Power Research

Open Access Open Access  Restricted Access Subscription Access
Open Access Open Access Open Access  Restricted Access Restricted Access Subscription Access

Transmission Network Expansion Planning–A Critical Review


Affiliations
1 Electrical Engineering Department, Government College of Engineering, Amravati – 444 604, Maharashtra, India
2 Electrical Engineering Department, Government College of Engineering, Chandrapur – 442 403, Maharashtra, India
3 Electrical Engineering Department, Government College of Engineering, Pune, Maharashtra, India
     

   Subscribe/Renew Journal


Transmission Network Expansion Planning (TNEP) is determination of an optimal network configuration that satisfies the operational conditions for forecasted load growth under a particular generation expansion plan. TNEP may be broadly classified into static and dynamic network planning. Static TNEP (STNEP) deals with finding where and which type of new lines should be installed in an optimal way that minimizes the installation and operational cost. Dynamic TNEP (DTNEP) is more complex and aims at determining when to install the new lines (in addition to determination of where and which type of lines to be installed). Researchers have used mathematical optimization methods, heuristic methods and meta-heuristic methods to solve STNEP problem. DTNEP problem have been tackled using mathematical optimization methods and meta-heuristic methods by the researchers. This paper compiles the significant developments made in the area of TNEP using conventional (mathematical) optimization methods, and advanced (heuristic & meta-heuristic) optimization methods. After a thorough study of vast literature available on TNEP, critical comments and future scope have been presented to make the review study focused and useful for the researchers in this area.

Keywords

Dynamic Planning, Heuristic Methods, Mathematical Optimization Methods, Meta-Heuristic Methods, Static Planning, Transmission Network Expansion Planning.
User
Subscription Login to verify subscription
Notifications
Font Size

  • Lai LL. Intelligent system applications in power engineering. John Wiley & Sons, West Sussex; 1998.

  • Wang X, McDonald JR. Modern power system planning. McGraw Hill, New York; 1994.

  • Seifi H, Sepasian MS. Electric power system planning: Issues. Algorithms and Solutions. Springer-Verlag Berlin Heidelberg; 2011. https://doi.org/10.1007/978-3-64217989-1

  • Lee KY, Mohd. A E–S. Modern heuristic optimization techniques - Theory and applications to power systems. IEEE Press Series on Power Engineering, John Wiley & Sons, Inc., New Jersey. 2008. https://doi.org/10.1002/9780470225868

  • Panigrahi BK, Abraham A, Das S. Computational intelligence in power engineering. Vol. 302, Springer; 2010. https://doi.org/10.1007/978-3-642-14013-6

  • Kritsana T. Development of an efficient calculation method based on evolutionary programming for optimal power flow considering transient and voltage stabilities, Ph. D dissertation, Graduate School of Engineering, Tokyo, December; 2009.

  • Telang AS, Bedekar PP. Voltage stability constrained optimum power flow - A critical review. The Journal of CPRI. 2016 Jun; 12(2):201–18.

  • Garver LL. Transmission network estimation using linear programming. IEEE Transactions on PAS. 1970; 89(7):1688–97. https://doi.org/10.1109/TPAS.1970.292825

  • Rathore C, Roy R, Sharma U, Patel J. Artificial bee colony algorithm based static transmission expansion planning. IEEE Procedure of International Conference on Energy Efficient Technologies for Sustainability; 2013 April. p. 1126–31. https://doi.org/10.1109/ICEETS.2013.6533544

  • Khardenvis MD, Tembhere SB, Pande VN. Artificial Bee Colony (ABC) algorithm based transmission expansion planning with security constraints. Power Research - A Journal of CPRI. 2018 Jun; 14(1):27–36. https://doi.org/10.33686/pwj.v14i1.142182

  • Verma A. Transmission network expansion planning. Ph. D thesis, Indian Institute of Technology Delhi, December; 2009.

  • Dusonchet YP, El-Abiad AH. Transmission planning using discrete dynamic optimization. IEEE Transactions on PAS. 1973; 92(4):1358–71. https://doi.org/10.1109/TPAS.1973.293543

  • Romero R, Monticelli A. A hierarchical decomposition approach for transmission network expansion planning. IEEE Transactions on Power System. 1994; 9(1):373–80. https://doi.org/10.1109/59.317588

  • Kim KJ, Park YM, Lee KY. Optimal long term transmission expansion planning based on maximum principle. IEEE Transactions on Power System. 1988; 3(4):1494–501. https://doi.org/10.1109/59.317588

  • Villasana R, Garver LL, Salon SJ. Transmission network planning using linear programming. IEEE Transactions on PAS. 1985; 104(2):349–56. https://doi.org/10.1109/TPAS.1985.319049

  • Hashimoto SHM, Romero R, Montovani JRS. Efficient linear programming algorithm for the transmission network expansion planning problem. IET Generation, Transmission & Distribution. 2003; 150(5):536–42. https:// doi.org/10.1049/ip-gtd:20030656

  • Al-Hamouz ZM, Al-Faraz AS. Transmission expansion planning based on a non-linear programming algorithm. Applied Energy.2003; 76:169–177. https://doi.org/10.1016/S0306-2619(03)00060-6

