Skip to main content
SpringerLink
Log in

A Survey on Modeling Approaches for Generation and Transmission Expansion Planning Analysis

  • Conference paper
  • First Online:
Numerical Analysis and Optimization (NAO 2020)

Part of the book series: Springer Proceedings in Mathematics & Statistics ((PROMS,volume 354))

Included in the following conference series:

  • 700 Accesses

Abstract

Generation and transmission expansion planning (GTEP) models determine the evolution of power systems over a long-term planning horizon, by defining technology, capacity and location of new generating units, as well as new electrical interconnections to be built. The models required to plan investment decisions in the power sector are typically large-scale models, since many variables and constraints are needed to represent a great number of strategic and operating decisions: to compute a solution to GTEP models different approximations have to be introduced. This paper provides a comprehensive description of the GTEP analysis, by highlighting the characteristics and the challenges of this problem and by reviewing the main approaches proposed in the literature to answer to specific research questions. This paper provides also a formulation of the GTEP problem suited to address decarbonization challenges in the power sector.

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

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 84.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Hardcover Book
USD 109.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. D. Huppmann and R. Egging-Bratseth, “Market power, fuel substitution and infrastructure – A large-scale equilibrium model of global energy markets,” Energy, vol. 75, no. C, pp. 483–500, 2014.

    Google Scholar 

  2. P. Seljom and A. Tomasgard, “Short-term uncertainty in long-term energy system models – A case study of wind power in Denmark,” Energy Economics, vol. 49, pp. 157–167, 2015.

    Article  Google Scholar 

  3. L. Garver, “Transmission network estimation using linear programming,” IEEE Transactions on Power Apparatus and Systems, vol. 89, no. 7, pp. 1686–1697, 1970.

    Google Scholar 

  4. Y. Gu, J. McCalley, and M. Ni, “Coordinating large-scale wind integration and transmission planning,” IEEE Transactions on Sustainable Energy, vol. 3, no. 4, pp. 652–659, 2011.

    Article  Google Scholar 

  5. H. Haghighat and B. Zneg, “Bilevel conic transmission expansion planning,” IIEEE Transactions on Power Systems, vol. 33, no. 4, pp. 4640–4642, 2018.

    Article  Google Scholar 

  6. R. Hemmati, H. Saboori, and M. Jirdehi, “Multistage generation expansion planning incorporating large scale energy storage systems and environmental pollution,” Renewable Energy, vol. 97, pp. 636–645, 2016.

    Article  Google Scholar 

  7. J. Meza, M. Yildirim, and A. Masud, “A model for the multiperiod multiobjective power generation expansion problem,” IEEE Transactions on Power Systems, vol. 22, no. 2, pp. 871–878, 2007.

    Article  Google Scholar 

  8. S. Kazempour, A. Conejo, and C. Ruiz, “Strategic generation investment using a complementarity approach,” IEEE Transactions on Power Systems, vol. 26, no. 2, pp. 940–948, 2011.

    Article  Google Scholar 

  9. V. Krishnan, J. Ho, B. Hobbs, A. Liu, J. McCalley, M. Shahidehpour, and Q. Zheng, “Co-optimization of electricity transmission and generation resources for planning and policy analysis: review of concepts and modeling approaches,” Energy Systems, vol. 7, no. 2, pp. 297–332, 2016.

    Article  Google Scholar 

  10. D. Pozo, E. Sauma, and J. Contreras, “A three-level static MILP model for generation and transmission expansion planning,” IEEE Transactions on Power Systems, vol. 28, pp. 201–210, 2013.

    Article  Google Scholar 

  11. Y. Tohidi, M. Hesamzadeh, and F. Regairaz, “Sequential coordination of transmission expansion planning with strategic generation investments,” IEEE Transactions on Power Systems, vol. 32, no. 4, pp. 2521–2534, 2017.

    Article  Google Scholar 

  12. E. Sauma and S. Oren, “Economic criteria for planning transmission investment in restructured electricity markets,” IEEE Transactions on Power Systems, vol. 22, no. 4, pp. 1394–1405, 2007.

    Article  Google Scholar 

  13. D. Pozo, J. Contreras, and E. Sauma, “If you build it, he will come: Anticipative power transmission planning,” Energy Economics, vol. 36, pp. 135–146, 2013.

    Article  Google Scholar 

  14. J. Aghaei, N. Amjady, A. Baharvandi, and M. Akbari, “Generation and transmission expansion planning: MILP-based probabilistic model,” IEEE Transactions on Power Systems, vol. 29, pp. 1592–1601, 2014.

