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Intra-Hour Microgrid Economic Dispatch Based on Model Predictive Control

机译:基于模型预测控制的小时内微电网经济派遣

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Renewable energy-based generation facilities emerging in microgrids are modifying many traditional principles of economic dispatch because of the variability and uncertainty of their output characteristics. Since the power generation from renewable resources is difficult to anticipate, a real-time adjustment of generation schedules is necessary after more forecast information becomes available. Intra-hour, or ultra-short-term dispatch, allows microgrid operators to frequently update generators' outputs for providing power supplies efficiently in an uncertain operating condition. However, several technical challenges such as information availability, control architecture, and computational burden make it difficult to find an optimal generation schedule at runtime. This work addresses the intra-hour economic dispatch problem by designing a closed-loop distributed model predictive control (DMPC) that reduces potential variations in the determined generation schedules. At first, optimization problems regarding the behaviors of several participants in a microgrid are formulated. Then, the procedures for achieving the real-time power balance under ramp-rate constraints are detailed. Simulation results present the efficiency of the proposed DMPC for the optimal intra-hour economic dispatch when multiple types of generation resources are considered in a microgrid.
机译:由于其产出特性的可变性和不确定,微电网中出现的可再生能源生成设施正在修改许多传统的经济派遣原则。由于可再生资源的发电难以预测​​,因此在更多预测信息可用后,需要对生成计划的实时调整。小时内或超短术语调度允许微电网运营商经常更新生成器的输出,以便在不确定的操作条件下有效地提供电源。但是,诸如信息可用性,控制架构和计算负担之类的几种技术挑战使得在运行时难以找到最佳的发电时间表。这项工作通过设计闭环分布式模型预测控制(DMPC)来解决时间内经济调度问题,该预测控制减少了所确定的一代时间表中的潜在变化。首先,制定了关于微电网中若干参与者的行为的优化问题。然后,详细介绍了在斜率约束下实现实时功率平衡的程序。仿真结果在微电网中考虑多种类型的生成资源时,提出了所提出的DMPC的效率。

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