Week-ahead dispatching of active distribution networks using hybrid energy storage systems

IF 4.8 2区 工程技术 Q2 ENERGY & FUELS
Matthieu Jacobs, Rahul Gupta, Mario Paolone
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引用次数: 0

Abstract

This paper presents a week-long scheduling approach to address the issues associated with uncertain stochastic generation. Specifically, the method is designed for active distribution networks (ADNs) hosting hybrid energy storages, composed by a hydrogen energy storage system (HESS) and a battery energy storage system (BESS). The inclusion of a pressurized HESS allows to balance energy over longer time periods, as opposed to methods considering only BESSs. To this end, this paper combines linearized models for the electricity grid with linearized models of the HESS to solve a tractable scheduling problem. The proposed optimal schedule consists of an active power trajectory at the grid connection point (GCP), called the dispatch plan, and the unit commitment schedule of a PEM fuel cell and electrolyzer system interfacing the electricity network with the HESS. Additionally, a bilevel model predictive control strategy is proposed, where the upper layer MPC computes a storage target accounting for the full horizon, while the lower layer computes the controllable resource setpoints to minimize the dispatch tracking error in each period. A numerical experiment shows the effectiveness of the proposed scheduling and control to accurately compute and track a dispatch plan over a full week. The results clearly show the benefits of combining a HESS with a BESS especially in periods where the prosumption is highly uncertain. Finally, we discuss the computational challenges associated with the weekly horizon and the use of a HESS that exhibits different dynamics than a BESS and propose an approach to mitigate the computational cost.

利用混合储能系统对主动配电网进行周前调度
本文介绍了一种周调度方法,用于解决与不确定随机发电相关的问题。具体来说,该方法是针对由氢储能系统(HESS)和电池储能系统(BESS)组成的混合储能有源配电网(ADN)而设计的。与只考虑电池储能系统的方法相比,加入加压氢储能系统可以在更长的时间段内实现能量平衡。为此,本文将电网的线性化模型与 HESS 的线性化模型相结合,解决了一个棘手的调度问题。建议的最优调度包括电网连接点(GCP)上的有功功率轨迹(称为调度计划),以及连接电网与 HESS 的 PEM 燃料电池和电解槽系统的单位承诺调度。此外,还提出了一种双层模型预测控制策略,其中上层 MPC 计算整个范围内的存储目标,而下层则计算可控资源设定点,以最小化每个周期的调度跟踪误差。数值实验表明,建议的调度和控制能有效准确地计算和跟踪一整周的调度计划。实验结果清楚地表明了将 HESS 与 BESS 相结合的优势,尤其是在预测消耗高度不确定的时期。最后,我们讨论了与周范围相关的计算挑战,以及使用与 BESS 不同动态的 HESS 所带来的挑战,并提出了一种降低计算成本的方法。
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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来源期刊
Sustainable Energy Grids & Networks
Sustainable Energy Grids & Networks Energy-Energy Engineering and Power Technology
CiteScore
7.90
自引率
13.00%
发文量
206
审稿时长
49 days
期刊介绍: Sustainable Energy, Grids and Networks (SEGAN)is an international peer-reviewed publication for theoretical and applied research dealing with energy, information grids and power networks, including smart grids from super to micro grid scales. SEGAN welcomes papers describing fundamental advances in mathematical, statistical or computational methods with application to power and energy systems, as well as papers on applications, computation and modeling in the areas of electrical and energy systems with coupled information and communication technologies.
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