Active distribution network (ADN) voltage real-time fuzzy control method

Abstract

The invention discloses an active distribution network (ADN) voltage real-time fuzzy control method. The method comprises steps: according to the maximum and minimum values of feeder voltage uploaded by each feeder, the maximum voltage and the minimum voltage of the distribution system are put forward, if certain feeder voltage exceeds a threshold, a reactive power fuzzy controller FQC for DG (distributed generation) is started, and reactive power is injected or absorbed through the DG; and if the reactive power fuzzy controller FQC for the DG can not restore the voltage to a normal level and deltaVsys</=deltaVmax-deltaalpha, a transformer on-load tap changer fuzzy controller FOC is started, the transformer on-load tap changer OLTC completes a voltage regulating task, or otherwise, an FPC is started, and the deltaVsys is reduced, wherein the deltaalpha is an adjusting value of the tap changer. The main control unit of the invention has a simple control algorithm, the needed communication data are few, the calculation amount is small, the decision-making time is short, problems of over voltage and low voltage caused due to mutual action between the OLTC and the DG can be lessened, and the consumptive ability towards the DG by the ADN can be improved.

Description

technical field [0001] The invention relates to a real-time fuzzy control method for active distribution network voltage. Background technique [0002] The increasingly serious environmental pollution and the shortage of traditional fossil fuels drive the rapid development of distributed generation (Distributed Generation, DG) technology, especially renewable energy (Renewable Energy Sources, RES) power generation technology, and the penetration rate of DG in the distribution network is growing rapidly. , the traditional distribution network will gradually evolve into an active distribution network (Active Distribution Network, ADN) with many adjustable and controllable resources. ADN achieves large-scale renewable energy grid integration and optimizes the primary energy structure through flexible and changeable grid structures and coordinated control of various types of distributed power sources and controllable loads. [0003] Compared with the traditional distribution ne...

AI Technical Summary

Problems solved by technology

However, this control method has the following problems: 1) Renewable energy generation and load forecast data are required, and the accuracy of the forecast data has a great impact on the effectiveness of the control strategy; 2) The network topology information, various The unified processing of a large amount of data such as node state quantities and reactive power / voltage adjustment equipment parameters leads to complex calculations, long calculation time, and it is difficult to meet the real-time requirements of the active power distribution network; 3) There is a convergence problem in the optimization calculation method

[0004] The grid connection of large-scale intermittent energy sources (such as wind energy, solar energy, etc.) in the active distribution network will aggravate voltage fluctuations or cause them to be disconnected from the grid due to overvoltage, which not only seriously restricts the ability of the active distribution network to accommodate renewable energy generation, but also makes The quality of distribution network voltage has declined, which poses new challenges to distribution network voltage control

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