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A receding horizon control approach for re-dispatching stochastic heterogeneous resources accounting for grid and battery losses

机译:重新调度随机异构资源核算网格和电池损失的后退地平线控制方法

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摘要

In this paper, we propose a re-dispatch scheme for radial distribution grids hosting stochastic Distributed Energy Resources (DERs) and controllable batteries. At each re-dispatch round, the proposed scheme computes a new dispatch plan that modifies and extends the existing one. To do so, it uses the CoDistFlow algorithm and applies a receding horizon control principle, while accounting for hard time computation constraints that impact on the instantaneous update of a dispatch plan. CoDistFlow handles stochastic DERs and prosumers uncertainties via scenario-based optimization and the non-convexity of the AC Optimal Power Flow by iteratively solving suitably defined convex problems until convergence. We perform numerical evaluations based on real-data, obtained from a real Swiss grid. We show that, with our proposed re-dispatch scheme, the daily dispatch tracking error can decrease more than 80%, even for small battery capacities, and if re-dispatch is frequent enough, it can be eliminated. Finally, we show that re-dispatch should be performed as often as the market allows and the performance continues to improve.
机译:在本文中,我们提出了一种重新调度方案,用于托管随机分布能源(DERS)和可控电池的径向分布网格。在每个重新调度回合时,所提出的方案计算了一种修改和扩展现有的新派遣计划。为此,它使用了Codistflow算法,并应用了后退的地平线控制原理,同时考虑了对派遣计划的瞬时更新影响的硬时间计算约束。通过基于场景的优化和AC最佳功率流的非凸性通过迭代地解决直到收敛,通过基于场景的优化和非凸性处理随机的优化和非凸性,处理随机数据流,以及AC最佳功率流的非凸性。我们根据真实瑞士网格获得的实际数据进行数值评估。我们展示,随着我们提出的重新调度方案,日常调度跟踪误差可能会降低80%以上,即使是小电池容量,如果重新调度足够频繁,则可以消除它。最后,我们表明,应尽可能频繁地执行重新派遣,并且性能继续提高。

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