    Article  Google Scholar 

  15. S. Moghaddam, “Generation and transmission expansion planning with high penetration of wind farms considering spatial distribution of wind speed,” International Journal of Electrical Power & Energy Systems, vol. 106, pp. 232–241, 2019.

    Article  Google Scholar 

  16. S. You, S. Hadley, M. Shankar, and Y. Liu, “Co-optimizing generation and transmission expansion with wind power in large-scale power grids – implementation in the us eastern interconnection,” Electric Power System Research, vol. 133, pp. 209–218, 2016.

    Article  Google Scholar 

  17. B. Alizadeh and S. Jadid, “Reliability constrained coordination of generation and transmission expansion planning in power systems using mixed integer programming,” IET Generation, Transmission & Distribution, vol. 5, pp. 948–960, 2011.

    Article  Google Scholar 

  18. B. Alizadeh and S. Jadid, “A dynamic model for coordination of generation and transmission expansion planning in power systems,” International Journal of Electrical Power & Energy Systems, vol. 65, pp. 408–418, 2015.

    Article  Google Scholar 

  19. F. Fallahi, M. Nick, G. Riahy, S. Hosseinian, and A. Doroudi, “The value of energy storage in optimal non-firm wind capacity connection to power systems,” Renewable Energy, vol. 64, pp. 34–42, 2014.

    Article  Google Scholar 

  20. C. Unsihuay-Vila, J. Marangon-Lima, A. Zambroni de Souza, and I. Perez-Arriaga, “Multistage expansion planning of generation and interconnections with sustainable energy development criteria: A multiobjective model,” International Journal of Electrical Power & Energy Systems, vol. 33, no. 2, pp. 258–270, 2011.

    Article  Google Scholar 

  21. M. Hesamzadeh, J. Rosellon, and I. Vogelsang, Transmission Network Investment in Liberalized Power Markets. Springer, 2020.

    Google Scholar 

  22. G. Micheli, M. Vespucci, M. Stabile, C. Puglisi, and A. Ramos, “A two-stage stochastic MILP model for generation and transmission expansion planning with high shares of renewables,” Energy Systems, 2020.

    Google Scholar 

  23. A. Schwele, J. Kazempour, and P. Pinson, “Do unit commitment constraints affect generation expansion? A scalable stochastic model,” Energy Systems, 2019.

    Google Scholar 

  24. M. Fürsch, S. Hagspiel, C. Jägemann, S. Nagl, D. Lindenberger, and E. Tröster, “The role of grid extensions in a cost-efficient transformation of the european electricity system until 2050,” Applied Energy, vol. 104, pp. 642 – 652, 2013.

    Article  Google Scholar 

  25. M. Moeini-Aghtaie, A. Abbaspour, and M. Fotuhi-Firuzabad, “Incorporating large-scale distant wind farms in probabilistic transmission expansion planning–part i: Theory and algorithm,” IEEE Transactions on Power Systems, vol. 27, no. 3, pp. 1585–1593, 2012.

    Article  Google Scholar 

  26. H. Yu, C. Chung, K. Wong, and J. Zhang, “A chance constrained transmission network expansion planning method with consideration of load and wind farm uncertainties,” IEEE Transactions on Power Systems, vol. 24, no. 3, pp. 1568–1576, 2009.

    Article  Google Scholar 

  27. G. Orfanos, P. Georgilakis, and N. Hatziargyriou, “Transmission expansion planning of systems with increasing wind power integration,” IEEE Transactions on Power Systems, vol. 28, no. 2, pp. 1355–1362, 2012.

    Article  Google Scholar 

  28. C. Ruiz and A. Conejo, “Robust transmission expansion planning,” European Journal of Operational Research, vol. 242, no. 2, pp. 390–401, 2015.

    Article  Google Scholar 

  29. Z. Li, J. Li, F. Liu, H. Ye, X. Zhang, S. Mei, and N. Chang, “Robust coordinated transmission and generation expansion planning considering ramping requirements and construction periods,” IEEE Transactions on Power Systems, vol. 33, no. 1, pp. 268–280, 2018.

    Article  Google Scholar 

  30. S. Dehghan, N. Amjady, and K. Ahad, “Two-stage robust generation expansion planning: A mixed integer linear programming model,” IEEE Transactions on Power Systems, vol. 29, no. 2, pp. 584–597, 2014.

    Article  Google Scholar 

  31. S. Chen, J. Wang, Y. He, and Z. Wang, “Robust optimization for transmission expansion planning: Minimax cost vs. minimax regret,” IEEE Transactions on Power Systems, vol. 29, no. 6, pp. 3069–3077, 2014.

    Article  Google Scholar 

  32. D. Mejía-Giraldo and J. McCalley, “Maximizing future flexibility in electric generation portfolios,” IEEE Transactions on Power Systems, vol. 29, pp. 279–288, 2014.

