FACTS placement for reactive power planning with weak node constraints using an improved symbiotic search algorithm


  • Vikash Kumar Gupta Department of Applied Sciences and Humanities, National Institute of Advanced Manufacturing Technology, Hatia, Ranchi, India.
  • Sudhansu Kumar Mishra Department of Electrical and Electronics Engineering, Birla Institute of Technology, Mesra, Ranchi, India
  • Rohit Babu Alliance University, Anekal, Bengaluru https://orcid.org/0000-0003-4128-4428




Optimal power flow, Energy Loss, Operating Cost, FACTS, ISOS


In this paper, an economically feasible and reliable operation of the IEEE 57 bus system for Optimal Power Flow (OPF) is proposed. The Improved Symbiotic Organisms Search (ISOS) algorithm is proposed for effective reactive power planning as an OPF issue. Further, the optimal position of Flexible AC Transmission Systems (FACTS) is taken into consideration, by including the existing system controlling variables like reactive power generators output, transformer tapping and capacitors connected at shunt. The objective of the work is two-fold; i.e., to reduce the energy loss and to enhance the voltage profile within the prescribed limit by ensuring the economic operation and investment cost of FACTS in the system. In this work, two FACTS devices like Static Var Compensator (SVC) and Thyristor-Controlled Series Controller (TCSC) have been taken into consideration. Voltage sensitivity indicator and reactive power flow are two tools that are utilised in order to locate weak nodes for the implementation of FACTS. Finally, the performance of the ISOS algorithm is compared with that of three other state- of-the -art optimization techniques, such as, Symbiotic Organisms Search (SOS), Differential Evolution (DE) and Teaching Learning Based Optimization (TLBO). A Non-parametric statistical analysis is also performed to investigate the dominance of the ISOS algorithm over others.


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How to Cite

Gupta, V. K., Mishra, S. K., & Babu, R. (2023). FACTS placement for reactive power planning with weak node constraints using an improved symbiotic search algorithm. Transactions on Energy Systems and Engineering Applications, 4(2), 1–18. https://doi.org/10.32397/tesea.vol4.n2.524