A Methodology for Quantifying Reliability Benefits From Improved Solar Power Forecasting in Multi-Timescale Power System Operations

被引:28
作者
Cui, Mingjian [1 ]
Zhang, Jie [1 ]
Hodge, Bri-Mathias [2 ]
Lu, Siyuan [3 ]
Hamann, Hendrik F. [3 ]
机构
[1] Univ Texas Dallas, Dept Mech Engn, Dallas, TX 75080 USA
[2] Natl Renewable Energy Lab, Golden, CO 80401 USA
[3] IBM TJ Watson Res Ctr, Yorktown Hts, NY 10598 USA
关键词
Area control error; multi-timescale power system operation; photovoltaic; reliability benefit; forecast; GENERATION;
D O I
10.1109/TSG.2017.2728480
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
Solar power forecasting improvements are mainly evaluated by statistical and economic metrics, and the practical reliability benefits of these forecasting enhancements have not yet been well quantified. This paper aims to quantify reliability benefits from solar power forecasting improvements. To systematically analyze the relationship between solar power forecasting improvements and reliability performance in power system operations, an expected synthetic reliability (ESR) metric is proposed to integrate multiple state-of-the-art independent reliability metrics. The absolute value and standard deviation of area control errors (ACEs), and the North American Electric Reliability Corporation Control Performance Standard 2 (CPS2) score are calculated through a multi-timescale scheduling simulation, including the day-ahead unit commitment, real-time unit commitment, real-time economic dispatch, and automatic generation control sub-models. The absolute ACE in energy, CPS2 violations, CPS2 score, and standard deviation of the raw ACE are all calculated and combined as the ESR metric. Numerical simulations show that the reliability benefits of multi-timescale power system operations are significantly increased due to the improved solar power forecasts.
引用
收藏
页码:6897 / 6908
页数:12
相关论文
共 26 条
[1]  
[Anonymous], 2015, NRELTP5D0063175
[2]  
[Anonymous], 2003, Market Operations in Electric Power Systems: Forecasting, Scheduling, and Risk Management
[3]  
[Anonymous], NRELCP5D0062817
[4]  
[Anonymous], 2008, Engineering Design Via Surrogate Modelling: A Practical Guide
[5]  
[Anonymous], REL STAND BULK EL SY
[6]  
[Anonymous], 2012, WATT SUN MULT MACH L
[7]  
[Anonymous], IEEE 118 BUS 54 UN 2
[8]   Review of photovoltaic power forecasting [J].
Antonanzas, J. ;
Osorio, N. ;
Escobar, R. ;
Urraca, R. ;
Martinez-de-Pison, F. J. ;
Antonanzas-Torres, F. .
SOLAR ENERGY, 2016, 136 :78-111
[9]   Short-term reforecasting of power output from a 48 MWe solar PV plant [J].
Chu, Yinghao ;
Urquhart, Bryan ;
Gohari, Seyyed M. I. ;
Pedro, Hugo T. C. ;
Kleissl, Jan ;
Coimbra, Carlos F. M. .
SOLAR ENERGY, 2015, 112 :68-77
[10]   Wind-Friendly Flexible Ramping Product Design in Multi-Timescale Power System Operations [J].
Cui, Mingjian ;
Zhang, Jie ;
Wu, Hongyu ;
Hodge, Bri-Mathias .
IEEE TRANSACTIONS ON SUSTAINABLE ENERGY, 2017, 8 (03) :1064-1075