was conducted to show how to evaluate the impact of energy policy by 2025. Sensitivity analyses on two scenarios (with and without limiting coal-fired power generation) on LOLE were done. Finally, recommendations related to the reliability of the power system under Taiwan’s energy transition were provided.

Keywords: Renewable energy; Power system; Loss of load expectation; Monte Carlo simulation; Reliability analysis (search for similar items in EconPapers)
Date: 2019
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