With the increase of distributed generator (DG) penetration in the power system

new challenges have been taken to the optimal operation of distributed system in large scale. The reactive power optimization is analyzed on the basis of cluster division with the consideration of DG integration. The modified electrical distance is introduced as the distance measurement in clustering algorithm. The spectral clustering method is applied to divide the high-denetration distributed renewable energy system into several sub-communities and determine the key nodes in each cluster. With the minimum network loss and voltage fluctuation as the optimization goal

the reactive power of the photovoltaic inverter at the key node is adjusted to reduce the network loss and stabilize the voltage output. In order to solve the problem of dual-objective reactive power optimization

an intelligent voltage regulation strategy based on improved particle swarm optimization algorithm is proposed to optimize reactive power for multiple sub-communities. The cluster division method and the reactive power optimization strategy are applied to the IEEE 33-bus standard system

which improves the node voltage stability and reduces the network loss. Aiming at the large-scale distributed energy system

a fast intelligent voltage regulation strategy is further proposed

which is applied to the actual system of a certain district in Jinzhai County

Anhui Province

and has good control effect

and has been greatly reduced in terms of adjustment time

operation cost and input cost.