Coordination of multi‐type FACTS for available transfer capability enhancement using PI–PSO

To relieve congestion due to open-access feature in competitive power system framework, utilities plan flexible alternating current transmission systems (FACTS), ensuring improved utilization and performance of the transmission infrastructure. However, high-investment cost restricts implementation to single type of FACTS' planning in a time. Therefore, successive planning of another FACTS to delay transmission expansion results in multi-type FACTS planning. Consequently, to optimise performance, subsequent planning must coordinate with existing FACTS. The main objective of this study is to implement coordination of multi-type FACTS for available transfer capability (ATC) enhancement. A hybrid real power flow performance index (PI) and particle swarm optimisation (PSO), coordinate thyristor control series compensator (TCSC) in the first planning horizon with static synchronous series compensator (SSSC) and unified power flow controller (UPFC), in the second horizon. The PI–PSO-based multi-type FACTS coordination improves ATC of multilateral power transfers in a standard 9-buses test network. Results show that multi-type FACTS achieved higher ATC; such that enhanced ATC by TCSC–SSSC ranges between 8.06–69.34% while the TCSC–UPFC ranges between 11.85–71.59% for various power transfer transactions. A comparison of the three coordination schemes shows that the scheme with more decision parameters provides superior loadability and transfer capability improvement.

[1]  Muhammad Buhari,et al.  Available transfer capability enhancement with FACTS using hybrid PI-PSO , 2019, Turkish J. Electr. Eng. Comput. Sci..

[2]  Muhammad Murtadha Othman,et al.  Determination of available transfer capability with implication of cascading collapse uncertainty , 2014 .

[3]  Ghadir Radman,et al.  Power flow model/calculation for power systems with multiple FACTS controllers , 2007 .

[4]  Seema Singh,et al.  Dynamic available transfer capability computation using a hybrid approach , 2008 .

[5]  J. G. Jamnani,et al.  Coordination of SVC and TCSC for Management of Power Flow by Particle Swarm Optimization , 2019, Energy Procedia.

[6]  Annamária R. Várkonyi-Kóczy,et al.  Intelligent road inspection with advanced machine learning; Hybrid prediction models for smart mobility and transportation maintenance systems , 2020 .

[7]  Salah Kamel,et al.  Constraints violation handling of SSSC with multi‐control modes in Newton–Raphson load flow algorithm , 2017 .

[8]  M. Balasubbareddya,et al.  A non-dominated Sorting Hybrid Cuckoo Search Algorithm for multi-objective optimization in the presence of FACTS devices , 2017 .

[9]  T. T. Lie,et al.  Design and application of co-ordinated multiple FACTS controllers , 2000 .

[10]  Xiaobo Dou,et al.  An improved CPF for static stability analysis of distribution systems with high DG penetration , 2017 .

[11]  Salah Kamel,et al.  Comparison of various UPFC models for power flow control , 2015 .

[12]  V. Srinivasa Rao,et al.  A generalized approach for determination of optimal location and performance analysis of FACTs devices , 2015 .

[13]  T. Nireekshana,et al.  Available transfer capability enhancement with FACTS using Cat Swarm Optimization , 2016 .

[14]  Canbing LI,et al.  Optimal allocation of multi-type FACTS devices in power systems based on power flow entropy , 2014 .

[15]  A. Elmitwally,et al.  Planning of multi-type FACTS devices in restructured power systems with wind generation , 2016 .

[16]  Max Mulder,et al.  Ecological Interface for Collaboration of Multiple UAVs in Remote Areas , 2016 .

[17]  R. Ramanujam,et al.  Effect of iron core loss nonlinearity on chaotic ferroresonance in power transformers , 2003 .

[18]  Innocent Kamwa,et al.  Optimal placement of multiple-type FACTS devices to maximize power system loadability using a generic graphical user interface , 2013, IEEE Transactions on Power Systems.

[19]  Tao Jiang,et al.  Available Transfer Capability Evaluation in a Deregulated Electricity Market Considering Correlated Wind Power , 2018 .

[20]  R D Zimmerman,et al.  MATPOWER: Steady-State Operations, Planning, and Analysis Tools for Power Systems Research and Education , 2011, IEEE Transactions on Power Systems.

[21]  Mohamed Shaaban,et al.  Risk-based available transfer capability assessment including nondispatchable wind generation , 2015 .

[22]  P. Venkatesh,et al.  Optimal Setting of FACTS Devices using Particle Swarm Optimization for ATC Enhancement in Deregulated Power System , 2016 .