Voltage prediction control method considering loss reduction optimization of wind power plant current collection line

Abstract

The invention belongs to the technical field of wind power plant operation control, and particularly relates to a voltage prediction control method considering wind power plant current collection lineloss reduction optimization, which comprises the steps of establishing a prediction model among reactive power, voltage and loss by adopting an experimental method; comprehensively considering a target function of voltage wave fluctuation and current collection system loss in a prediction period and an optimization solving method based on a particle swarm algorithm; designing a self-adaptive target function for the target function, wherein the target weight coefficient realizes self-adaptive calculation; carrying out iterative optimization on the target weight coefficient so that the weightsof the voltage stabilization sub-target and the current collection system loss sub-target are gradually improved while the constraint condition is preferentially guaranteed; selecting a reactive set value of each wind turbine generator set as an optimization variable; for farther prediction points, temporarily determining and averagely distributing only the total reactive set values of all the wind turbine generators to each wind turbine generator, and specifically optimizing the specific distribution of the reactive set values of the second prediction point in the next round of optimization,so that the variable dimensionality is reduced in a rolling manner.

Description

technical field [0001] The invention belongs to the technical field of wind farm operation control, and in particular relates to a voltage prediction control method considering the optimization of the loss reduction of wind farm collector lines. Background technique [0002] With the continuous development of wind power technology, intelligence, refinement and high efficiency have become the new trend of wind power operation. Due to large-scale centralized development and time-varying wind power output, wind farms have a significant impact on the voltage stability of the connected grid. Therefore, wind farms must be equipped with reliable voltage control systems to ensure grid-connected point voltage and power factor under different working conditions. Comply with grid requirements. [0003] At present, the wind farm-level automatic voltage control system mainly performs reactive power adjustment based on the current working conditions, such as the patent "A Wind Farm React...

AI Technical Summary

Problems solved by technology

However, in complex scenarios such as wind speed fluctuations, drastic changes in the active power of wind turbines will cause fluctuations in the grid-connected point voltage and power factor

The traditional wind farm reactive power adjustment strategy lacks a pre-judgment mechanism for voltage adjustment, so the speed and stability of adjustment need to be improved

At the same time, due to the long collector lines and many transformer equipment in the wind farm, the problem of line loss is also very prominent. The statistics of the actual operation data of a certain wind farm show that the field loss rate of the wind farm exceeds 7%.

[0004] The conventional wind farm-level voltage control system only aims to maintain voltage stability. In order to pursue the maximum voltage stability, the reactive power equipment and wind turbine reactive power set values ​​are frequently adjusted, and the loss of the power collection system is not concerned. Economic benefits; some voltage control systems that consider the loss of the wind farm power collection system are only optimized for a single scenario, and the optimization target cannot be adjusted according to the operating scenario, resulting in rapid fluctuations in wind speed or failures, etc. Targets cannot coordinate and switch autonomously

[0005] At the same time, due to the large number of wind turbines and reactive power equipment in large-scale wind farms, and the use of predictive model control requires optimization of multiple prediction points, if the conventional optimization algorithm is used, the number of optimization parameters needs to be large, and the dimension of the target search space is too high. As a result, the optimization effect is poor and the optimization speed is slow

Images