Index for wind power variability

Juha Kiviluoma, Hannele Holttinen, richard Scharff, David Edward Weir, Nicolaos Cutululis, Marisciel Litong-Palima, Michael Milligan

    Research output: Chapter in Book/Report/Conference proceedingConference article in proceedingsScientific

    Abstract

    Variability of large scale wind power generation is dependent on several factors: characteristics of installed wind power plants, size of the area where the plants are installed, geographic dispersion within that area and its weather regime(s). Variability can be described by ramps in power generation, i.e. changes from time period to time period. Given enough data points, it can be described with a probability density function. This approach focuses on two dimensions of variability: duration of the ramp and probability distribution. This paper proposes an index based on these two dimensions to enable comparisons and characterizations of variability under different conditions. The index is tested with real, large scale wind power generation data from several countries. Considerations while forming an index are discussed, as well as the main results regarding what the drivers of variability experienced for different data.
    Original languageEnglish
    Title of host publication13th Wind Integration Workshop proceedings
    PublisherEnergynautics GmbH
    ISBN (Print)978-3-98 13870-9-4
    Publication statusPublished - 2014
    MoE publication typeB3 Non-refereed article in conference proceedings
    Event13th International Workshop on Large-Scale Integration of Wind Power into Power Systems as well as on Transmission Networks for Offshore Wind Farms, WIW 2014 - Berlin, Germany
    Duration: 11 Nov 201413 Nov 2014

    Conference

    Conference13th International Workshop on Large-Scale Integration of Wind Power into Power Systems as well as on Transmission Networks for Offshore Wind Farms, WIW 2014
    Abbreviated titleWIW 2014
    CountryGermany
    CityBerlin
    Period11/11/1413/11/14

    Fingerprint

    wind power
    power generation
    probability density function
    power plant
    weather
    index

    Keywords

    • wind power integration
    • variations
    • indices for variability
    • variable renewable energy sources

    Cite this

    Kiviluoma, J., Holttinen, H., Scharff, R., Weir, D. E., Cutululis, N., Litong-Palima, M., & Milligan, M. (2014). Index for wind power variability. In 13th Wind Integration Workshop proceedings Energynautics GmbH.
    Kiviluoma, Juha ; Holttinen, Hannele ; Scharff, richard ; Weir, David Edward ; Cutululis, Nicolaos ; Litong-Palima, Marisciel ; Milligan, Michael. / Index for wind power variability. 13th Wind Integration Workshop proceedings. Energynautics GmbH, 2014.
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    title = "Index for wind power variability",
    abstract = "Variability of large scale wind power generation is dependent on several factors: characteristics of installed wind power plants, size of the area where the plants are installed, geographic dispersion within that area and its weather regime(s). Variability can be described by ramps in power generation, i.e. changes from time period to time period. Given enough data points, it can be described with a probability density function. This approach focuses on two dimensions of variability: duration of the ramp and probability distribution. This paper proposes an index based on these two dimensions to enable comparisons and characterizations of variability under different conditions. The index is tested with real, large scale wind power generation data from several countries. Considerations while forming an index are discussed, as well as the main results regarding what the drivers of variability experienced for different data.",
    keywords = "wind power integration, variations, indices for variability, variable renewable energy sources",
    author = "Juha Kiviluoma and Hannele Holttinen and richard Scharff and Weir, {David Edward} and Nicolaos Cutululis and Marisciel Litong-Palima and Michael Milligan",
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    Kiviluoma, J, Holttinen, H, Scharff, R, Weir, DE, Cutululis, N, Litong-Palima, M & Milligan, M 2014, Index for wind power variability. in 13th Wind Integration Workshop proceedings. Energynautics GmbH, 13th International Workshop on Large-Scale Integration of Wind Power into Power Systems as well as on Transmission Networks for Offshore Wind Farms, WIW 2014, Berlin, Germany, 11/11/14.

    Index for wind power variability. / Kiviluoma, Juha; Holttinen, Hannele; Scharff, richard; Weir, David Edward; Cutululis, Nicolaos; Litong-Palima, Marisciel; Milligan, Michael.

    13th Wind Integration Workshop proceedings. Energynautics GmbH, 2014.

    Research output: Chapter in Book/Report/Conference proceedingConference article in proceedingsScientific

    TY - GEN

    T1 - Index for wind power variability

    AU - Kiviluoma, Juha

    AU - Holttinen, Hannele

    AU - Scharff, richard

    AU - Weir, David Edward

    AU - Cutululis, Nicolaos

    AU - Litong-Palima, Marisciel

    AU - Milligan, Michael

    N1 - Project code: 104775

    PY - 2014

    Y1 - 2014

    N2 - Variability of large scale wind power generation is dependent on several factors: characteristics of installed wind power plants, size of the area where the plants are installed, geographic dispersion within that area and its weather regime(s). Variability can be described by ramps in power generation, i.e. changes from time period to time period. Given enough data points, it can be described with a probability density function. This approach focuses on two dimensions of variability: duration of the ramp and probability distribution. This paper proposes an index based on these two dimensions to enable comparisons and characterizations of variability under different conditions. The index is tested with real, large scale wind power generation data from several countries. Considerations while forming an index are discussed, as well as the main results regarding what the drivers of variability experienced for different data.

    AB - Variability of large scale wind power generation is dependent on several factors: characteristics of installed wind power plants, size of the area where the plants are installed, geographic dispersion within that area and its weather regime(s). Variability can be described by ramps in power generation, i.e. changes from time period to time period. Given enough data points, it can be described with a probability density function. This approach focuses on two dimensions of variability: duration of the ramp and probability distribution. This paper proposes an index based on these two dimensions to enable comparisons and characterizations of variability under different conditions. The index is tested with real, large scale wind power generation data from several countries. Considerations while forming an index are discussed, as well as the main results regarding what the drivers of variability experienced for different data.

    KW - wind power integration

    KW - variations

    KW - indices for variability

    KW - variable renewable energy sources

    M3 - Conference article in proceedings

    SN - 978-3-98 13870-9-4

    BT - 13th Wind Integration Workshop proceedings

    PB - Energynautics GmbH

    ER -

    Kiviluoma J, Holttinen H, Scharff R, Weir DE, Cutululis N, Litong-Palima M et al. Index for wind power variability. In 13th Wind Integration Workshop proceedings. Energynautics GmbH. 2014