Coordinated Optimal Control of Distributed Photovoltaic Cluster Based on Enhanced Pinning

Due to the intermittent and uncertain output of distributed photovoltaic power, the problem of grid voltage and frequency out of limit has become increasingly prominent. This paper proposes a distributed photovoltaic cluster collaborative optimization control strategy. Firstly, reinforcement learning and pinning control are integrated, and the action of Q-learning is realized through pinning control; The cluster is divided by the sensitivity of active power and voltage and reactive power and voltage of the distribution network, and the pinning node of each cluster is selected; Secondly, the optimal control model between clusters is established and solved by artificial fish swarm algorithm. On this basis, according to the optimal action selected by reinforcement pinning learning, all agents will realize the optimal coordinated control of system frequency and voltage; Finally, the simulation analysis is carried out with an example, and the results show that the voltage control strategy based on enhanced pinning photovoltaic cluster collaborative optimization can effectively improve the voltage operation level of distribution network.