Input Convex Neural Networks for Optimal Voltage Regulation

Understand

The increasing penetration of renewables in distribution networks calls for faster and more advanced voltage regulation strategies.

• A promising approach is to formulate the problem as an optimization problem, where the optimal reactive power injection from inverters are calculated to maintain the voltages while satisfying power network constraints.
• However, existing optimization algorithms require the exact topology and line parameters of underlying distribution system, which are not known for most cases and are difficult to infer.
• In this paper, we propose to use specifically designed neural network to tackle the learning and optimization problem together.