Site Characterization Index for Continuous Power Quality Monitoring Based on Higher-order Statistics

查看全文 作　　者：Olivia Florencias-[1]Oliveros;Juan-José González-de-la-[1]Rosa;Jose-María Sierra-[1]Fernández;Agustín Agüera-[1]Pérez;Manuel-Jesús Espinosa-[1]Gavira;José-Carlos Palomares-[1]Salas 机构地区：[1]Department of Automation Engineering,Electronics,Architecture and Computers Networks,Research Group TIC168,Higher Polytechnic School,University of Cádiz,Algeciras 11202,Spain 出　　处：《Journal of Modern Power Systems and Clean Energy》索引2022年第10卷第1期,共10页 基　　金：This work was supported by the Spanish Ministry of Science and Innovation(Statal Agency for Research),the EU(AEI/FEDER/UE)via project PID2019-108953RB-C21 Strategies for Aggregated Generation of Photovoltaic Plants:Energy and Meteorological Operational Data(SAGPVEMOD),the precedent TEC2016-77632-C3-3-R. 摘　　要：The high penetration of distributed generation(DG)has set up a challenge for energy management and consequently for the monitoring and assessment of power quality(PQ).Besides,there are new types of disturbances owing to the uncontrolled connections of non-linear loads.The stochastic behaviour triggers the need for new holistic indicators which also deal with big data of PQ in terms of compression and scalability so as to extract the useful information regarding different network states and the prevailing PQ disturbances for future risk assessment and energy management systems.Permanent and continuous monitoring would guarantee the report to claim for damages and to assess the risk of PQ distortions.In this context,we propose a measurement method that postulates the use of two-dimensional(2D)diagrams based on higher-order statistics(HOSs)and a previous voltage quality index that assesses the voltage supply waveform in a continous monitoring campaign.Being suitable for both PQ and reliability applications,the results conclude that the inclusion of HOS measurements in the industrial metrological reports helps characterize the deviations of the voltage supply waveform,extracting the individual customers’pattern fingerprint,and compressing the data from both time and spatial aspects.The method allows a continuous and robust performance needed in the SG framework.Consequently,the method can be used by an average consumer as a probabilistic method to assess the risk of PQ deviations in site characterization. 关 键 词：Continuous statistical monitoring big data data compression higher-order statistics(HOSs) power quality(PQ)