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    Impact of Forecast Uncertainty on Wind Farm Profitability

    Source: Journal of Engineering for Gas Turbines and Power:;2020:;volume( 142 ):;issue: 004
    Author:
    Frate, Guido Francesco
    ,
    Ferrari, Lorenzo
    ,
    Desideri, Umberto
    DOI: 10.1115/1.4045085
    Publisher: The American Society of Mechanical Engineers (ASME)
    Abstract: The great amount of support schemes that initially fueled the fast and often uncontrollable, renewable energy sources (RESs) growth have been strongly reduced or revoked in many countries. Currently, the general trend is to try to equate RESs to traditional power plants. From the energy market point of view, this entails exposing RESs to market competition and mechanics. For example, it could be requested that RESs submit a production schedule in advance and are financially responsible for any deviation from it. This could push the wind farm (WF) operators to make accurate forecasts, thus fostering the electric system resiliency and an efficient use of balancing resources. From the forecasting point of view, this is not a trivial problem since the schedule submission is often due 10–12 h before the actual delivery. Since forecast errors are unavoidable, the submitted schedule could turn out to be infeasible, thus forcing the WF to adopt correcting actions, which are generally costly. This study estimates the revenue reduction that would affect a WF operating in the energy market due to forecast errors. To do this in a realistic way, a case study is selected, and realistic forecast scenarios are generated by using a copula approach. Relevant forecast error features, like autocorrelation and dependency on forecasted power level and forecast lead time, are modeled. The revenue reduction due to balancing actions is calculated on an annual basis, by using typical days. These were derived through a clustering procedure based on production data. Losses ranging from 5% to 35% have been found, depending on the days and market prices. A sensitivity analysis to the costs of balancing actions is performed. The effect of different market architectures and different RESs penetration level is considered in the analysis. Finally, the effectiveness of two techniques (i.e., curtailment and batteries) to reduce forecast error impact in highly penalizing market environments is assessed.
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      Impact of Forecast Uncertainty on Wind Farm Profitability

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    contributor authorFrate, Guido Francesco
    contributor authorFerrari, Lorenzo
    contributor authorDesideri, Umberto
    date accessioned2022-02-04T14:41:11Z
    date available2022-02-04T14:41:11Z
    date copyright2020/02/04/
    date issued2020
    identifier issn0742-4795
    identifier othergtp_142_04_041018.pdf
    identifier urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4274166
    description abstractThe great amount of support schemes that initially fueled the fast and often uncontrollable, renewable energy sources (RESs) growth have been strongly reduced or revoked in many countries. Currently, the general trend is to try to equate RESs to traditional power plants. From the energy market point of view, this entails exposing RESs to market competition and mechanics. For example, it could be requested that RESs submit a production schedule in advance and are financially responsible for any deviation from it. This could push the wind farm (WF) operators to make accurate forecasts, thus fostering the electric system resiliency and an efficient use of balancing resources. From the forecasting point of view, this is not a trivial problem since the schedule submission is often due 10–12 h before the actual delivery. Since forecast errors are unavoidable, the submitted schedule could turn out to be infeasible, thus forcing the WF to adopt correcting actions, which are generally costly. This study estimates the revenue reduction that would affect a WF operating in the energy market due to forecast errors. To do this in a realistic way, a case study is selected, and realistic forecast scenarios are generated by using a copula approach. Relevant forecast error features, like autocorrelation and dependency on forecasted power level and forecast lead time, are modeled. The revenue reduction due to balancing actions is calculated on an annual basis, by using typical days. These were derived through a clustering procedure based on production data. Losses ranging from 5% to 35% have been found, depending on the days and market prices. A sensitivity analysis to the costs of balancing actions is performed. The effect of different market architectures and different RESs penetration level is considered in the analysis. Finally, the effectiveness of two techniques (i.e., curtailment and batteries) to reduce forecast error impact in highly penalizing market environments is assessed.
    publisherThe American Society of Mechanical Engineers (ASME)
    titleImpact of Forecast Uncertainty on Wind Farm Profitability
    typeJournal Paper
    journal volume142
    journal issue4
    journal titleJournal of Engineering for Gas Turbines and Power
    identifier doi10.1115/1.4045085
    page41018
    treeJournal of Engineering for Gas Turbines and Power:;2020:;volume( 142 ):;issue: 004
    contenttypeFulltext
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