Ascending Load Order Method for Capacity Credit Estimation for Renewable Energy Projects

• Published in: 2024 IEEE 22nd Mediterranean Electrotechnical Conference (MELECON) pp. 1013 - 1018
• Main Authors: Malik, Arif S., Al Umairi, Majid A.
• Format: Conference Proceeding
• Language: English
• Published: IEEE 25-06-2024
• Subjects: Accuracy; capacity credit; Data privacy; Effective load carrying capability; generation system reliability; Interconnected systems; Loss-of-load expectation; Measurement; Probability; renewable energy resources; Renewable energy sources; Robustness
• ISSN: 2158-8481
• DOI: 10.1109/MELECON56669.2024.10608668

This research introduces an innovative and straightforward technique for accurately evaluating the cumulative capacity credit of renewable energy (RE) projects. Utilizing load and generation data from the IEEE RTS, we present this novel approach alongside the traditional effective load carrying capability (ELCC) method. To ensure its dependability, we conduct a comparative analysis of Cumulative Capacity Credit (CCC) outcomes with ELCC calculations, utilizing a Loss of Load Hours (LOLH) metric of 3 hours per year. Our method demonstrates precise results, emphasizing its exceptional accuracy, efficiency, and simplicity. A notable feature of our approach is its independence from Loss of Load Probability (LOLP) calculations and the iterative processes associated with reliability methods based on analytics. Instead, it relies solely on easily accessible data, such as annual hourly load profiles and hourly generation data from integrated RE plants. This advancement is particularly significant for potential Independent Power Producers (IPPs) in the RE sector, providing them with a valuable tool for estimating capacity credits without the need for sensitive generating unit forced outage rate data, often constrained by privacy considerations.