  • Youssef HK, Ackam R. New transmission planning model. IEEE Transactions on Power System. 1989; 4(2):9–18. https://doi.org/10.1109/59.32451

  • Oliveira GC, Costa APC, Binato S. Large scale transmission network planning using optimization and heuristic techniques. IEEE Transactions on Power System. 1995; 10(4):1828–34. https://doi.org/10.1109/59.476047

  • Binato S, Pereira MVF, Granville S. A new benders decomposition approach to solve power Transmission network design problems. IEEE Transactions on Power System. 2001; 16(2):235–40. https://doi.org/10.1109/59.918292

  • Haffner S, Monticelli A, Garcia A, Mantovani J, Romero R. Branch and bound algorithm for transmission system expansion planning using a transportation model. IET Generation, Transmission & Distribution. 2000; 147(3):149–56. https://doi.org/10.1049/ip-gtd:20000337

  • Haffner S, Monticelli A, Garcia A, Romero R. Specialised branch-and-bound algorithm for transmission network expansion planning using a transportation model. IET Generation, Transmission & Distribution. 2001; 148(5):482–88. https://doi.org/10.1049/ip-gtd:20010502

  • Choi J, El-Keib A, Tran T. A fuzzy branch-and-bound based transmission system expansion planning for the highest satisfaction level of the decision maker. IEEE Transactions on Power System. 2005; 20(1):476–84. https://doi.org/10.1109/TPWRS.2004.840446

  • Sharifnia A, Aashtiani HZ. Transmission network planning: A method for synthesis of minimum cost secure networks. IEEE Transactions on Power Apparatus and Systems. 1985; 104(8):2026—34. https://doi.org/10.1109/TPAS.1985.318777

  • Levi VA. A new mixed-integer methodology for optimal transmission expansion planning. Electric Power System Research. 1995; 32:227–38. https://doi.org/10.1016/0378-7796(94)00919-U

  • Bahiense L, Oliveira GC, Pereira M, Granville S. A mixed integer disjunctive model for transmission network expansion. IEEE Transactions on Power System. 2001; 16(3):560–65. https://doi.org/10.1109/59.932295

  • Alguacil N, Motto AL, Conejo AJ. Transmission expansion planning: A mixed -integer LP approach. IEEE Transactions on Power System. 2003; 18(3):1070–7. https:// doi.org/10.1109/TPWRS.2003.814891

  • Torre S, Conejo A, Contreras J. Transmission expansion planning in electricity markets. IEEE Transactions on Power System. 2008; 23(1):238–48. https://doi.org/10.1109/TPWRS.2007.913717

  • Sanchez IG, Romero R, Montavani JRS, Rider M. Transmission expansion planning using the DC model and nonlinear-programming technique. IET Generation, Transmission & Distribution. 2005; 1452(6):763–9. https://doi.org/10.1049/ip-gtd:20050074

  • Sarhadi S, Amraee T. Robust dynamic network expansion planning considering load uncertainty. Electric Power System Research. 2015; 71:140–50. https://doi.org/10.1016/j.ijepes.2015.02.043

  • Romero R, Rocha C, Montovani JRS. and Sanchez IG. Constructive Heuristic Algorithm for the DC model in network transmission expansion planning. IET Generation, Transmission & Distribution. 2005; 152(2):277–82. https:// doi.org/10.1049/ip-gtd:20041196

  • Bustamante-Cedeno E, Arora S. Multi-step simultaneous changes constructive Heuristic Algorithm for transmission network expansion planning. Electric Power System Research. 2009; 79:586–94. https://doi.org/10.1016/j.epsr.2008.08.011

  • Romero R, Rider MJ, Silva I. A metaheuristic to solve the transmission expansion planning. IEEE Transactions on Power System. 2007; 22(4):2289–91. https://doi.org/10.1109/TPWRS.2007.907592

  • Maghouli P, Hosseini SH, Buygi MO, Shahidehpour M. A multi-objective framework for transmission expansion planning in deregulated environments. IEEE Transactions on Power System. 2009; 24(2):1051–61. https://doi.org/10.1109/TPWRS.2009.2016499

  • DA Silva EL, Gil HA, Areiza JM. Transmission network expansion planning under improved genetic algorithm. IEEE Transactions on Power System. 2007; 15(3):1168–75. https://doi.org/10.1109/59.871750

  • Escobar AH, Gallego RA, Romero R. Multistage and Coordinated Planning of the Expansion of Transmission System, IEEE Transactions on Power System, Vol. 19, No. 2, 2004, pp. 735-744 https://doi.org/10.1109/TPWRS.2004.825920

  • Huang S, Dinavahi V. Multi-group Particle Swarm Optimization for transmission expansion planning solution based on LU decomposition. IET Generation, Transmission & Distribution. 2017; 11(6):1434–42. https:// doi.org/10.1049/iet-gtd.2016.0923

