An empirical estimate of the electricity supply curve from market outcomes
从市场结果估计电力供给曲线AI 解读 ↓
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从市场结果估计电力供给曲线
- 研究问题
- 如何从观测电价与交易量估计电力供给曲线，并在能源危机造成供给条件快速变化时辨识相对稳定的供给状态？
- 方法与思路
- 作者分别按供给基本驱动因素与市场观测结果实施聚类，识别稳定供给时期，并应用于德国电力市场的价格数量数据。
- 材料陈述的贡献
- 摘要称，两种聚类识别出近乎相同的状态转换，燃料价格是主要驱动，并形成可用于反事实分析的经验供给曲线。
- 阅读关注点
- 应核对价格数量关系如何识别供给而非供需共同变化，以及聚类状态的经济含义、弹性估计和反事实分析依据。
- 阅读边界
- 这是 arXiv 预印本，同行评审或期刊接收均未核实；摘要未解释供需同时性处理，不能仅凭无额外建模假设认定因果识别。
原文摘要
Researchers and electricity sector practitioners frequently require the supply curve of electricity markets and the price elasticity of supply for purposes such as price forecasting, policy analyses or market power assessment. It is common practice to construct supply curves from engineering data such as installed capacity and fuel prices. In this study, we propose a data-driven methodology to estimate the supply curve of electricity market empirically, i.e. from observed prices and quantities without further modeling assumptions. Due to the massive swings in fuel prices during the European energy crisis, a central task is detecting periods of stable supply curves. To this end, we implement two alternative clustering methods, one based on the fundamental drivers of electricity supply and the other directly on observed market outcomes. We apply our methods to the German electricity market between 2019 and 2024. We find that both approaches identify almost identical regimes shifts, supporting the idea of stable supply regimes stemming from stable drivers. Supply conditions are often stable for extended periods, but evolved rapidly during the energy crisis, triggering a rapid succession of regimes. Fuel prices were the dominant drivers of regime shifts, while conventional plant availability and the nuclear phase-out play a comparatively minor role. Our approach produces empirical supply curves suitable for causal inference and counterfactual analysis of market outcomes.