arXiv 2409.080842024-09-12eess.SYcs.SY

考虑爬坡速率、爬坡、时限和容量约束的线性储能与灵活性模型

Linear energy storage and flexibility model with ramp rate, ramping, deadline and capacity constraints

Md Umar Hashmi, Dirk Van Hertem, Aleen van der Meer, Andrew Keane

AI总结：

本研究针对电网有源组件建模需求，提出考虑爬坡与容量限制、精确建模爬坡速率约束的线性储能及灵活性套利模型，可高效求解，实验验证了慢爬坡资源的套利价值。

摘要：

随着储能、以及源自电动汽车、热泵、工业流程等负荷的灵活性等有源组件不断增多，电网正持续演进。我们需要更完善的模型来准确表征这类资源，否则其真实能力可能被高估或低估。本研究提出了一种全新的储能与灵活性套利模型，该模型同时考虑爬坡（功率）限制和容量（能量）限制，同时对爬坡速率约束进行精确建模。所提出的模型为线性结构，可作为线性规划问题使用现成求解器高效求解。我们还提供了一个在线代码仓库，以支持更广泛的应用和基准测试。最后，我们开展了数值案例研究，以量化爬坡速率约束对储能与灵活性利润最大化运营目标的敏感性。对于爬坡速率较慢的资源，研究结果颇具参考价值。我们观察到，对于爬坡速率限制为最大爬坡限制10%的资源，与无爬坡速率限制的情况相比，利用这类资源进行能源套利的边际价值超过最大利润的65%，最高可达90%。

英文摘要：

The power networks are evolving with increased active components such as energy storage and flexibility derived from loads such as electric vehicles, heat pumps, industrial processes, etc. Better models are needed to accurately represent these assets; otherwise, their true capabilities might be over or under-estimated. In this work, we propose a new energy storage and flexibility arbitrage model that accounts for both ramp (power) and capacity (energy) limits, while accurately modelling the ramp rate constraint. The proposed models are linear in structure and efficiently solved using off-the-shelf solvers as a linear programming problem. We also provide an online repository for wider application and benchmarking. Finally, numerical case studies are performed to quantify the sensitivity of ramp rate constraint on the operational goal of profit maximization for energy storage and flexibility. The results are encouraging for assets with a slow ramp rate limit. We observe that for resources with a ramp rate limit of 10% of the maximum ramp limit, the marginal value of performing energy arbitrage using such resources exceeds 65% and up to 90% of the maximum profit compared to the case with no ramp rate limitations.

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