NDLI: Probabilistic tools for DMS

Content Provider	IEEE Xplore Digital Library
Author	Vlaehokyriakou, O. Mavrogerrou, K. Trakas, D. Koukoula, D. Sideratos, G. Dinieas, A. Hatziargynou, N. Kouveletsou, M. Leonidaki, E. Aiidreadis, K.
Copyright Year	2015
Description	Author affiliation: Hellenic Electr. Distrib. Network Operator, HEDNO, Athens, Greece (Kouveletsou, M.; Leonidaki, E.; Aiidreadis, K.) \|\| NTUA, Nat. Teclinical Univ., Athens, Greece (Vlaehokyriakou, O.; Mavrogerrou, K.; Trakas, D.; Koukoula, D.; Sideratos, G.; Dinieas, A.; Hatziargynou, N.)
Abstract	The paper presents a set of probabilistic functions based on stochastic RES (PV and Wind) forecasting and probabilistic load flow, which use the AMR (Automatic Meter Reading) infrastructure for data acquisition at MY Networks and the SCADA measurements at the MA" bus. More specifically, probabilistic functions are implemented, in order to provide improved monitoring of the system state, identification in advance and management of operational limits notations (e.g. over voltages), etc. Moreover, probabilistic tools are used for RES Hosting Capacity Evaluation and the Assessment of the impact of Y/Q control strategies of Distributed Energy Resources (DER). Results from the application and evaluation of the probabilistic functions in actual, rural MY feeders with high PY penetration are presented and evaluated.
Starting Page	189
Ending Page	194
File Size	502349
Page Count	6
File Format	PDF
e-ISBN	9781479977369
DOI	10.1109/SEDST.2015.7315205
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2015-09-08
Publisher Place	Austria
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Photovoltaic systems Voltage measurement Meter Reading Predictive models Probabilistic logic Over voltages Probabilistic functions Voltage control Forecasting Load flow Reactive power Probabilistic load flow SCADA systems Y/Q control strategies High PY penetration Renewable Energy Sources Load modeling
Content Type	Text
Resource Type	Article

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