Skip to main content
SpringerLink
Log in

A novel brainstorm based optimization method for optimum planning of reactive power with FACTS devices

  • Original Article
  • Published:
International Journal of System Assurance Engineering and Management Aims and scope Submit manuscript

Abstract

This paper presents a solution for planning of reactive power using a novel brainstorm optimization method with flexible alternating current transmission system (FACTS) devices. For shunt compensation static VAR compensator (SVC) and for series compensation thyristor-controlled series compensator (TCSC) are being used in this proposed work which is adapted into IEEE-14, IEEE-30 and IEEE-57 test bus system. The location for TCSC and SVC has been chosen by performing power flow analysis. In this paper brainstorm optimization algorithm (BSOA) is proposed to evaluate the optimal value of reactive VAR generation of generators, tap setting of transformers, and size of SVC and TCSC to reduce the active power loss as well as operating cost in the transmission network. The outcomes proposed by BSOA approach is obtained and compared with some other techniques like krill heard algorithm (KHA), symbiotic organisms search (SOS), particle swarm optimization (PSO), biogeography-based optimization (BBO) methods.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9

Similar content being viewed by others

References

  • Babu R, Raj S, Bhattacharyya B (2020) Weak bus-constrained PMU placement for complete observability of a connected power network considering voltage stability indices. Protect Control Modern Power Syst 5(1):1–14

    Google Scholar 

  • Babu R et al (2021) "Modified branch‐and‐bound algorithm for unravelling optimal PMU placement problem for power grid observability: A comparative analysis. CAAI Trans Intell Technol

  • Badi M, Sheila M, Saurav R (2021) Hybrid BOA‐GWO‐PSO algorithm for mitigation of congestion by optimal reactive power management. Optimal Control Appl Methods

  • Bhattacharya A, Chattopadhyay PK (2011) Application of biogeography-based optimisation to solve different optimal power flow problems. IET Gener Transm Distrib 5(1):70–80

    Article  Google Scholar 

  • Bhattacharyya B, Karmakar N (2020) Optimal reactive power management problem: a solution using evolutionary algorithms. IETE Tech Rev. https://doi.org/10.1080/02564602.2019.1675541

    Article  Google Scholar 

  • Bhattacharyya B, Kumar S (2016a) Approach for the solution of transmission congestion with multi-type FACTS devices. IET Gener Transm Distrib 10(11):2802–2809

    Article  Google Scholar 

  • Bhattacharyya B, Kumar S (2016b) Loadability enhancement with FACTS devices using gravitational search algorithm. Electr Power Energy Syst 78:470–479

    Article  Google Scholar 

  • CERC (2012) Report on the grid disturbances on 30th July and 31st July 2012, CERC Order in Petition No. 167/Suo- Motu/2012, pp 1–129

  • Dash SP, Subhashini KR, Satapathy JK (2019) Optimal location and parametric settings of FACTS devices based on JAYA blended moth flame optimization for transmission loss minimization in power systems. Microsyst Technol 25:1–10

    Google Scholar 

  • Dash S, Subhashini K, Satapathy J (2020) Efficient utilization of power system network through optimal location of FACTS devices using a proposed hybrid meta-heuristic Ant Lion-Moth Flame-Salp Swarm optimization algorithm. Int Trans Elect Energy Syst 30(4):e12402. https://doi.org/10.1002/2050-7038.12402

    Article  Google Scholar 

  • De M, Goswami SK (2014) Optimal reactive power procurement with voltage stability consideration in deregulated power system. IEEE Trans Power Syst 29(5):2078–2086

    Article  Google Scholar 

  • Dey B et al (2020) Economic emission dispatch on unit commitment-based microgrid system considering wind and load uncertainty using hybrid MGWOSCACSA. J Elect Syst Inf Technol 7(1):1–26

    Google Scholar 

  • Dey B et al (2022) Optimal scheduling of distributed energy resources in microgrid systems based on electricity market pricing strategies by a novel hybrid optimization technique. Int J Elect Power Energy Syst. 134:107419

    Article  Google Scholar 

  • El-Araby EE, Yorino N (2018) Reactive power reserve management tool for voltage stability enhancement. IET Gener Trans Distrib 12(8):1879–1888

    Article  Google Scholar 

  • Gandomi AH, Alavi AH (2012) Krill heard: A new bioinspired optimization algorithm. Commun Nonlinear Sci Numer Simul 17(12):4831–4845

    Article  MathSciNet  MATH  Google Scholar 

  • Gudadappanavar SS and Sheila M (2021) Metaheuristic nature-based algorithm for optimal reactive power planning. Int J Syst Assur Eng Manag 1–14

  • Jordehi AR (2015) Brainstorm optimization algorithm (BSOA): an efficient algorithm for finding optimal location and setting of FACTS devices in electric power systems. Int J Electr Power Energy Syst 69:48–57

