This paper presents a novel method for accurately estimating the cumulative capacity credit(CCC)of renewable energy(RE)projects.Leveraging data from the main interconnected system(MIS)of Oman for 2028,where a substant...This paper presents a novel method for accurately estimating the cumulative capacity credit(CCC)of renewable energy(RE)projects.Leveraging data from the main interconnected system(MIS)of Oman for 2028,where a substantial increase in RE generation is anticipated,the method is introduced alongside the traditional effective load carrying capability(ELCC)method.To ensure its robustness,we compare CCC results with ELCC calculations using two distinct standards of reliability criteria:loss of load hours(LOLH)at 24 hour/year and 2.4 hour/year.The method consistently gives accurate results,emphasizing its exceptional accuracy,efficiency,and simplicity.A notable feature of the method is its independence from loss of load probability(LOLP)calculations and the iterative procedures associated with analytic-based reliability methods.Instead,it relies solely on readily available data such as annual hourly load profiles and hourly generation data from integrated RE plants.This innovation is of particular significance to prospective independent power producers(IPPs)in the RE sector,offering them a valuable tool for estimating capacity credits without the need for sensitive generating unit forced outage rate data,often restricted by privacy concerns.展开更多
文摘This paper presents a novel method for accurately estimating the cumulative capacity credit(CCC)of renewable energy(RE)projects.Leveraging data from the main interconnected system(MIS)of Oman for 2028,where a substantial increase in RE generation is anticipated,the method is introduced alongside the traditional effective load carrying capability(ELCC)method.To ensure its robustness,we compare CCC results with ELCC calculations using two distinct standards of reliability criteria:loss of load hours(LOLH)at 24 hour/year and 2.4 hour/year.The method consistently gives accurate results,emphasizing its exceptional accuracy,efficiency,and simplicity.A notable feature of the method is its independence from loss of load probability(LOLP)calculations and the iterative procedures associated with analytic-based reliability methods.Instead,it relies solely on readily available data such as annual hourly load profiles and hourly generation data from integrated RE plants.This innovation is of particular significance to prospective independent power producers(IPPs)in the RE sector,offering them a valuable tool for estimating capacity credits without the need for sensitive generating unit forced outage rate data,often restricted by privacy concerns.
