TY - JOUR
T1 - Distribution network reliability enhancement and power loss reduction by optimal network reconfiguration
AU - Anteneh, Degarege
AU - Khan, Baseem
AU - Mahela, Om Prakash
AU - Alhelou, Hassan Haes
AU - Guerrero, Josep M.
N1 - Funding Information:
This work was supported by VILLUM FONDEN, Center for Research on Microgrids, Aalborg University, Denmark.
Publisher Copyright:
© 2021 Elsevier Ltd
PY - 2021/12
Y1 - 2021/12
N2 - Voltage instability, power imbalance, and unreliability are all caused by power interruptions and losses in the distribution system. The optimal reconfiguration of the distribution network is offered in this research as a solution to such challenges. The investigation is carried out using an actual distribution system in Kombolcha, Ethiopia. Modified shark smell optimization (MSSO) is used in the MATLAB environment to improve system reliability and voltage profile with low power loss. Tie switches are optimally placed to reduce power losses, total cost of outages, and reliability indices such as the system average interruption frequency index (SAIFI), system average interruption duration index (SAIDI), and expected energy not supply (EENS) all at the same time. The MSSO's effectiveness is demonstrated through a comparison with other approaches. Furthermore, a real-time digital simulator is used to implement the suggested task in real time with allowable mistakes in the results (RTDS).
AB - Voltage instability, power imbalance, and unreliability are all caused by power interruptions and losses in the distribution system. The optimal reconfiguration of the distribution network is offered in this research as a solution to such challenges. The investigation is carried out using an actual distribution system in Kombolcha, Ethiopia. Modified shark smell optimization (MSSO) is used in the MATLAB environment to improve system reliability and voltage profile with low power loss. Tie switches are optimally placed to reduce power losses, total cost of outages, and reliability indices such as the system average interruption frequency index (SAIFI), system average interruption duration index (SAIDI), and expected energy not supply (EENS) all at the same time. The MSSO's effectiveness is demonstrated through a comparison with other approaches. Furthermore, a real-time digital simulator is used to implement the suggested task in real time with allowable mistakes in the results (RTDS).
KW - Modified shark smell optimization
KW - Optimal reconfiguration
KW - Power loss reduction
KW - Real time digital simulator
UR - http://www.scopus.com/inward/record.url?scp=85117074141&partnerID=8YFLogxK
U2 - 10.1016/j.compeleceng.2021.107518
DO - 10.1016/j.compeleceng.2021.107518
M3 - Article
AN - SCOPUS:85117074141
SN - 0045-7906
VL - 96
JO - Computers and Electrical Engineering
JF - Computers and Electrical Engineering
IS - Part A
M1 - 107518
ER -