Load forecasting based distribution system network reconfiguration - A distributed data-driven approach

Yi Gu, Huaiguang Jiang, Jun Jason Zhang, Yingchen Zhang, Eduard Muljadi, Francisco Solis

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

In this paper, a short-term load forecasting approach based network reconfiguration is proposed in a parallel manner. Specifically, a support vector regression (SVR) based short-term load forecasting approach is designed to provide an accurate load prediction and benefit the network reconfiguration. Because of the nonconvexity of the three-phase balanced optimal power flow, a second-order cone program (SOCP) based approach is used to relax the optimal power flow problem. Then, the alternating direction method of multipliers (ADMM) is used to compute the optimal power flow in distributed manner. Considering the limited number of the switches and the increasing computation capability, the proposed network reconfiguration is solved in a parallel way. The numerical results demonstrate the feasible and effectiveness of the proposed approach.

Original languageEnglish (US)
Title of host publicationConference Record of 51st Asilomar Conference on Signals, Systems and Computers, ACSSC 2017
EditorsMichael B. Matthews
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1358-1362
Number of pages5
Volume2017-October
ISBN (Electronic)9781538618233
DOIs
StatePublished - Apr 10 2018
Event51st Asilomar Conference on Signals, Systems and Computers, ACSSC 2017 - Pacific Grove, United States
Duration: Oct 29 2017Nov 1 2017

Other

Other51st Asilomar Conference on Signals, Systems and Computers, ACSSC 2017
CountryUnited States
CityPacific Grove
Period10/29/1711/1/17

Fingerprint

Optimal Power Flow
Load Forecasting
Distribution System
Reconfiguration
Data-driven
Short-term Load Forecasting
forecasting
Method of multipliers
Second-order Cone
Alternating Direction Method
Non-convexity
Support Vector Regression
multipliers
Cones
regression analysis
Switch
cones
switches
Switches
Numerical Results

Keywords

  • alternating direction method of multipliers
  • convex optimization
  • Electrical distribution system
  • network reconfiguration
  • optimal power flow
  • semidefinite relaxation programming
  • short-term load forecasting
  • support vector regression

ASJC Scopus subject areas

  • Control and Optimization
  • Computer Networks and Communications
  • Hardware and Architecture
  • Signal Processing
  • Biomedical Engineering
  • Instrumentation

Cite this

Gu, Y., Jiang, H., Zhang, J. J., Zhang, Y., Muljadi, E., & Solis, F. (2018). Load forecasting based distribution system network reconfiguration - A distributed data-driven approach. In M. B. Matthews (Ed.), Conference Record of 51st Asilomar Conference on Signals, Systems and Computers, ACSSC 2017 (Vol. 2017-October, pp. 1358-1362). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ACSSC.2017.8335576

Load forecasting based distribution system network reconfiguration - A distributed data-driven approach. / Gu, Yi; Jiang, Huaiguang; Zhang, Jun Jason; Zhang, Yingchen; Muljadi, Eduard; Solis, Francisco.

Conference Record of 51st Asilomar Conference on Signals, Systems and Computers, ACSSC 2017. ed. / Michael B. Matthews. Vol. 2017-October Institute of Electrical and Electronics Engineers Inc., 2018. p. 1358-1362.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Gu, Y, Jiang, H, Zhang, JJ, Zhang, Y, Muljadi, E & Solis, F 2018, Load forecasting based distribution system network reconfiguration - A distributed data-driven approach. in MB Matthews (ed.), Conference Record of 51st Asilomar Conference on Signals, Systems and Computers, ACSSC 2017. vol. 2017-October, Institute of Electrical and Electronics Engineers Inc., pp. 1358-1362, 51st Asilomar Conference on Signals, Systems and Computers, ACSSC 2017, Pacific Grove, United States, 10/29/17. https://doi.org/10.1109/ACSSC.2017.8335576
Gu Y, Jiang H, Zhang JJ, Zhang Y, Muljadi E, Solis F. Load forecasting based distribution system network reconfiguration - A distributed data-driven approach. In Matthews MB, editor, Conference Record of 51st Asilomar Conference on Signals, Systems and Computers, ACSSC 2017. Vol. 2017-October. Institute of Electrical and Electronics Engineers Inc. 2018. p. 1358-1362 https://doi.org/10.1109/ACSSC.2017.8335576
Gu, Yi ; Jiang, Huaiguang ; Zhang, Jun Jason ; Zhang, Yingchen ; Muljadi, Eduard ; Solis, Francisco. / Load forecasting based distribution system network reconfiguration - A distributed data-driven approach. Conference Record of 51st Asilomar Conference on Signals, Systems and Computers, ACSSC 2017. editor / Michael B. Matthews. Vol. 2017-October Institute of Electrical and Electronics Engineers Inc., 2018. pp. 1358-1362
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