Modern electric systems, such as electric vehicles, mobile robots, nano satellites, and drones, require to support various power-demand operations for user applications and system maintenance. This, in turn, calls for advanced power management that jointly considers power demand by the operations and power supply from various sources, such as batteries, solar panels, and supercapacitors. In this article, we develop a power scheduling framework for a reliable energy storage system with multiple power-supply sources and multiple power-demand operations. Specifically, we develop offline power-supply guarantee analysis and online power management. The former provides an offline power-supply guarantee such that every power-demand operation completes its execution in time while the sum of power required by individual operations does not exceed the total power supplied by the entire energy storage system at any time; to this end, we develop a plain power-supply analysis as well as its improved version using real-time scheduling techniques. On the other hand, the latter efficiently utilizes the surplus power available at runtime for improving system performance; we propose two approaches, depending on whether future scheduling information of power-demanding tasks is available or not. For evaluation, we perform simulations to evaluate both the plain and improved analyses for offline power guarantee under various synthetic power-demand operations. In addition, we have built a simulation model and demonstrated that the proposed framework with the offline analysis and online management not only guarantees the required power-supply, but also enhances system performance by up to 56.49 percent.

中文翻译：

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利用实时调度为电力系统提供电力保证


现代电力系统，例如电动汽车、移动机器人、纳米卫星和无人机，需要支持用户应用和系统维护的各种电力需求操作。这反过来又需要先进的电源管理，共同考虑运营的电力需求和各种来源的电力供应，例如电池、太阳能电池板和超级电容器。在本文中，我们为具有多个电源和多个电力需求操作的可靠储能系统开发了一个电力调度框架。具体来说，我们开发了离线供电保障分析和在线电源管理。前者提供离线供电保证，使得每次用电操作都能及时完成执行，且各个操作所需的电量总和不超过整个储能系统在任何时刻提供的总电量；为此，我们开发了简单的电源分析及其使用实时调度技术的改进版本。另一方面，后者有效地利用运行时可用的剩余功率来提高系统性能；我们提出两种方法，具体取决于耗电任务的未来调度信息是否可用。为了进行评估，我们进行了模拟，以评估各种综合电力需求操作下离线电力保障的简单分析和改进分析。此外，我们还建立了仿真模型，并证明所提出的框架通过离线分析和在线管理不仅保证了所需的供电，而且还将系统性能提高了高达56.49%。