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Load Estimation of Complex Power Networks from Transformer Measurements and Forecasted Loads
Joint Authors
Source
Issue
Vol. 2020, Issue 2020 (31 Dec. 2020), pp.1-14, 14 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2020-01-22
Country of Publication
Egypt
No. of Pages
14
Main Subjects
Abstract EN
This paper presents a load estimation method applicable to complex power networks (namely, heavily meshed secondary networks) based on available network transformer measurements.
The method consists of three steps: network reduction, load forecasting, and state estimation.
The network is first mathematically reduced to the terminals of loads and measurement points.
A load forecasting approach based on temperature is proposed to solve the network unobservability.
The relationship between outdoor temperature and power consumption is studied.
A power-temperature curve, a nonlinear function, is obtained to forecast loads as the temperature varies.
An “effective temperature” reflecting complex weather conditions (sun irradiation, humidity, rain, etc.) is introduced to properly consider the effect on the power consumption of cooling and heating devices.
State estimation is adopted to compute loads using network transformer measurements and forecasted loads.
Experiments conducted on a real secondary network in New York City with 1040 buses verify the effectiveness of the proposed method.
American Psychological Association (APA)
Rong, Haina& de León, Francisco. 2020. Load Estimation of Complex Power Networks from Transformer Measurements and Forecasted Loads. Complexity،Vol. 2020, no. 2020, pp.1-14.
https://search.emarefa.net/detail/BIM-1140045
Modern Language Association (MLA)
Rong, Haina& de León, Francisco. Load Estimation of Complex Power Networks from Transformer Measurements and Forecasted Loads. Complexity No. 2020 (2020), pp.1-14.
https://search.emarefa.net/detail/BIM-1140045
American Medical Association (AMA)
Rong, Haina& de León, Francisco. Load Estimation of Complex Power Networks from Transformer Measurements and Forecasted Loads. Complexity. 2020. Vol. 2020, no. 2020, pp.1-14.
https://search.emarefa.net/detail/BIM-1140045
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1140045