A study on the integrated application of computational methods in low-voltage distributed photovoltaic user regulation and station side-end autonomy strategies

Guocheng Li1, Cong Wang1, Zeguang Lu1, Ze Zhang1, Xiaoran Li1, Xiaoqin Wang2
1State Grid Dezhou Power Supply Company, Dezhou, Shandong, 253000, China
2Sichuan Changduo Electric Power Engineering Co., Ltd., Zibo, Shandong, 255000, China

Abstract

This paper follows the active reactive power cooperative control strategy of station voltage autonomy, combines the operation scenarios of the autonomous control strategy within the group, and establishes the reactive power optimization objective function of the low-voltage distribution network to improve the voltage quality and reduce the active loss, which takes into account the installation location of reactive power compensation device, and the constraints include the system power balance constraints and voltage quality constraints. In order to solve the reactive power optimization model of low-voltage distribution network containing distributed photovoltaic, the uniformity of the population distribution of the MPA algorithm is initialized using Bernoulli mapping, the inertia weight function and elite strategy of nonlinear attenuation are introduced to enhance the optimization capability of the MPA algorithm in the iterative process, and the eddy-current and fish aggregation effects are applied to widen the scope of optimization search. The network loss and voltage amplitude of the proposed strategy are analyzed to compare the changes of node voltage, voltage offset, objective function value and branch circuit active loss before and after the voltage autonomous reactive power control of low voltage stations. After adopting the optimization strategy of voltage autonomous reactive power control for LV stations, the branch circuit active loss of LV distribution network decreases with the increase of the proportion of distributed PV, and the branch circuit active loss of LV distribution network can be reduced by up to 60%.

Keywords: distributed PV, distribution network reactive power optimization, reactive power compensation, MPA algorithm