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Title: NV energy electricity storage valuation :

Abstract

This study examines how grid-level electricity storage may benefit the operations of NV Energy, and assesses whether those benefits are likely to justify the cost of the storage system. To determine the impact of grid-level storage, an hourly production cost model of the Nevada Balancing Authority ("BA") as projected for 2020 was created. Storage was found to add value primarily through the provision of regulating reserve. Certain storage resources were found likely to be cost-effective even without considering their capacity value, as long as their effectiveness in providing regulating reserve was taken into account. Giving fast resources credit for their ability to provide regulating reserve is reasonable, given the adoption of FERC Order 755 ("Pay-for-performance"). Using a traditional five-minute test to determine how much a resource can contribute to regulating reserve does not adequately value fast-ramping resources, as the regulating reserve these resources can provide is constrained by their installed capacity. While an approximation was made to consider the additional value provided by a fast-ramping resource, a more precise valuation requires an alternate regulating reserve methodology. Developing and modeling a new regulating reserve methodology for NV Energy was beyond the scope of this study, as was assessing the incremental valuemore » of distributed storage.« less

Authors:
; ; ;
Publication Date:
Research Org.:
Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Pacific Northwest National Laboratory,, Richland, WA
Sponsoring Org.:
USDOE National Nuclear Security Administration (NNSA)
OSTI Identifier:
1089991
Report Number(s):
SAND2013-4902
456866
DOE Contract Number:  
AC04-94AL85000
Resource Type:
Technical Report
Country of Publication:
United States
Language:
English

Citation Formats

Ellison, James F., Bhatnagar, Dhruv, Samaan, Nader, and Jin, Chunlian. NV energy electricity storage valuation :. United States: N. p., 2013. Web. doi:10.2172/1089991.
Ellison, James F., Bhatnagar, Dhruv, Samaan, Nader, & Jin, Chunlian. NV energy electricity storage valuation :. United States. https://doi.org/10.2172/1089991
Ellison, James F., Bhatnagar, Dhruv, Samaan, Nader, and Jin, Chunlian. 2013. "NV energy electricity storage valuation :". United States. https://doi.org/10.2172/1089991. https://www.osti.gov/servlets/purl/1089991.
@article{osti_1089991,
title = {NV energy electricity storage valuation :},
author = {Ellison, James F. and Bhatnagar, Dhruv and Samaan, Nader and Jin, Chunlian},
abstractNote = {This study examines how grid-level electricity storage may benefit the operations of NV Energy, and assesses whether those benefits are likely to justify the cost of the storage system. To determine the impact of grid-level storage, an hourly production cost model of the Nevada Balancing Authority ("BA") as projected for 2020 was created. Storage was found to add value primarily through the provision of regulating reserve. Certain storage resources were found likely to be cost-effective even without considering their capacity value, as long as their effectiveness in providing regulating reserve was taken into account. Giving fast resources credit for their ability to provide regulating reserve is reasonable, given the adoption of FERC Order 755 ("Pay-for-performance"). Using a traditional five-minute test to determine how much a resource can contribute to regulating reserve does not adequately value fast-ramping resources, as the regulating reserve these resources can provide is constrained by their installed capacity. While an approximation was made to consider the additional value provided by a fast-ramping resource, a more precise valuation requires an alternate regulating reserve methodology. Developing and modeling a new regulating reserve methodology for NV Energy was beyond the scope of this study, as was assessing the incremental value of distributed storage.},
doi = {10.2172/1089991},
url = {https://www.osti.gov/biblio/1089991}, journal = {},
number = ,
volume = ,
place = {United States},
year = {Sat Jun 01 00:00:00 EDT 2013},
month = {Sat Jun 01 00:00:00 EDT 2013}
}