An Optimal Phase Arrangement of Distribution Transformers under Risk Assessment

Chia-Sheng Tu, Chung-Yuen Yang and Ming-Tang Tsai
Additional contact information
Chia-Sheng Tu: College of Intelligence Robot, Fuzhou Polytechnic, Fuzhou 350108, China
Chung-Yuen Yang: Department of Electrical Engineering, Cheng-Shiu University, Kaohsiung 833, Taiwan
Ming-Tang Tsai: Department of Electrical Engineering, Cheng-Shiu University, Kaohsiung 833, Taiwan

Energies, 2020, vol. 13, issue 21, 1-16

Abstract: This paper presents a phase arrangement procedure for distribution transformers to improve system unbalance and voltage profile of distribution systems, while considering the location and uncertainties of the wind turbine (WT) and photovoltaics (PV). Based on historical data, the Monte Carlo method is used to calculate the power generation value-at-risk (VAR) of WTs/PVs installed under a given level of confidence. The main target of this paper is to reduce the line loss and unbalance factor during 24-hour intervals. Assessing the various confidence levels of risk, a feasible particle swarm optimization (FPSO) is proposed to solve the optimal location of WTs/PVs installed and transformer load arrangement. A three-phase power flow with equivalent current injection (ECI) is analyzed to demonstrate the operating efficiency of the FPSO in a Taipower feeder. Simulation results will support the planner in the proper location of WTs/PVs installed to reduce system losses and maintain the voltage profile. They can also provide more risk information for handing uncertainties when the renewable energy is connected to the distribution system.

Keywords: distribution transformer; value-at-risk; particle swarm optimization; Monte Carlo method (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://www.mdpi.com/1996-1073/13/21/5852/pdf (application/pdf)
https://www.mdpi.com/1996-1073/13/21/5852/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jeners:v:13:y:2020:i:21:p:5852-:d:442275

Access Statistics for this article

Energies is currently edited by Ms. Agatha Cao

More articles in Energies from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().