Synthetic wind speed scenarios generation for probabilistic analysis of hybrid energy systems

Chen, Jun; Rabiti, Cristian

doi:10.1016/j.energy.2016.11.103

Title: Synthetic wind speed scenarios generation for probabilistic analysis of hybrid energy systems

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Abstract

Hybrid energy systems consisting of multiple energy inputs and multiple energy outputs have been proposed to be an effective element to enable ever increasing penetration of clean energy. In order to better understand the dynamic and probabilistic behavior of hybrid energy systems, this paper proposes a model combining Fourier series and autoregressive moving average (ARMA) to characterize historical weather measurements and to generate synthetic weather (e.g., wind speed) data. In particular, Fourier series is used to characterize the seasonal trend in historical data, while ARMA is applied to capture the autocorrelation in residue time series (e.g., measurements minus seasonal trends). The generated synthetic wind speed data is then utilized to perform probabilistic analysis of a particular hybrid energy system con guration, which consists of nuclear power plant, wind farm, battery storage, natural gas boiler, and chemical plant. As a result, requirements on component ramping rate, economic and environmental impacts of hybrid energy systems, and the effects of deploying different sizes of batteries in smoothing renewable variability, are all investigated.

Authors:

^[1]; Rabiti, Cristian ^[1]

Idaho National Lab. (INL), Idaho Falls, ID (United States)

Publication Date:: Fri Nov 25 00:00:00 EST 2016

Research Org.:: Idaho National Lab. (INL), Idaho Falls, ID (United States)

Sponsoring Org.:: USDOE Office of Nuclear Energy (NE)

OSTI Identifier:: 1361550

Alternate Identifier(s):: OSTI ID: 1397060

Report Number(s):: INL/JOU-16-39654
Journal ID: ISSN 0360-5442; PII: S036054421631742X

Grant/Contract Number:: AC07-05ID14517

Resource Type:: Accepted Manuscript

Journal Name:: Energy (Oxford)

Additional Journal Information:: Journal Name: Energy (Oxford); Journal Volume: 120; Journal Issue: C; Journal ID: ISSN 0360-5442

Publisher:: Elsevier

Country of Publication:: United States

Language:: English

Subject:: 97 MATHEMATICS AND COMPUTING; 99 GENERAL AND MISCELLANEOUS; 17 WIND ENERGY; autoregressive moving average; hybrid energy systems; renewable energy integration; synthetic data generation

Citation Formats


                    Chen, Jun, and Rabiti, Cristian. Synthetic wind speed scenarios generation for probabilistic analysis of hybrid energy systems.  United States: N. p., 2016. 
Web.  doi:10.1016/j.energy.2016.11.103.

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                    Chen, Jun, & Rabiti, Cristian. Synthetic wind speed scenarios generation for probabilistic analysis of hybrid energy systems.  United States.  https://doi.org/10.1016/j.energy.2016.11.103

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                    Chen, Jun, and Rabiti, Cristian. Fri .  
"Synthetic wind speed scenarios generation for probabilistic analysis of hybrid energy systems".  United States.  https://doi.org/10.1016/j.energy.2016.11.103.  https://www.osti.gov/servlets/purl/1361550.

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@article{osti_1361550,

  title        = {Synthetic wind speed scenarios generation for probabilistic analysis of hybrid energy systems},

  author       = {Chen, Jun and Rabiti, Cristian},

  abstractNote = {Hybrid energy systems consisting of multiple energy inputs and multiple energy outputs have been proposed to be an effective element to enable ever increasing penetration of clean energy. In order to better understand the dynamic and probabilistic behavior of hybrid energy systems, this paper proposes a model combining Fourier series and autoregressive moving average (ARMA) to characterize historical weather measurements and to generate synthetic weather (e.g., wind speed) data. In particular, Fourier series is used to characterize the seasonal trend in historical data, while ARMA is applied to capture the autocorrelation in residue time series (e.g., measurements minus seasonal trends). The generated synthetic wind speed data is then utilized to perform probabilistic analysis of a particular hybrid energy system con guration, which consists of nuclear power plant, wind farm, battery storage, natural gas boiler, and chemical plant. As a result, requirements on component ramping rate, economic and environmental impacts of hybrid energy systems, and the effects of deploying different sizes of batteries in smoothing renewable variability, are all investigated.},

  doi          = {10.1016/j.energy.2016.11.103},

  journal      = {Energy (Oxford)},

  number       = C,

  volume       = 120,

  place        = {United States},

  year         = {Fri Nov 25 00:00:00 EST 2016},

  month        = {Fri Nov 25 00:00:00 EST 2016}

}

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