High renewable energy permeability power grid recovery optimization method based on robust theory

Abstract

The invention discloses a high renewable energy permeability power grid recovery optimization method based on a robust theory and is used for converting a deterministic power grid recovery optimization model into a robust optimization model, carrying out the solving through employing an artificial bee colony algorithm, and obtaining a power grid recovery scheme considering the uncertainty. The method comprises the following steps of 1, establishing a deterministic power grid recovery optimization model in a high renewable energy permeability power grid recovery process; 2, according to the deterministic model established in the step 1, establishing a double-layer robust model considering the uncertainty of renewable energy sources by applying a robust theory; 3, converting the double-layerrobust model obtained in the step 2 into a single-layer robust model which is easy to solve by applying a dual theorem; and 4, solving the single-layer robust model obtained in the step 3 by adoptingan artificial bee colony algorithm to obtain a power grid recovery scheme considering the uncertainty of renewable energy sources. The method is advantaged in that the power grid recovery scheme obtained by the method can bear all fluctuations in an uncertain interval of renewable energy sources, can ensure the safety of the power grid recovery process, and has certain theoretical values and engineering values.

Description

technical field [0001] The invention belongs to the technical field of power grids, in particular to a restoration optimization method for power grids with high renewable energy penetration rates based on robust theory. Background technique [0002] The participation of renewable energy in grid restoration can help improve the efficiency of system restoration and reduce the curtailment of renewable energy. However, due to the intermittence and volatility of the active output of renewable energy, it may bring a series of safety problems to the restored system. Therefore, it is necessary to study power grid outage recovery schemes that take into account the uncertainty of renewable energy. Methods to deal with the uncertainty of renewable energy include autoregressive-sliding average model method and chance constrained programming method. However, it is difficult to obtain the probability distribution function of the stochastic programming model, and it is difficult to guara...

AI Technical Summary

Problems solved by technology

However, it is difficult to obtain the probability distribution function of the stochastic programming model, and it is difficult to guarantee the accuracy of the probability density function simulated by the sampling method. At the same time, in order to ensure the accuracy of uncertainty processing, a large number of possible scenarios need to be generated, which also increases the burden on the power system.

Images