Quantifying the Economic and Grid Reliability Impacts of Improved Wind Power Forecasting

Qin Wang, Carlo Brancucci Martinez-Anido, Hongyu Wu, Anthony R. Florita, Bri Mathias Hodge

Research output: Contribution to journalArticlepeer-review

82 Scopus Citations

Abstract

Wind power forecasting is an important tool in power system operations to address variability and uncertainty. Accurately doing so is important to reduce the occurrence and length of curtailment, enhancing market efficiency, and improving the operational reliability of the bulk power system. This research quantifies the value of wind power forecasting improvements in the IEEE 118-bus test system as modified to emulate the generation mixes of Midcontinent, California, and New England independent system operator balancing authority areas. To measure the economic value, a commercially available production cost modeling tool was used to simulate the multitimescale unit commitment (UC) and economic dispatch process for calculating the cost savings and curtailment reductions. To measure the reliability improvements, an in-house tool, Flexible energy scheduling tool for integrating variable generation, was used to calculate the system's area control error and the North American Electric Reliability Corporation Control Performance Standard 2. The approach allowed scientific reproducibility of results and cross validation of the tools. A total of 270 scenarios were evaluated to accommodate the variation of three factors: generation mix, wind penetration level, and wind forecasting improvements. The modified IEEE 118-bus systems utilized 1 year of data at multiple time scales, including the day-ahead UC, 4-h-ahead UC, and real-time dispatch. The value of improved wind power forecasting was found to be strongly tied to the conventional generation mix, existence of energy storage devices, and the penetration level of wind energy. The simulation results demonstrate that wind power forecasting brings clear benefits to power system operations.

Original languageAmerican English
Article number7469774
Pages (from-to)1525-1537
Number of pages13
JournalIEEE Transactions on Sustainable Energy
Volume7
Issue number4
DOIs
StatePublished - Oct 2016

Bibliographical note

Publisher Copyright:
© 2016 IEEE.

NREL Publication Number

  • NREL/JA-5D00-65220

Keywords

  • Area control error (ACE)
  • economic dispatch
  • economic impacts
  • market operations
  • reliability
  • unit commitment
  • wind forecasting

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