Data-Driven Sizing of Co-Located Storage for Uncertain Renewable Energy

Tomas Valencia Zuluaga;Shmuel S. Oren
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Abstract

We propose a high-level stochastic steady-state model to analyze the value of co-located energy storage systems for wind power producers that participate in an electricity market through forward contracts and use storage to unlock access to capacity payments. In particular, we try to find optimal storage and contract sizing, as well as stationary operating policies for profit maximization in the long-run. We propose a stylized model calibrated to actual wind power production that allows us to obtain limiting distributions of battery storage levels, assess the value of storage size and perform a sensitivity analysis on key parameters such as contract prices, capacity payments and storage efficiency. We develop the case with contracts of constant price, outline how this model can be extended to a variable-price setting and discuss potential challenges in that avenue.
针对不确定的可再生能源,以数据为导向确定同地存储的规模
我们提出了一个高层次的随机稳态模型,以分析通过远期合同参与电力市场并使用存储来解锁容量支付的风电生产商的共置储能系统的价值。特别是,我们试图找到最优的存储和合同规模,以及长期利润最大化的固定运营策略。我们提出了一个风格化的模型,根据实际的风力发电进行校准,使我们能够获得电池存储水平的限制分布,评估存储规模的价值,并对合同价格、容量支付和存储效率等关键参数进行敏感性分析。我们以固定价格合同为例,概述了如何将该模型扩展到可变价格设置,并讨论了该方法中的潜在挑战。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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