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Forecasting-Aided Monitoring for the Distribution System State Estimation
Joint Authors
Carcangiu, S.
Fanni, A.
Pegoraro, P. A.
Sias, G.
Sulis, S.
Source
Issue
Vol. 2020, Issue 2020 (31 Dec. 2020), pp.1-15, 15 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2020-02-28
Country of Publication
Egypt
No. of Pages
15
Main Subjects
Abstract EN
In this paper, an innovative approach based on an artificial neural network (ANN) load forecasting model to improve the distribution system state estimation accuracy is proposed.
High-quality pseudomeasurements are produced by a neural model fed with both exogenous and historical load information and applied in a realistic measurement scenario.
Aggregated active and reactive powers of small or medium enterprises and residential loads are simultaneously predicted by a one-step ahead forecast.
The correlation between the forecasted real and reactive power errors is duly kept into account in the definition of the estimator together with the uncertainty of the overall measurement chain.
The beneficial effects of the ANN-based pseudomeasurements on the quality of the state estimation are demonstrated by simulations carried out on a small medium-voltage distribution grid.
American Psychological Association (APA)
Carcangiu, S.& Fanni, A.& Pegoraro, P. A.& Sias, G.& Sulis, S.. 2020. Forecasting-Aided Monitoring for the Distribution System State Estimation. Complexity،Vol. 2020, no. 2020, pp.1-15.
https://search.emarefa.net/detail/BIM-1141870
Modern Language Association (MLA)
Carcangiu, S.…[et al.]. Forecasting-Aided Monitoring for the Distribution System State Estimation. Complexity No. 2020 (2020), pp.1-15.
https://search.emarefa.net/detail/BIM-1141870
American Medical Association (AMA)
Carcangiu, S.& Fanni, A.& Pegoraro, P. A.& Sias, G.& Sulis, S.. Forecasting-Aided Monitoring for the Distribution System State Estimation. Complexity. 2020. Vol. 2020, no. 2020, pp.1-15.
https://search.emarefa.net/detail/BIM-1141870
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1141870