DG collaborative planning based on the EV charging station and AHAPSO
algorithm
- haihong bian,
- chengang zhou
, - Zhengyang Guo
haihong bian
Nanjing Institute of Technology
Corresponding Author:bhh_njit@126.com
Author ProfileAbstract
With the popularity of new energy electric vehicles, more and more EV
charging stations have appeared in cities. In the face of the
intermittent and random access of distributed power sources, it brings
problems such as voltage fluctuation and network loss to the
distribution network. This paper proposes a configuration method for
multi-objective collaborative optimization of dis-tributed power
generation under the premise that existing EV charging stations are
connected to the distribution network. First, four typical wind-light
operating scenarios and EV charging sta-tion working scenarios are
constructed based on the K-means clustering algorithm. Secondly, based
on the complementary evaluation mechanism to find the best ratio of wind
and solar in-stallations, create multi-objective functions from the
economic and technical aspects of distributed power planning, and
establish the Pareto optimization evaluation mechanism. Finally, based
on the IEEE-33 node example, the adaptive hybrid annealing particle
swarm algorithm is used to solve the above model, and the Pareto optimal
solution set is obtained to verify that the method pro-posed in this
paper can reasonably plan the distributed power generation and improve
the power quality of the distribution network.