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

Abstract

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 state-of-the-art independent reliability metrics. The absolute value and standard deviation of area control errors (ACE), and the North American Electric Reliability Corporation Control Performance Standard 2 (CPS2) score are calculated through the multi-timescale scheduling simulation, including the day-ahead unit commitment (DU), real-time unit commitment (RU), real-time economic dispatch (RE), automatic generation control (AGC) sub-models. The absolute area control error in energy (AACEE), 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.

Authors:
ORCiD logo; ORCiD logo; ; ;
Publication Date:
Research Org.:
National Renewable Energy Lab. (NREL), Golden, CO (United States)
Sponsoring Org.:
USDOE Office of Energy Efficiency and Renewable Energy (EERE), Solar Energy Technologies Office (EE-4S)
OSTI Identifier:
1479264
Report Number(s):
NREL/JA-5D00-70184
Journal ID: ISSN 1949-3053
DOE Contract Number:  
AC36-08GO28308
Resource Type:
Journal Article
Journal Name:
IEEE Transactions on Smart Grid
Additional Journal Information:
Journal Volume: 9; Journal Issue: 6; Journal ID: ISSN 1949-3053
Publisher:
IEEE
Country of Publication:
United States
Language:
English
Subject:
24 POWER TRANSMISSION AND DISTRIBUTION; area control error; multi-timescale power system operation; photovoltaic; reliability benefit; forecast

Citation Formats

Cui, Mingjian, Zhang, Jie, Hodge, Bri-Mathias, Lu, Siyuan, and Hamann, Hendrik F. A Methodology for Quantifying Reliability Benefits From Improved Solar Power Forecasting in Multi-Timescale Power System Operations. United States: N. p., 2018. Web. doi:10.1109/TSG.2017.2728480.
Cui, Mingjian, Zhang, Jie, Hodge, Bri-Mathias, Lu, Siyuan, & Hamann, Hendrik F. A Methodology for Quantifying Reliability Benefits From Improved Solar Power Forecasting in Multi-Timescale Power System Operations. United States. doi:10.1109/TSG.2017.2728480.
Cui, Mingjian, Zhang, Jie, Hodge, Bri-Mathias, Lu, Siyuan, and Hamann, Hendrik F. Thu . "A Methodology for Quantifying Reliability Benefits From Improved Solar Power Forecasting in Multi-Timescale Power System Operations". United States. doi:10.1109/TSG.2017.2728480.
@article{osti_1479264,
title = {A Methodology for Quantifying Reliability Benefits From Improved Solar Power Forecasting in Multi-Timescale Power System Operations},
author = {Cui, Mingjian and Zhang, Jie and Hodge, Bri-Mathias and Lu, Siyuan and Hamann, Hendrik F.},
abstractNote = {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 state-of-the-art independent reliability metrics. The absolute value and standard deviation of area control errors (ACE), and the North American Electric Reliability Corporation Control Performance Standard 2 (CPS2) score are calculated through the multi-timescale scheduling simulation, including the day-ahead unit commitment (DU), real-time unit commitment (RU), real-time economic dispatch (RE), automatic generation control (AGC) sub-models. The absolute area control error in energy (AACEE), 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.},
doi = {10.1109/TSG.2017.2728480},
journal = {IEEE Transactions on Smart Grid},
issn = {1949-3053},
number = 6,
volume = 9,
place = {United States},
year = {2018},
month = {11}
}