Active power distribution network fault management method based on random optimization

Abstract

The invention discloses an active power distribution network fault management method based on random optimization, and the method comprises the steps: building an uncertainty model, initializing a system, obtaining initial data, and simulating scene data including a load demand, renewable energy output and fault duration through a Monte Carlo method; and then, establishing a power optimization andpower flow optimization two-stage model, and meanwhile, configuring a risk management scheme to ensure that the obtained scheduling strategy can keep good applicability when facing an extreme scene.In the solving process, decoupling calculation is carried out on power optimization and power flow optimization, alternate iteration is carried out, and the difference value of the network loss valuescalculated twice is used as a convergence criterion; and finally, a calculation result during final convergence is taken as a day-ahead optimal scheduling strategy. According to the method, the economic benefit of the active power distribution network during normal operation can be effectively improved, and meanwhile, the load reduction cost under the fault condition is remarkably reduced.

Description

technical field [0001] The invention relates to a stochastic optimization-based active distribution network fault management method. Background technique [0002] With the large-scale use of fossil fuels causing global warming, the probability of extreme natural disasters such as tsunamis and earthquakes has increased significantly, and the resulting large-scale power outages have caused major economic losses to the power grid. The solution to environmental pollution and resource shortage has become urgent, and clean energy renewable energy (Renewable Energy Source, RES), mainly including wind turbine (Wind Turbine WT) and photovoltaic (Photovoltaic array PV) has gradually become a research hotspot and is widely used in power distribution. The penetration rate in the network continues to increase. However, the output of wind turbines at night is often more than that during the day, and the change trend is opposite to the load demand, which has the characteristics of anti-pe...

AI Technical Summary

Problems solved by technology

In practice, the unplanned island time, that is, the duration of the failure, is uncertain and cannot be accurately predicted

This poses a serious challenge to the dispatching strategy of the distribution network to deal with fault situations. When considering the intermittency and volatility of renewable energy and the uncertainty of load demand, this fault management problem becomes more complicated and must be Solved by appropriate random methods

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