The DOI matches its Crossref record; 15 of the 15 references it cites were found in a registry or an index.
Evaluating the Impacts of Real-Time Pricing on the Cost and Value of Wind Generation
Open accessAbstract
One of the costs associated with integrating wind generation into a power system is the cost of redispatching the system in real-time due to day-ahead wind resource forecast errors. One possible way of reducing these redispatch costs is to introduce demand response in the form of real-time pricing (RTP), which could allow electricity demand to respond to actual real-time wind resource availability using price signals. A day-ahead unit commitment model with day-ahead wind forecasts and a real-time dispatch model with actual wind resource availability is used to estimate system operations in a high wind penetration scenario. System operations are compared to a perfect foresight benchmark, in which actual wind resource availability is known day-ahead. The results show that wind integration costs with fixed demands can be high, both due to real-time redispatch costs and lost load. It is demonstrated that introducing RTP can reduce redispatch costs and eliminate loss of load events. Finally, social surplus with wind generation and RTP is compared to a system with neither and the results demonstrate that introducing wind and RTP into a market can result in superadditive surplus gains.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
The check wasn’t confident either way, so it gives no verdict — never disputed.
In the citing paper
“In this way, the magnitude of the wholesale and the retail prices can be reduced while the price spikes and the volatility of the spot market can be mitigated [110].”
From An overview of Demand Response: Key-elements and international experience (2017) · cites this paper as [110]
Experimental — accuracy not yet measured
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
A New Approach to Quantify Reserve Demand in Systems With Significant Installed Wind Capacity
Doherty, R., & O'Malley, M. J. (2005) · IEEE Transactions on Power Systems · doi:10.1109/tpwrs.2005.846206 · Cited by 755
Stochastic Security for Operations Planning With Significant Wind Power Generation
Bouffard, F., & Galiana, F. D. (2008) · IEEE Transactions on Power Systems · doi:10.1109/tpwrs.2008.919318 · Cited by 720
Unit Commitment for Systems With Significant Wind Penetration
Tuohy, A., Meibom, P., Denny, E., et al. (2009) · IEEE Transactions on Power Systems · doi:10.1109/tpwrs.2009.2016470 · Cited by 709
The Trouble With Electricity Markets: Understanding California's Restructuring Disaster
Borenstein, S. (2002) · The Journal of Economic Perspectives · doi:10.1257/0895330027175 · Cited by 563
Utility Wind Integration and Operating Impact State of the Art
Smith, J. C., Milligan, M. R., DeMeo, E. A., & Parsons, B. (2007) · IEEE Transactions on Power Systems · doi:10.1109/tpwrs.2007.901598 · Cited by 466
Fabbri, A., Román, T. G. S., RivierAbbad, J., et al. (2005) · IEEE Transactions on Power Systems · doi:10.1109/tpwrs.2005.852148 · Cited by 459
The Long-Run Efficiency of Real-Time Electricity Pricing
Borenstein, S. (2005) · The Energy Journal · doi:10.5547/issn0195-6574-ej-vol26-no3-5 · Cited by 442
On the Efficiency of Competitive Electricity Markets With Time-Invariant Retail Prices
Holland, S. P., & NC DOCKS at The University of North Carolina at Greensboro (2005) · NC Digital Online Collection of Knowledge and Scholarship (The University of North Carolina at Greensboro) · Cited by 305
Evaluating the Impacts of Real-Time Pricing on the Usage of Wind Generation
Sioshansi, R., & Short, W. (2009) · IEEE Transactions on Power Systems · doi:10.1109/tpwrs.2008.2012184 · Cited by 216
Self-citationWind plant integration [wind power plants
DeMeo, E. A., Grant, W., Milligan, M., et al. (2005) · IEEE Power and Energy Magazine · doi:10.1109/mpae.2005.1524619 · Cited by 174
Research works printed but not linked: 4
- borenstein, 1997, A Cournot-Nash Equilibrium Analysis of the New Jersey Electricity Market
- king, 2003, predicting california demand response, Public Utility Fortnightly, 27
- 2007, Integration of Renewable Resources
- felder, 2007, Quantifying Demand Response Benefits in PJM
Cited by
Sorted by citations
Benefits and challenges of electrical demand response: a critical review
O׳Connell, N., Pinson, P., Madsen, H., & O׳Malley, M. (2014) · Renewable and Sustainable Energy Reviews · doi:10.1016/j.rser.2014.07.098 · Cited by 636
An overview of Demand Response: Key-elements and international experience
Paterakis, N. G., Erdinç, O., & Catalão, J. P. S. (2017) · Renewable and Sustainable Energy Reviews · doi:10.1016/j.rser.2016.11.167 · Cited by 640
Benefits of Demand Response on Operation of Distribution Networks: A Case Study
Safdarian, A., Fotuhi-Firuzabad, M., & Lehtonen, M. (2016) · IEEE Systems Journal · doi:10.1109/jsyst.2013.2297792 · Cited by 162
Metadata
- Authors
- Sioshansi, R.
- Affiliations
- National Laboratory of the Rockies (US)
- Corresponding author
- Sioshansi, Ramteen
- ORCID
- Sioshansi, Ramteen
- Venue
- IEEE Transactions on Power Systems
- Published
- 2010-05
- Volume
- 25
- Issue
- 2
- Pages
- 741-748
- ISSN
- 0885-8950 (ISSN-L)
- 1558-0679
- OpenAlex
- W2126540864
- Cited by
- 152
- References
- 15
- Citations by year
- 2026: 2 · 2025: 2 · 2024: 2 · 2023: 4 · 2022: 8 · 2021: 3 · 2020: 3 · 2019: 10 · 2018: 6 · 2017: 15 · 2016: 9 · 2015: 15 · 2014: 20 · 2013: 17 · 2012: 16
- FWCI
- 9.52
- Type
- journal article
- Language
- en
- Open access
- green
- www.osti.gov
- Locations
- IEEE Transactions on Power Systems (publishedVersion)
- OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information) (submittedVersion)
- Funders
- Ohio State University
- Topics
- Physical Sciences › Engineering › Electrical and Electronic Engineering › Electric Power System Optimization
- Physical Sciences › Engineering › Electrical and Electronic Engineering › Smart Grid Energy Management
- Physical Sciences › Engineering › Electrical and Electronic Engineering › Integrated Energy Systems Optimization
- Keywords
- real-time pricing, wind power integration, demand response, wind forecast errors, day-ahead unit commitment, real-time dispatch, social surplus, high wind penetration, electricity market
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
