Chance-Constrained Generic Energy Storage Operations Under Decision-Dependent Uncertainty
Chance-Constrained Generic Energy Storage Operations Under Decision-Dependent Uncertainty
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DOI：
10.1109/tste.2023.3262135
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发表时间：
2022-01
影响因子：
8.8
通讯作者：
Ning Qi;P. Pinson;M. Almassalkhi;Lin Cheng-;Yingrui Zhuang
中科院分区：
文献类型：
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作者：
Ning Qi;P. Pinson;M. Almassalkhi;Lin Cheng-;Yingrui Zhuang
与大规模物理电池相比，聚合和协调的通用储能(GES)资源为电网运营提供了低成本但不确定的灵活性。虽然GES可以用不同类型的不确定性来描述，但文献主要集中在决策独立不确定性(DIUS)上，例如天气条件引起的外源随机扰动。相反，本文侧重于新引入的决策相关不确定性(DDU)，并考虑了考虑受激励信号和不适程度影响的不确定可用荷电状态(SOC)界限的最优GES调度。为了引入DDU，我们提出了一种新的机会约束优化(CCO)方法来解决GES机组的日前经济调度问题。提出了两种简单的方法来解决所提出的带DDU的CCO问题：(I)对一般的但不完全分布的DDU的稳健重构；(Ii)对特定的和已知的DDU分布的迭代算法。在此基础上，引入可靠性指标，验证了该方法对发电机组响应可靠性的适用性。基于仿真的分析表明，通过在约束中加入DDU并利用数据驱动的参数辨识，所提出的方法产生了保守但可信的GES调度策略，并降低了惩罚成本。这改善了协调的全球环境观测系统单元的可用性和性能。
Compared with large-scale physical batteries, aggregated and coordinated generic energy storage (GES) resources provide low-cost, but uncertain, flexibility for power grid operations. While GES can be characterized by different types of uncertainty, the literature mostly focuses on decision-independent uncertainties (DIUs), such as exogenous stochastic disturbances caused by weather conditions. Instead, this manuscript focuses on newly-introduced decision-dependent uncertainties (DDUs) and considers an optimal GES dispatch that accounts for uncertain available state-of-charge (SoC) bounds that are affected by incentive signals and discomfort levels. To incorporate DDUs, we present a novel chance-constrained optimization (CCO) approach for the day-ahead economic dispatch of GES units. Two tractable methods are presented to solve the proposed CCO problem with DDUs: (i) a robust reformulation for general but incomplete distributions of DDUs, and (ii) an iterative algorithm for specific and known distributions of DDUs. Furthermore, reliability indices are introduced to verify the applicability of the proposed approach with respect to the reliability of the response of GES units. Simulation-based analysis shows that the proposed methods yield conservative, but credible, GES dispatch strategies and reduced penalty cost by incorporating DDUs in the constraints and leveraging data-driven parameter identification. This results in improved availability and performance of coordinated GES units.