{"title":"Fast measurement-based identification of small signal behaviour of commercial single-phase inverters","authors":"E. Kaufhold, Jan Meyer, P. Schegner","doi":"10.1109/AMPS50177.2021.9586029","DOIUrl":"https://doi.org/10.1109/AMPS50177.2021.9586029","url":null,"abstract":"This paper presents a fast approach for a measurement-based method for the identification of the small signal behaviour of commercially available single-phase inverters. This small signal behaviour is typically represented by a frequency coupling matrix and is used for stability analysis and to derive black-box frequency domain models, e.g. for harmonic power flow studies. Typically, a large amount of measurements is required to identify the frequency coupling matrix of a single device. In case multiple small-signal models are required, i.e. in case of operating point dependency, the amount of measurements increases even further. However, the large number of required measurements is very time and energy consuming. This limits often the level of detail required for developing a comprehensive and accurate model. Therefore, this paper proposes an approach that significantly reduces the required measurements to identify the small signal model in terms of the admittance characteristic of commercially available single-phase inverters with unknown topology and parameters. The improved method is explained and tested for a commercial single-phase photovoltaic inverter in the laboratory.","PeriodicalId":333660,"journal":{"name":"2021 IEEE 11th International Workshop on Applied Measurements for Power Systems (AMPS)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130849916","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
O. Florencias-Oliveros, José María Sierra Fernández, J. D. L. Rosa, Manuel-Jesús Espinosa-Gavira, A. A. Pérez, J. C. P. Salas
{"title":"Instrument for Power Quality monitoring using Higher-Order Statistics 2D planes","authors":"O. Florencias-Oliveros, José María Sierra Fernández, J. D. L. Rosa, Manuel-Jesús Espinosa-Gavira, A. A. Pérez, J. C. P. Salas","doi":"10.1109/AMPS50177.2021.9586011","DOIUrl":"https://doi.org/10.1109/AMPS50177.2021.9586011","url":null,"abstract":"Penetration of renewable energies has changed the way of managing energy and monitoring the quality of the power supply. New types of disturbances have appeared because of uncontrolled connections and non-linear loads, whose stochastic behaviour triggers the need for global indicators capable of dealing with big data in terms of compression and scalability so that to extract useful information regarding network’s status and the prevailing disturbances for risk assessment. We propose a permanent and continuous measurement strategy through a virtual instrument that incorporate higher-order statistics that assesses the voltage waveform from a statistical point of view; using two-dimensional graphics and computing changes in the probability density funtion in the voltage waveform in the point of common coupling (PCC). Being suitable for both power quality and reliability the campaign results also conclude that graphics for the industrial reports that incorporate the skewness and kurtosis measurements helps characterizes the deviations of the voltage supply waveform, extracting the individual customers’ pattern traces, and compressing data, and the signal behaviour under normal operating continuous from both time and spatial considerations. The approach fosters a continuous and robust performance as needed in rel time campaigns in the modern network. Consequently, it can be used as a probabilistic approach to assess the risk of deviation of the voltage quality.","PeriodicalId":333660,"journal":{"name":"2021 IEEE 11th International Workshop on Applied Measurements for Power Systems (AMPS)","volume":"114 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122306075","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Copyright Page","authors":"","doi":"10.1109/icssp.2019.00003","DOIUrl":"https://doi.org/10.1109/icssp.2019.00003","url":null,"abstract":"","PeriodicalId":333660,"journal":{"name":"2021 IEEE 11th International Workshop on Applied Measurements for Power Systems (AMPS)","volume":"48 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1957-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132947803","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}