The application discloses a kind of
reinforcement learning power distribution network
voltage regulation method and
system considering photovoltaic heterogeneity characteristics, it is related to power
system operation optimization and
artificial intelligence technical field, including based on
voltage active and
voltage reactive sensitivity Construction
electrical distance index, and the
power grid is divided into multiple sub-regions, constructs multi-agent distributed control architecture;According to the control difference of photovoltaic equipment in power distribution network, three kinds of heterogeneous
photovoltaic inverter models including uncontrollable, only reactive power controllable, active and reactive power collaborative control are constructed;The distributed
voltage regulation problem of power distribution network is modeled as Markov game, and a training framework based on multi-agent flexible actor-critic
algorithm is constructed, and the agent is centrally trained using historical operation data;The trained agent is deployed to each sub-region, and each agent generates a control strategy in real time according to local observation information, and is mapped to the actual
power setting value of the heterogeneous
photovoltaic inverter.The method of the application accurately cooperates and regulates heterogeneous resources.