Open AccessImproving voltage profile and reducing power losses based on reconfiguration and optimal placement of UPQC in the network by considering system reliability indices
Author(s) -
Dashtdar Masoud,
Bajaj Mohit,
Hosseinimoghadam Seyed Mohammad Sadegh,
Sami Irfan,
Choudhury Subhashree,
Rehman Ateeq Ur,
Goud B. Srikanth
Publication year - 2021
Publication title -
international transactions on electrical energy systems
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.428
H-Index - 42
ISSN - 2050-7038
DOI - 10.1002/2050-7038.13120
Subject(s) - control reconfiguration , voltage sag , genetic algorithm , reliability (semiconductor) , matlab , voltage , control theory (sociology) , engineering , reduction (mathematics) , power (physics) , computer science , reliability engineering , electronic engineering , mathematical optimization , power quality , mathematics , control (management) , embedded system , electrical engineering , physics , quantum mechanics , artificial intelligence , geometry , operating system
Summary Distribution networks have problems such as an increase in active losses, overload on distribution substations, voltage drop, decrease in network reliability, increase in load unbalance and unbalance in line current due to variable characteristics in terms of load consumption. In this article, to reduce losses, improve the voltage profile and increase the reliability of the system, the UPQC (Unified Power Quality Controller) optimal placement and reconfiguration method have been used in the distribution network. The two objective functions of losses and the mean voltage deviation are defined by considering the reliability indices. Since the reconfiguration of distribution networks is a large‐scale nonlinear hybrid optimization problem with several constraints, the genetic algorithm combines genes including key numbers and UPQC location, UPQC series power size, UPQC shunt power size used to solve the problem. The proposed method is implemented in three steps on IEEE 33‐bus and 69‐bus standard networks by considering the load model by genetic algorithm (GA). In the first stage, without considering the UPQC in the network, it only deals with the reconfiguration of the distribution network; at the second stage, without considering the network reconfiguration, only the appropriate UPQC placement is considered and in the final stage, the network reconfiguration and UPQC placement in these two networks are examined simultaneously. In this study, all simulations were performed with MATLAB software, and finally, reviewing and comparing the obtained results according to the solution method and the intended objective functions showed the proper performance of the proposed method compared to other methods.