论文标题
基于数据驱动的逆变器的伏特/VAR控制，用于部分可观察到的分布网络
Data-driven Inverter-based Volt/VAr Control for Partially Observable Distribution Networks
论文作者
论文摘要
对于与大量逆变器能源集成在一起的主动分配网络（ADN），由于ADN的大规模ADN，在所有节点上保持准确的模型和部署测量值是不切实际的。因此，当前的ADN模型通常涉及重大错误甚至未知。此外，通常可以部分观察到ADN，因为与重要用户的试点节点或节点只有一些测量值。为了为此类网络提供实用的Volt/VAR控制（VVC）策略，本文提出了数据驱动的VVC方法。首先，通过递归回归封闭形式解决方案来估算系统响应策略，该系统响应策略近似于控制变量与监测节点的状态之间的关系。然后，基于实时测量和新更新的系统响应策略，实现了具有收敛保证的VVC策略。由于递归回归解决方案嵌入了控制阶段，因此建立了数据驱动的闭环VVC框架。考虑到非线性载荷的不平衡分配系统，提出的方法的有效性不仅可以实现快速和自适应电压调节，而且还实现了全系统的优化。
For active distribution networks (ADNs) integrated with massive inverter-based energy resources, it is impractical to maintain the accurate model and deploy measurements at all nodes due to the large-scale of ADNs. Thus, current models of ADNs are usually involving significant errors or even unknown. Moreover, ADNs are usually partially observable since only a few measurements are available at pilot nodes or nodes with significant users. To provide a practical Volt/Var control (VVC) strategy for such networks, a data-driven VVC method is proposed in this paper. Firstly, the system response policy, approximating the relationship between the control variables and states of monitoring nodes, is estimated by a recursive regression closed-form solution. Then, based on real-time measurements and the newly updated system response policy, a VVC strategy with convergence guarantee is realized. Since the recursive regression solution is embedded in the control stage, a data-driven closed-loop VVC framework is established. The effectiveness of the proposed method is validated in an unbalanced distribution system considering nonlinear loads where not only the rapid and self-adaptive voltage regulation is realized but also system-wide optimization is achieved.
