Unlocking and managing flexibility is an important contribution to the integration of renewable energy and an efficient and resilient operation of the power system. In this paper, we discuss how the potential of a fleet of battery-electric transportation vehicles can be used to provide frequency containment reserve. To this end, we first examine the use case in detail and then present the system designed to meet this challenge. We give an overview of the tasks and individual sub-components, consisting of (a) an artificial neural network to predict the availability of Automated Guided Vehicles (AGVs) day-ahead, (b) a heuristic approach to compute marketable flexibility, (c) a simulation to check the plausibility of flexibility schedules, (d) a multi-agent system to continuously monitor and control the AGVs and (e) the integration of fleet flexibility into a virtual power plant. We also present our approach to the economic analysis of this provision of a system-critical service in a logistical context characterised by high uncertainty and variability.

中文翻译：

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汉堡集装箱码头Altenwerder中的电池电动自动导引车的灵活性管理和提供平衡服务

释放和管理灵活性是对可再生能源的整合以及电力系统高效，弹性运行的重要贡献。在本文中，我们讨论了如何利用一组电池电动运输车辆的潜力来提供频率限制储备。为此，我们首先详细研究用例，然后介绍旨在应对这一挑战的系统。我们对任务和各个子组件进行了概述，其中包括（a）人工神经网络来预测日前自动引导车辆（AGV）的可用性，（b）一种启发式方法来计算可销售的灵活性，（c ）模拟，以检查灵活性时间表的合理性，（d）多主体系统，可连续监视和控制AGV，以及（e）将车队灵活性集成到虚拟电厂中。我们还介绍了在具有高度不确定性和可变性的后勤环境中对这种系统关键服务的提供进行经济分析的方法。