L. Michi, E. Carlini, M. Bonanni, P. Capurso, F. Quaglia, L. Nuccio, S. Biondi, B. Cova, D. Canever, L. Giorgi
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引用次数: 0
Abstract
In according to the Regulation (EC) No 714/2009 ENTSO-E and the TSO Community strive for a secure, resilient, flexible, adequate and well interconnected pan-European power system, and they are acting unanimously to develop the most suitable responses to the challenges of the energy transition and digital transformation. The publishing of Summer and Winter Outlook, twice per year, and of the annual Mid-term Adequacy Forecast (MAF) report provides a comprehensive information to the Member States in terms of hourly probabilistic assessment of reliability standards, e.g. Loss Of Load Expectations (LOLE), Expected Energy Not Supplied (EENS). With a time horizon between mid-term resource adequacy assessments (1 to 10 years ahead) and short term resource adequacy assessments (week ahead to intraday), the seasonal outlook aims to bridge them. Since the degree of uncertainty decreases in the shorter time horizons, seasonal outlooks can improve the quality of adequacy assessment for the upcoming months compared to yearly assessments. However seasonal outlook degree of uncertainty is quite high, as for instance temperatures, wind and PV cannot be precisely forecasted in this time horizon. Hence, a probabilistic methodology is needed in order to improve seasonal outlook reliability, starting from general approaches already applied for mid-term adequacy assessments. This paper highlights potentiality and challenges of adopting a probabilistic approach in the seasonal outlook process, especially focusing on the use case of Italy.
根据法规(EC) No 714/2009, ENTSO-E和TSO共同体致力于建立一个安全、有弹性、灵活、充足和良好互联的泛欧电力系统,他们一致采取行动,制定最合适的应对能源转型和数字化转型挑战的措施。每年出版两次的夏季和冬季展望,以及年度中期充足性预测(MAF)报告,为成员国提供了关于可靠性标准的每小时概率评估的全面信息,例如负荷预期损失(LOLE),预期未供应能源(EENS)。在中期资源充足性评估(未来1至10年)和短期资源充足性评估(未来一周至今日)之间有一个时间跨度,季节性展望旨在弥合两者之间的差距。由于不确定的程度在较短的时间范围内减少,与年度评估相比,季节性展望可以提高未来几个月的充分性评估的质量。然而,季节性前景的不确定性程度相当高,例如温度,风和PV无法在这个时间范围内精确预测。因此,为了提高季节性前景的可靠性,需要一种概率方法,从已经应用于中期充分性评估的一般方法开始。本文强调了在季节展望过程中采用概率方法的潜力和挑战,特别是关注意大利的用例。