Variability (and extremes) in streamflow, wind speeds, temperatures, and solar irradiance influence supply and demand for electricity. However, previous research falls short in addressing the risks that joint uncertainties in these processes pose in power systems and wholesale electricity markets. Limiting challenges have included the large areal extents of power systems, high temporal resolutions (hourly or sub-hourly), and the data volumes and computational intensities required. This paper introduces an open source modeling framework for evaluating risks from correlated hydrometeorological processes in electricity markets at decision relevant scales. The framework is able to reproduce historical price dynamics in high profile systems, while also offering unique capabilities for stochastic simulation. Synthetic generation of weather and hydrologic variables is coupled with simulation models of relevant infrastructure (dams, power plants). Our model will allow the role of hydrometeorological uncertainty (including compound extreme events) on electricity market outcomes to be explored using publicly available models.

流量，风速，温度和太阳辐照度的可变性（和极端性）会影响电力的供求。但是，先前的研究未能解决这些过程中共同不确定性在电力系统和电力批发市场中带来的风险。有限的挑战包括电力系统的大范围范围，较高的时间分辨率（每小时或每小时）以及所需的数据量和计算强度。本文介绍了一个开放源代码建模框架，用于以决策相关规模评估电力市场中相关水文气象过程的风险。该框架能够在高端系统中重现历史价格动态，同时还为随机模拟提供独特的功能。天气和水文变量的综合生成与相关基础设施（水坝，发电厂）的仿真模型结合在一起。我们的模型将允许使用公开可用的模型来探索水文气象不确定性（包括复合极端事件）在电力市场结果中的作用。