High penetration of renewables in the distribution network brings significant uncertainties, especially during volatile weather conditions. Hence, the network controllers should be designed to account for these uncertainties, and respond to unpredictable events like voltage-dips for reliable voltage control. This paper proposes a control scheme, where inverter-based Distributed Energy Resources (DERs) respond locally with Q(V) control and adapt to set-points assigned by the centralized controller (CC). The Robust Constrained Model Predictive Control (RCMPC) scheme is proposed for centralized voltage control. It robustly deploys control resources from DERs and tap-changers to regulate the lower/upper bound of node voltages within the targeted limit. Moreover, RCMPC ensures minimum resource utilization by relaxing the targeted voltage limit whenever it anticipates significant uncertainties. The CC is implemented in Python, which communicates with the RMS model of the UKGDS network for measurements and dispatching set-points. The performance of RCMPC is compared with deterministic MPC (DMCP) at 5, 10, and 15-minute time-steps of CC. The proposed RCMPC can regulate the node voltage even at a higher degree of uncertainty seen at a 15-minute time-step. In contrast, the DMPC could not contain the node voltages under the targeted limit and worsened at a larger time-step.

中文翻译：

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有源配电网中的鲁棒约束模型预测电压控制

可再生能源在配电网络中的高度渗透带来了巨大的不确定性，尤其是在多变的天气条件下。因此，网络控制器应设计为解决这些不确定性，并响应不可预测的事件（例如电压降），以实现可靠的电压控制。本文提出了一种控制方案，其中基于逆变器的分布式能源（DER）通过Q（V）控制进行本地响应，并适应中央控制器（CC）分配的设定点。提出了一种鲁棒约束模型预测控制（RCMPC）方案，用于集中式电压控制。它强大地部署了来自DER和分接开关的控制资源，以将节点电压的下限/上限限制在目标限值之内。此外，RCMPC在预期到明显的不确定性时，通过放宽目标电压限制来确保最低的资源利用率。CC用Python实现，该Python与UKGDS网络的RMS模型进行通信以进行测量和调度设定点。将RCMPC的性能与CC的5分钟，10分钟和15分钟的确定性MPC（DMCP）进行比较。所提出的RCMPC甚至可以在15分钟的时间步长上看到更高的不确定度时，也可以调节节点电压。相反，DMPC不能包含低于目标限制的节点电压，并且在更大的时间步长时会恶化。将RCMPC的性能与CC的5分钟，10分钟和15分钟的确定性MPC（DMCP）进行比较。所提出的RCMPC甚至可以在15分钟的时间步长上看到更高的不确定度时，也可以调节节点电压。相反，DMPC不能包含低于目标限制的节点电压，并且在更大的时间步长时会恶化。将RCMPC的性能与CC的5分钟，10分钟和15分钟的确定性MPC（DMCP）进行比较。所提出的RCMPC甚至可以在15分钟的时间步长上获得更高的不确定度，也可以调节节点电压。相反，DMPC不能包含低于目标限制的节点电压，并且在更大的时间步长时会恶化。