| The development of smart grids and new energy technologies has promoted the application of flexible loads and also made the composition and uncertainties of the load side more complicated.At the same time,with the advent of the big data era,grid data has exploded,causing the new challenges of power systems security and stability assessments.Available transmission capacity(ATC)is an important indicator for grid dispatching and power market transactions.The traditional model-based analysis methods for ATC of power systems always calculate slowly,so it is difficult to meet the online assessment requirements of ATC,which data mining methods provide new ideas to solve.The thesis conducts the research on the fast estimation method of ATC considering the load side uncertainties,whose work and results mainly include:(1)The description method of the load side uncertainties is studied,mainly considering the uncertainties of wind power output,photovoltaics,price-based demand response,and incentive-based demand response.The load side uncertainties are different from the source side uncertainties,because most load nodes on the load side have uncertainties.This description method is superimposed,so it can effectively deal with this characteristic of the load side.Taking the wind power data of Northern Ireland in 2019,the photovoltaic data of the certain area of Shandong in 2016,and the load data of the city of Shandong Power Grid as samples,the results show that the uncertainty description method of wind power and photovoltaic has strong adaptability,and can better fit the multi-peak and asymmetric characteristics of the prediction error probability distribution of wind power and photovoltaic output,which is more accurate than nuclear density distribution,T distribution and normal distribution.The fitting effect of this method is affected by the number of sub-Gaussians,and the effect of uncertainties of the price-based demand response and incentive-based demand response on the load curve is obvious.The study of description method of the load side uncertainties is the the foundation for the estimation method of ATC considering load side uncertainties.(2)A TTC statistical moment calculation method based on the improved multi-point estimation method is studied.The above description method of the load side uncertainties is used to descripe the uncertainties of wind power output,photovoltaics,price-based demand response,and incentive-based demand response.Wind power output,photovoltaics,price-based demand response,and incentive-based demand response are calculated by Nataf transformation and Guass-Hermite integral,and then TTC statistical moment considering load side uncertainties is calculated in operating scenarios set.The simulation results of 500kV and above main grid system of Shandong Power Grid show that the method can account for the uncertainties of load side effectively and its accuracy can be improved by increasing the number of point estimates,which is more acurrate than the two-point estimation method that improved by Nataf transformation.(3)An ATC estimation method based on stacked denoising autoencoder(SDAE)and the improved multi-point estimation method is studied.The above description method of the load side uncertainties is used to descripe the uncertainties of wind power output,photovoltaics,price-based demand response,and incentive-based demand response.ATC under certain limit violation probability is derived based on SDAE and Gram-Charlier series expansion calculations.Compared with ATC in the traditional deterministic scenarios,ATC under certain limit violation probability evaluates the remaining transfer capability of the transmission lines more comprehensively.The simulation results of 500kV and above main grid system of Shandong Power Grid show that the method is more acurrate than the two-point estimation method that improved by Nataf transformation,and the TTC calculation method in deterministic scenarios is more acurrate than principal component analysis combined with neural network and ordinary neural network.This method can effectively account for the uncertainties of load side,whose accuracy can be improved by increasing the point number of the estimation method. |
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