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Reactive power optimization method of power distribution network

An optimization method and technology of distribution network, applied in the field of power information, can solve problems such as voltage collapse, loss of active power, and raise system voltage, and achieve the effect of small calculation amount and reduced network loss.

Inactive Publication Date: 2013-01-02
SHANGHAI JIAO TONG UNIV +2
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AI Technical Summary

Problems solved by technology

At present, there are problems in my country's power grids including wind farms: the voltage quality is not ideal, and the voltage fluctuations are too large during peak and valley loads
On the one hand, excess reactive power will increase the system voltage, and the excess reactive power flowing in the system will not only consume active power, occupy the capacity of transmission lines and equipment, but also cause voltage drop on the line, affecting voltage quality and stability
On the other hand, insufficient reactive power will lead to a decrease in system voltage, and the electrical equipment cannot be fully utilized. Too low a voltage level may even lead to serious accidents such as voltage collapse.

Method used

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  • Reactive power optimization method of power distribution network
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  • Reactive power optimization method of power distribution network

Examples

Experimental program
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Embodiment

[0028] see figure 1 , a reactive power optimization method for a distribution network, comprising the following steps:

[0029] Step (1): The wind speed of the wind farm is given, and the output power of the wind turbine is determined under this wind speed;

[0030] The change of wind farm output power is caused by the fluctuation of wind speed and wind direction. The wind speed obeys the Weibull distribution, as shown in formula (1):

[0031] φ ( V ) = k c ( V c ) k - 1 exp [ - ( V c ) k ] - - - ( 1 ...

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Abstract

The invention discloses a reactive power optimization method of a power distribution network. The method comprises the steps of 1), building a mathematical model of a fan; 2), initializing the node voltage; 3), building a reactive power planning mathematical model and converting into a multi-objective optimization problem; 4), inputting original data; 5), forming an initial particle swarm and initializing the speeds and the positions of particles; 6), performing load flow calculation and obtaining adaptive values and a current optimum value of the particles; 7), correcting the speeds and the positions of the particles by using an ecological niche weight flight time method; 8), calculating the adaptability of the whole population, obtaining the adaptability value and updating the current optimum solution pBestid; 9), adjusting a control variable of a border crossing point of an individual particle and modifying a border crossing state variable; and 10), determining whether a requirement of an end condition is met, if the requirement of the end condition is met, outputting the result, otherwise, returning to the 6).

Description

technical field [0001] The invention belongs to the technical field of electric power information, and relates to a reactive power optimization method of a power distribution network, which is based on a niche weight flying particle swarm optimization algorithm. Background technique [0002] Wind energy is a cheap renewable energy, and wind-based power generation technology has attracted more and more people's attention. Due to the randomness, intermittent and uncontrollable properties of wind, when wind power is connected to the grid, it will inevitably have an immeasurable impact on the operation of the power system. [0003] Optimizing operation is an important task in the construction of smart grid, and the access of wind power provides a new means of adjustment for the optimization of regional grid operation. At present, there are problems in my country's power grids including wind farms: the voltage quality is not ideal, and the voltage fluctuations are too large duri...

Claims

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Application Information

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IPC IPC(8): H02J3/18
CPCY02E40/30
Inventor 王昕李立学郑益慧王希张忠保邵凤鹏柳杨
Owner SHANGHAI JIAO TONG UNIV
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