Energy-Function Based Pilot Protection Scheme for Hybrid UHVDC Transmission Applying Improved Hausdorff Distance

A hybrid UHVDC transmission system applying LCC as the rectifier and MMC as the inverter combines the advantages of both converter types,which makes this protection scheme more complicated.A new pilot protection scheme for a three-terminal hybrid DC transmission system applying energy functions is proposed.The energy function for LCC is applied to MMC to derive the energy level of the hybrid system.Furthermore,an improved Hausdorff distance(IHD)algorithm is proposed to detect the difference in energy levels between the normal and fault states.An abrupt change in energy level is characterized by IHD change rate.Time points at which the IHD change rate exceeds the threshold at converter stations are applied to determine the fault line and to estimate the fault section.The proposed protection scheme is then verified by a simulation model of the Wudongde±800 kV three-terminal hybrid UHVDC transmission project.The appropriate sampling frequency is selected for a real-time calculation,and the threshold is selected considering the effect of noise.Results show the proposed scheme can identify and trip fault lines quickly and effectively,even for a 600Ωgrounding fault.Other waveshape similarity algorithms are compared and analyzed.Compared with existing protection schemes,the proposed scheme transmits less data to improve communication speed and reliability.

Decay-like fracture diagnosis of composite insulator based on small sample virtual expansion and radar graph mapping

Due to the complexity of test procedures and the high cost of measurements,the mechanism of the decay-like fracture is unclear,which brings hard concepts and the small sample problem.Therefore,it is intractable to establish accurate data-driven models.To solve the above mentioned problems,this paper proposes a data-driven modeling method based on radar graph mapping models and virtual sample generation(Radar-VSG).The main idea of the proposed method is to construct and select the most appropriate input features by using radar graph mapping,and to generate virtual samples by using the local outlier factor based on the isometric feature mapping algorithm(Isomap-LOF).To verify the effectiveness of our approach,a set of 27 training samples and 127 testing samples from China Southern Power Grid was applied.Experimental results suggested the accuracy was up to 100%after adding more than 27 virtual samples,with a 4.75%improvement.And the model has the best generalisation ability for 270 virtual samples,with the root mean square error of 0.018.Compared with support vector machine and four advanced VSG methods,the proposed Radar-VSG can achieve better performance.