Open AccessVoltage stability margin improvement using hybrid non‐linear programming and modified binary particle swarm optimisation algorithm considering optimal transmission line switching
Author(s) -
Nojavan Morteza,
Seyedi Heresh,
MohammadiIvatloo Behnam
Publication year - 2018
Publication title -
iet generation, transmission and distribution
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.92
H-Index - 110
eISSN - 1751-8695
pISSN - 1751-8687
DOI - 10.1049/iet-gtd.2016.1895
Subject(s) - particle swarm optimization , margin (machine learning) , voltage , transmission line , control theory (sociology) , electric power transmission , mathematical optimization , stability (learning theory) , transmission (telecommunications) , computer science , binary number , linear programming , algorithm , engineering , mathematics , control (management) , telecommunications , electrical engineering , artificial intelligence , arithmetic , machine learning
A new method is proposed for economic improvement of voltage stability margin. The preventive control facilities include demand response, active/reactive generation rescheduling and load shedding. Transmission line switching is also considered as a new solution for economic improvement of voltage stability margin. The best candidate transmission lines for switching action are selected using modified binary particle swarm optimisation algorithm and the voltage stability subproblem is formulated as non‐linear programming model. In order to verify effectiveness of the proposed method, comprehensive simulations are performed on the IEEE 118‐bus test system. The results indicate high efficiency of the proposed method in identifying the best lines and also decreasing the cost of voltage stability margin improvement. As a result, for the same voltage stability margin, the cost is decreased using optimal transmission line switching.