The Evolution of Probabilistic Price Forecasting Techniques: A Review of the Day-Ahead, Intra-Day, and Balancing Markets
Ciaran O'Connor, Mohamed Bahloul, Steven Prestwich, Andrea Visentin
电价预测已成为能源市场决策的关键工具,特别是随着可再生能源渗透率的增加带来更大的波动性和不确定性。 从历史上看,该领域的研究一直以点预测方法为主,该方法提供单值预测,但未能量化不确定性。 然而,随着电力市场的发展,由于可再生能源集成,智能电网和监管变化,对概率预测的需求变得更加明显,为风险评估和市场参与提供了更全面的方法。 本文介绍了概率预测方法的回顾,通过分位数回归技术,从贝叶斯和基于分布的方法,追踪到构象预测的最新发展。 特别强调概率预测的进步,包括以有效性为重点的方法,解决不确定性估计的关键限制。 此外,该审查超越了“未来日”市场,包括日内和平衡市场,其中预测挑战因更高的时间粒度和实时操作限制而加剧。 我们研究最先进的方法,关键评估指标和持续挑战,如预测有效性,模型选择和缺乏标准化基准,为研究人员和从业者提供全面和及时的资源,以驾驭现代电力市场的复杂性。
Electricity price forecasting has become a critical tool for decision-making in energy markets, particularly as the increasing penetration of renewable energy introduces greater volatility and uncertainty. Historically, research in this field has been dominated by point forecasting methods, which provide single-value predictions but fail to quantify uncertainty. However, as power markets evolve due to renewable integration, smart grids, and regulatory changes, the need for probabilistic forecast...