  • Kamyab GR, Fotuhi-Firozabad M, Rashidinezad M. A PSO based approach for multi-stage transmission expansion planning in electricity market. Electrical Power and Energy Systems. 2014; 54:91–100. https://doi.org/10.1016/j.ijepes.2013.06.027

  • Jin Y, Cheng H, Yan J, Zhang L. New discrete method for Particle Swarm Optimization and its application in transmission network expansion planning. Electric Power System Research. 2007; 77:227–33. https://doi.org/10.1016/j.epsr.2006.02.016

  • Verma A, Panigrahi BK, Bijwe PR. Harmony search algorithm for transmission network expansion planning. IET Generation, Transmission & Distribution. 2010; 4(6):663– 73. https://doi.org/10.1049/iet-gtd.2009.0611

  • Rastgou A, Moshtagh J. Improved harmony search algorithm for transmission expansion planning with adequacy-security considerations in the deregulated power systems. Electrical Power and Energy Systems. 2014; 60:153–64. https://doi.org/10.1016/j.ijepes.2014.02.036

  • Shivaie M, Ameli M. An implementation of improved harmony search algorithm for scenario-based transmission expansion planning. Soft Computing. 2013; 18:1615–30. https://doi.org/10.1007/s00500-013-1167-7

  • Romero R, Gallego RA, Monticelli A. Transmission network expansion planning by simulated annealing. IEEE Transactions on Power System. 1990; 11(1):364–9. https:// doi.org/10.1109/59.486119

  • Gallego RA, Alves AB, Monticelli A, Romero R. Parallel simulated annealing approach applied to long term transmission network expansion planning. IEEE Transactions on Power System. 1997; 12(1):181–8. https://doi.org/10.1109/59.574938

  • Gallego RA, Romero R, Monticelli AJ. Tabu search algorithm for network synthesis. IEEE Transactions on Power System. 2000; 15(2):490–5. https://doi.org/10.1109/59.867130

  • Silva EL, Ortiz JMA, Oliveira GC, Binato S. Transmission network expansion planning under a Tabu Search approach. IEEE Transactions on Power System. 2001; 16(1):62–8. https://doi.org/10.1109/59.910782

  • Binato S, Oliveira GC, Araujo JL. A greedy ramdomized adaptive search procedure for transmission expansion planning. IEEE Transactions on Power System. 2001; 16(2):247–53. https://doi.org/10.1109/59.918294

  • Silva AML, Rezende L, Manso LAF, Recende LC. Reliability worth applied to transmission expansion planning based on ant colony system. Electrical Power and Energy Systems. 2010; 32:1077–84. https://doi.org/10.1016/j.ijepes.2010.06.003

  • Sum-lm T, Taylor GA, Irving MR, Song YH. Differential evolution algorithm for static and multistage transmission expansion planning. IET Generation, Transmission & Distribution. 2009; 3(4):365–84. https://doi.org/10.1049/iet-gtd.2008.0446

  • Georgilakis PS. Market-based transmission expansion planning by improved differential evolution. Electrical Power and Energy Systems. 2010; 32:450–6. https://doi.org/10.1016/j.ijepes.2009.09.019

  • Alhamrouni I, Ferdavani A, Salem M, Khairuddin A. Transmission expansion planning using AC-based differential evolution algorithm. IET Generation, Transmission & Distribution. 2014; 8(10):1637–44. https://doi.org/10.1049/iet-gtd.2014.0001


Abstract Views: 251

PDF Views: 0




  • Transmission Network Expansion Planning–A Critical Review

Abstract Views: 251  |  PDF Views: 0

Authors

Manisha Dinkar Khardenvis
Electrical Engineering Department, Government College of Engineering, Amravati – 444 604, Maharashtra, India
Prashant Prabhakar Bedekar
Electrical Engineering Department, Government College of Engineering, Chandrapur – 442 403, Maharashtra, India
Vijay Narhar Pande
Electrical Engineering Department, Government College of Engineering, Pune, Maharashtra, India

Abstract


Transmission Network Expansion Planning (TNEP) is determination of an optimal network configuration that satisfies the operational conditions for forecasted load growth under a particular generation expansion plan. TNEP may be broadly classified into static and dynamic network planning. Static TNEP (STNEP) deals with finding where and which type of new lines should be installed in an optimal way that minimizes the installation and operational cost. Dynamic TNEP (DTNEP) is more complex and aims at determining when to install the new lines (in addition to determination of where and which type of lines to be installed). Researchers have used mathematical optimization methods, heuristic methods and meta-heuristic methods to solve STNEP problem. DTNEP problem have been tackled using mathematical optimization methods and meta-heuristic methods by the researchers. This paper compiles the significant developments made in the area of TNEP using conventional (mathematical) optimization methods, and advanced (heuristic & meta-heuristic) optimization methods. After a thorough study of vast literature available on TNEP, critical comments and future scope have been presented to make the review study focused and useful for the researchers in this area.

Keywords


Dynamic Planning, Heuristic Methods, Mathematical Optimization Methods, Meta-Heuristic Methods, Static Planning, Transmission Network Expansion Planning.

References





DOI: https://doi.org/10.33686/pwj.v15i1.144003