  This paper presents a problem in power networks that creates an exciting and
yet challenging real-world scenario for application of multi-agent
reinforcement learning (MARL). The emerging trend of decarbonisation is placing
excessive stress on power distribution networks. Active voltage control is seen
as a promising solution to relieve power congestion and improve voltage quality
without extra hardware investment, taking advantage of the controllable
apparatuses in the network, such as roof-top photovoltaics (PVs) and static var
compensators (SVCs). These controllable apparatuses appear in a vast number and
are distributed in a wide geographic area, making MARL a natural candidate.
This paper formulates the active voltage control problem in the framework of
Dec-POMDP and establishes an open-source environment. It aims to bridge the gap
between the power community and the MARL community and be a drive force towards
real-world applications of MARL algorithms. Finally, we analyse the special
characteristics of the active voltage control problems that cause challenges
(e.g. interpretability) for state-of-the-art MARL approaches, and summarise the
potential directions.
