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Stochastic risk-sensitive market integration for renewable energy: Application to ocean wave power plants

Journal Article · · Applied Energy
 [1];  [2];  [2];  [2]
  1. National Renewable Energy Lab. (NREL), Golden, CO (United States)
  2. Lehigh Univ., Bethlehem, PA (United States)
With the expected increase of intermittent renewable energy resources on the electric power grid, short-term reserve markets can prove to be a critical reliability asset. This paper introduces and tests a potential market structure that includes a short-term reserve market for renewable resources where the realized energy is drawn within the bounds of the hourly capacity offered. The study presents a risk-aware stochastic model that determines, based on the day-ahead offer derived using a classic newsvendor formula, the best intraday offers for a renewable energy power plant. The stochastic approach takes into account the uncertainties of energy production and market prices. The proposed risk-sensitive model aims to maximize the renewable power plant's revenues and minimize potential risks of loss in a multi-product multi-timescale market setup. To demonstrate the effectiveness of the proposed formulation, we study the case of a hypothetical 750-kW wave power plant coupled with energy storage. The study shows that the risk of profit loss is not uniformly distributed across the risk-aversion factor space. We also find that the introduction of the short-term reserve market results in a wider range of conditional value at risk while inducing 5% profit increase and a lower profit reduction across the risk range. In addition, the study reveals that the short-term reserve market is profitable for both the system operator and the wave energy power plant considered.
Research Organization:
National Renewable Energy Lab. (NREL), Golden, CO (United States)
Sponsoring Organization:
National Science Foundation (NSF)
Grant/Contract Number:
AC36-08GO28308
OSTI ID:
1471479
Alternate ID(s):
OSTI ID: 1703570
Report Number(s):
NREL/JA--5D00-71360
Journal Information:
Applied Energy, Journal Name: Applied Energy Journal Issue: C Vol. 229; ISSN 0306-2619
Publisher:
ElsevierCopyright Statement
Country of Publication:
United States
Language:
English

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Integrated shale gas supply chain design and water management under uncertainty journal December 2018

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