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    Temperatura energética do sector agrícola
    (INESC TEC, 2026-05-28) Faria, A. Sérgio ; Cruz, Fábio ; Andrade, Isabelle ; Villar, José ; Costa Gomes, José ; Silveira, João ; Quadros e Costa, António ; Brás, Paula ; Costa Santos, Marta
    No âmbito do projeto Tools4AgriEnergy, o INESC TEC, INIAV, COTR e FENAREG, com o apoio da EDIA, realizaram um estudo para analisar a relação do sector agrícola em Portugal com a energia e as comunidades de energia, com o objetivo de identificar oportunidades e propor caminhos para um maior desenvolvimento de soluções energéticas eficientes incluídos autoconsumos individuais e coletivos.
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    Demand Dispatch and Probabilistic Wind Power Forecasting in Unit Commitment and Economic Dispatch: A Case Study of Illinois
    ( 2013) Botterud,A ; Zhou,Z ; Wang,JH ; Jean Sumaili ; Keko,H ; Mendes,J ; Ricardo Jorge Bessa ; Vladimiro Miranda
    In this paper, we analyze how demand dispatch combined with the use of probabilistic wind power forecasting can help accommodate large shares of wind power in electricity market operations. We model the operation of day-ahead and real-time electricity markets, which the system operator clears by centralized unit commitment and economic dispatch. We use probabilistic wind power forecasting to estimate dynamic operating reserve requirements, based on the level of uncertainty in the forecast. At the same time, we represent price responsive demand as a dispatchable resource, which adds flexibility in the system operation. In a case study of the power system in Illinois, we find that both demand dispatch and probabilistic wind power forecasting can contribute to efficient operation of electricity markets with large shares of wind power.
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    Application of probabilistic wind power forecasting in electricity markets
    ( 2013) Zhou,Z ; Botterud,A ; Wang,J ; Ricardo Jorge Bessa ; Keko,H ; Jean Sumaili ; Vladimiro Miranda
    This paper discusses the potential use of probabilistic wind power forecasting in electricity markets, with focus on the scheduling and dispatch decisions of the system operator. We apply probabilistic kernel density forecasting with a quantile-copula estimator to forecast the probability density function, from which forecasting quantiles and scenarios with temporal dependency of errors are derived. We show how the probabilistic forecasts can be used to schedule energy and operating reserves to accommodate the wind power forecast uncertainty. We simulate the operation of a two-settlement electricity market with clearing of day-ahead and real-time markets for energy and operating reserves. At the day-ahead stage, a deterministic point forecast is input to the commitment and dispatch procedure. Then a probabilistic forecast is used to adjust the commitment status of fast-starting units closer to real time, on the basis of either dynamic operating reserves or stochastic unit commitment. Finally, the real-time dispatch is based on the realized availability of wind power. To evaluate the model in a large-scale real-world setting, we take the power system in Illinois as a test case and compare different scheduling strategies. The results show better performance for dynamic compared with fixed operating reserve requirements. Furthermore, although there are differences in the detailed dispatch results, dynamic operating reserves and stochastic unit commitment give similar results in terms of cost. Overall, we find that probabilistic forecasts can contribute to improve the performance of the power system, both in terms of cost and reliability. Copyright (c) 2012 John Wiley & Sons, Ltd.
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    Reliability Assessment Unit Commitment with Uncertain Wind Power
    ( 2013) Wang,J ; Valenzuela,J ; Botterud,A ; Keko,H ; Ricardo Jorge Bessa ; Vladimiro Miranda
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    Methodologies to determine operating reserves due to increased wind power
    ( 2013) Holttinen,H ; Milligan,M ; Ela,E ; Menemenlis,N ; Dobschinski,J ; Rawn,B ; Ricardo Jorge Bessa ; Flynn,D ; Gomez Lazaro,E ; Detlefsen,N
    Power systems with high wind penetration experience increased variability and uncertainty, such that determination of the required additional operating reserve is attracting a significant amount of attention and research. This paper presents methods used in recent wind integration analyses and operating practice, with key results that compare different methods or data. Wind integration analysis over the past several years has shown that wind variability need not be seen as a contingency event. The impact of wind will be seen in the reserves for non-event operation (normal operation dealing with deviations from schedules). Wind power will also result in some events of larger variability and large forecast errors that could be categorized as slow events. The level of operating reserve that is induced by wind is not constant during all hours of the year, so that dynamic allocation of reserves will reduce the amount of reserves needed in the system for most hours. The paper concludes with recent emerging trends. © 2013 IEEE.