A coordinated control of Flexible AC Transmission Systems (FACTS) reference setpoints is often absent in real systems. Despite the power quality gains demonstrated in studies, this absence can partly be derived from challenges with model-based control. As promising alternative methods of control, data driven approaches based on reinforcement learning (RL) have been considered. In this work, we study the potential gains in power quality using RL while recognizing the increasing number of installed Phasor Measurement Units, providing limited but reliable information. We demonstrate on the IEEE 14-bus and IEEE 57-bus systems that by adding a few measurements per FACTS device and a constraint violation signal, an RL scheme may significantly improve power quality compared to a baseline of fixed setpoints. To evaluate robustness, several configurations are simulated and for larger systems, we identify unobserved constraint violations as the main risk and propose a potential path for new research.