    Article  Google Scholar 

  • Kanagasabai L (2021) Real power loss reduction by enhanced Apple Maggot optimization algorithm. Int J Syst Assur Eng Manag 12:1385–1396

    Article  Google Scholar 

  • Kennedy J, Eberhart R (1995) Particle swarm optimization, In: Proceedings of ICNN'95 - international conference on neural networks, Perth, WA, Australia, vol 4, pp 1942–1948

  • Kumar L, Kar MK, Kumar S (2022) Reactive power management of transmission network using evolutionary techniques. J Elect Eng Technol. https://doi.org/10.1007/s42835-022-01185-1

    Article  Google Scholar 

  • Li Y, Li X, Li Z (2017) Reactive power optimization using hybrid CABC-DE algorithm. Electr Power Compon Syst 45(9):980–9

    Article  Google Scholar 

  • Mahapatra S, Dey B, Raj S (2021) A novel ameliorated Harris hawk optimizer for solving complex engineering optimization problems. Int J Intell Syst 36(12):7641–7681

    Article  Google Scholar 

  • Moger T, Dhadbanjan T (2015) A novel index for identification of weak nodes for reactive compensation to improve voltage stability. IET Gener Transm Distribution 9:1826–1834

    Article  Google Scholar 

  • Mondal D, Chakrabarti A, Sengupta A (2012) Optimal placement and parameter setting of SVC and TCSC using PSO to mitigate small signal stability problem. Int J Elec Power 42:334–340

    Article  Google Scholar 

  • Prasad D, Mukherjee V (2018) Solution of optimal reactive power dispatch by symbiotic organism search algorithm incorporating FACTS devices. IETE J Res 64(1):149–160

    Article  Google Scholar 

  • Raj S, Bhattacharyya B (2018) Reactive power planning by opposition-based grey wolf optimization method. Int Trans Electr Energy Syst 28(6):1–29

    Article  Google Scholar 

  • Raj S, Bhattacharyya B (2018a) Optimal placement of TCSCand SVC for reactive power planning using Whale optimization algorithm. Swarm Evol Comput 40:131–143

    Article  Google Scholar 

  • Raj S, Bhattacharyya B (2018b) Optimal placement of TCSC and SVC for reactive power planning using Whale optimization algorithm. Swarm Evol Comput 40:131–143

    Article  Google Scholar 

  • Roy PK, Chandan P (2015) Optimal power flow using krill herd algorithm. Int Trans Elect Energy Syst 25(8):1397–1419

    Article  Google Scholar 

  • Roy PK, Ghoshal SP, Thakur SS (2011) Optimal reactive power dispatch considering flexible AC transmission system devices using biogeography-based optimization. Elect Power Comp Syst 39(8):733–750. https://doi.org/10.1080/15325008.2010.541410

    Article  Google Scholar 

  • Shaikh MS et al (2021) Optimal parameter estimation of overhead transmission line considering different bundle conductors with the uncertainty of load modeling. Opt Control Appl Methods

  • Sharma A, Jain SK (2019) Gravitational search assisted algorithm for TCSC placement for congestion control in deregulated power system, Elect Power Syst Res, 174

  • Shekarappa G, Swetha SM, Saurav R (2021) Voltage constrained reactive power planning problem for reactive loading variation using hybrid harris hawk particle swarm optimizer. Elect Power Comp Syst 49(4–5):421–435

    Article  Google Scholar 

  • Shi Y (2011) An optimization algorithm based on brainstorming process. Int J Swarm Intelligence Res (IJSIR) 2:35–62

    Article  Google Scholar 

  • Simon D (2008) Biogeography-based optimization. IEEE Trans Evol Comput 12:702–713

    Article  Google Scholar 

  • Thukaram BD, Parthasarathy K (1996) Optimal reactive power dispatch algorithm for voltage stability improvement. Electr Power Energy Syst 18:461–468

    Article  Google Scholar 

Download references

Funding

No funding was received.

Author information

Authors and Affiliations

  1. Electrical Engineering Department, NIT Jamshedpur, Jamshedpur, India

    Lalit Kumar, Sushil Kumar Gupta & Sanjay Kumar

Authors
  1. Lalit Kumar
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Sushil Kumar Gupta
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Sanjay Kumar
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Lalit Kumar.

Ethics declarations

Conflict of interest

Authors doesn’t have any conflict of interest.

Human and animals participants

Human Participants and/or Animals are not involved in this research.

Informed consent

There was no informed consent in this research article.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Appendix

Appendix

See Table

Table 9 Description of test bus systems
Full size table

9.

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Kumar, L., Gupta, S.K. & Kumar, S. A novel brainstorm based optimization method for optimum planning of reactive power with FACTS devices. Int J Syst Assur Eng Manag 13, 3062–3073 (2022). https://doi.org/10.1007/s13198-022-01802-2

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s13198-022-01802-2

Keywords

Search

Navigation