Abstract
The power system reactive power optimization model mainly establishes a model to reduce the line active power loss as an indicator. The model is established with the least active power loss, the highest voltage stability margin and the smallest voltage deviation. Aiming at the shortcomings of differential evolution algorithm which is easy to fall into local optimum, this paper proposes to apply dynamic multi-subgroup differential evolution algorithm to power system reactive power optimization. The dynamic subgroup partitioning feature of the algorithm improves the global search ability, and increases the polymorphism of species during the iterative process. The dynamic multi-subgroup differential evolution algorithm and differential evolution algorithm are substituted into the power system IEEE-14 nodes for simulation comparison, and the feasibility and superiority of the algorithm are verified. Comparing the simulation diagrams of the two algorithms, it can be seen that the dynamic multi-subgroup differential evolution algorithm has significant advantages in power system reactive power optimization.
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