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Impact of Energy Storage on Renewable Energy Utilization: A Geometric Description

机译：能量存储对可再生能源利用的影响：几何描述

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摘要

The high penetration of volatile renewable energy challenges power system operation. Energy storage units (ESUs) can shift the demand over time and compensate real-time discrepancy between generation and demand, and thus improve system operation flexibility and reduce renewable energy curtailment. This paper proposes two parametric optimization models to quantify how the power (MW) and energy (MWh) capacity of ESU would impact renewable energy utilization from two aspects: renewable energy curtailment and system flexibility for uncertainty mitigation. The two indicators are characterized as multivariate functions in the capacity parameters of ESUs. A severity ranking algorithm is suggested to pick up critical scenarios of fluctuation patterns from the uncertainty set; consequently, the proposed models come down to multi-parametric mixed-integer linear programs (mp-MILPs) which can be solved by a decomposition algorithm. The proposed method provides analytical expressions of the two indicators as functions in MW and MWh capacity. Such a characterization delivers abundant sensitivity information on the impact of ESU capacity parameters, and provides a powerful tool for visualization and useful reference for storage sizing. Case studies verify the effectiveness of the proposed method and demonstrate how to use the geometric information.
机译：挥发性可再生能源的高渗透挑战电力系统运行。能量存储单元（ESU）可以随时间移动需求并补偿生成和需求之间的实时差异，从而提高系统运行灵活性，降低可再生能源缩减。本文提出了两个参数优化模型，以量化ESU的功率（MW）和能量（MWH）能力如何影响来自两个方面的可再生能源利用：可再生能源缩减和不确定性减缓的系统灵活性。这两个指示器的特征在于ESU的容量参数中的多变量功能。建议严重等级排名算法从不确定性集中拾取波动模式的临界场景;因此，所提出的模型归结为可以通过分解算法解决的多参数混合整数线性程序（MP-MILP）。该方法提供了两种指标作为MW和MWH容量中的功能的分析表达式。这种表征在ESU容量参数的影响下提供了丰富的灵敏度信息，并为存储尺寸提供了一个强大的可视化和有用参考工具。案例研究验证了所提出的方法的有效性，并演示如何使用几何信息。

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