Some countries have announced national benchmark rates,while others have been working on the recent trend in which the London Interbank Offered Rate will be retired at the end of 2021.Considering that Turkey announced...Some countries have announced national benchmark rates,while others have been working on the recent trend in which the London Interbank Offered Rate will be retired at the end of 2021.Considering that Turkey announced the Turkish Lira Overnight Reference Interest Rate(TLREF),this study examines the determinants of TLREF.In this context,three global determinants,five country-level macroeconomic determinants,and the COVID-19 pandemic are considered by using daily data between December 28,2018,and December 31,2020,by performing machine learning algorithms and Ordinary Least Square.The empirical results show that(1)the most significant determinant is the amount of securities bought by Central Banks;(2)country-level macroeconomic factors have a higher impact whereas global factors are less important,and the pandemic does not have a significant effect;(3)Random Forest is the most accurate prediction model.Taking action by considering the study’s findings can help support economic growth by achieving low-level benchmark rates.展开更多
新型电力系统中新能源、水电等清洁能源占比不断提升,高比例新能源带来的频率越限和高比例水电带来的超低频振荡风险日益突出。为支撑新型电力系统不同场景下频率安全稳定分析与控制研究需求,构建频率稳定标准算例(The Chinese Society ...新型电力系统中新能源、水电等清洁能源占比不断提升,高比例新能源带来的频率越限和高比例水电带来的超低频振荡风险日益突出。为支撑新型电力系统不同场景下频率安全稳定分析与控制研究需求,构建频率稳定标准算例(The Chinese Society for Electrical Engineering-frequency stability,CSEE-FS)。针对传统频率稳定问题,构建新能源装机及出力占比均在50%以上的高频、低频场景,分析故障强度、新能源出力及控制策略等对频率偏差最大值及其出现时间、稳态频率偏差的影响;针对超低频振荡问题,构建水电出力占比达89%场景,分析交直流不同故障形态、调速器关键参数、系统惯量等对振荡频率、振荡幅值的影响。敏感性分析结果表明,该文所建算例系统可准确反映不同频率稳定场景特性,且具备良好的扩展性,能满足新型电力系统频率安全稳定分析与控制方法验证需求。展开更多
文摘Some countries have announced national benchmark rates,while others have been working on the recent trend in which the London Interbank Offered Rate will be retired at the end of 2021.Considering that Turkey announced the Turkish Lira Overnight Reference Interest Rate(TLREF),this study examines the determinants of TLREF.In this context,three global determinants,five country-level macroeconomic determinants,and the COVID-19 pandemic are considered by using daily data between December 28,2018,and December 31,2020,by performing machine learning algorithms and Ordinary Least Square.The empirical results show that(1)the most significant determinant is the amount of securities bought by Central Banks;(2)country-level macroeconomic factors have a higher impact whereas global factors are less important,and the pandemic does not have a significant effect;(3)Random Forest is the most accurate prediction model.Taking action by considering the study’s findings can help support economic growth by achieving low-level benchmark rates.
文摘新型电力系统中新能源、水电等清洁能源占比不断提升,高比例新能源带来的频率越限和高比例水电带来的超低频振荡风险日益突出。为支撑新型电力系统不同场景下频率安全稳定分析与控制研究需求,构建频率稳定标准算例(The Chinese Society for Electrical Engineering-frequency stability,CSEE-FS)。针对传统频率稳定问题,构建新能源装机及出力占比均在50%以上的高频、低频场景,分析故障强度、新能源出力及控制策略等对频率偏差最大值及其出现时间、稳态频率偏差的影响;针对超低频振荡问题,构建水电出力占比达89%场景,分析交直流不同故障形态、调速器关键参数、系统惯量等对振荡频率、振荡幅值的影响。敏感性分析结果表明,该文所建算例系统可准确反映不同频率稳定场景特性,且具备良好的扩展性,能满足新型电力系统频率安全稳定分析与控制方法验证需求。
