.png){kind=icon}
.png){kind=icon}
Return
Active distribution network operational optimization problem: A multi-objective tuna swarm optimization model
.png){kind=icon}
PRE
AI
DOI：10.1016/j.asoc.2023.111087.png)
.png){kind=icon}
Original request for help.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
This study proposes multi-objective tuna swarm optimization through multi-objective transformation, initialization improvement and population variation for active distribution network (ADN). The ADN energy optimization model with dynamic reconfiguration, reactive power compensation, on-load tap changer and controllable load coordinated control are established with the minimum economic and environmental cost. Several controllable resources increase and increase the complexity of energy optimization problem in realized the effective clean energy consumption and the power grid stable operation. The minimum control cost and the minimum node voltage deviation are proposed. This study also proposes a decision-making method based on pareto front and an index to evaluate the maximum extensible dimension of intelligent algorithms in the process of analyzing energy optimization problems with intelligent algorithms. The proposed ADN energy optimization method based on multi-objective tuna swarm optimization shows excellent results after testing with the improved IEEE33 system. The voltage deviation and network loss are reduced by 51.62% and 22.16% on average
Keywords:
Active distribution network
Multi-objective tuna swarm optimization
Multi-objective decision making
Dynamic reconstruction
Controllable load
Journal
IF:
6.6
Papers:
1.4W
Citations:
4.8W