    Article  Google Scholar 

  33. P. Maloney, O. Olatujoye, A. Ardakani, D. Mejía-Giraldo, and J. McCalley, “A comparison of stochastic and adaptation programming methods for long term generation and transmission co-optimization under uncertainty,” in 2016 North American Power Symposium (NAPS), Denver, CO, USA, 2016.

    Google Scholar 

  34. J. Birge and F. Louveaux, Introduction to Stochastic Programming. Springer, New York: Springer Series in Operations Research and Financial Engineering, 2011.

    Book  MATH  Google Scholar 

  35. J. Alvarez Lopez, K. Ponnambalam, and V. Quintana, “Generation and transmission expansion under risk using stochastic programming,” IEEE Transactions on Power Systems, vol. 22, no. 3, pp. 1369–1378, 2007.

    Google Scholar 

  36. A. Van der Weijde and B. Hobbs, “The economics of planning electricity transmission to accommodate renewables: Using two-stage optimisation to evaluate flexibility and the cost of disregarding uncertainty,” Energy Economics, vol. 34, no. 6, pp. 2089–2101, 2012.

    Article  Google Scholar 

  37. S. Jin, S. Ryan, J. Watson, and D. Woodruff, “Modeling and solving a large-scale generation expansion planning problem under uncertainty,” Energy Systems, vol. 2, pp. 209–242, 2011.

    Article  Google Scholar 

  38. A. Conejo, L. Baringo, S. Kazempour, and A. Siddiqui, Investment in electricity generation and transmission: Decision making under uncertainty. Springer, 2016.

    Google Scholar 

  39. Y. Liu, R. Sioshansi, and A. Conejo, “Multistage stochastic investment planning with multiscale representation of uncertainties and decisions,” IEEE Transactions on Power Systems, vol. 33, no. 1, pp. 781–791, 2018.

    Article  Google Scholar 

  40. L. Baringo and A. Conejo, “Risk-constrained multi-stage wind power investment,” IEEE Transactions on Power Systems, vol. 28, no. 1, pp. 401–411, 2013.

    Article  Google Scholar 

  41. M. Fürsch, S. Nagl, and D. Lindenberg, “Optimization of power plant investments under uncertain renewable energy deployment paths: a multistage stochastic programming approach,” Energy Systems, vol. 5, pp. 85–121, 2014.

    Article  Google Scholar 

  42. K. Poncelet, E. Delarue, D. Six, J. Duerinck, and W. D’haeseleer, “Impact of the level of temporal and operational detail in energy-system planning models,” Applied Energy, vol. 162, pp. 631–643, 2016.

    Google Scholar 

  43. A. Belderbos and E. Delarue, “Accounting for flexibility in power system planning with renewables,” International Journal of Electrical Power & Energy Systems, vol. 71, pp. 33–41, 2015.

    Article  Google Scholar 

  44. D. Kirschen, J. Ma, V. Silva, and R. Belhomme, “Optimizing the flexibility of a portfolio of generating plants to deal with wind generation,” in 2011 IEEE Power and Energy Society General Meeting, Detroit, MI, USA, 2011.

    Google Scholar 

  45. M. Fripp, “Switch: A planning tool for power systems with large shares of intermittent renewable energy,” Environmental Science & Technology, vol. 46, no. 11, pp. 6371–6378, 2012.

    Article  Google Scholar 

  46. E. Hart and M. Jacobson, “A monte carlo approach to generator portfolio planning and carbon emissions,” Renewable Energy, vol. 36, no. 8, pp. 2278–2286, 2011.

    Article  Google Scholar 

  47. M. Nick, R. Cherkaoui, and M. Paolone, “Optimal allocation of dispersed energy storage systems in active distribution networks for energy balance and grid support,” IEEE Transactions on Power Systems, vol. 29, no. 5, pp. 2300–2310, 2014.

    Article  Google Scholar 

  48. P. Nahmmacher, E. Schmid, L. Hirth, and B. Knopf, “Carpe diem: A novel approach to select representative days for long-term power system models with high shares of renewable energy sources,” Energy, vol. 112, pp. 430–442, 2016.

    Article  Google Scholar 

  49. M. ElNozahy, M. Salama, and R. Seethapathy, “A probabilistic load modelling approach using clustering algorithms,” in 2013 IEEE Power & Energy Society General Meeting, 2013.

    Google Scholar 

  50. S. Fazlollahi, S. Bungener, P. Mandel, G. Becker, and F. Maréchal, “Multi-objectives, multi-period optimization of district energy systems: I. selection of typical operating periods,” Computers & Chemical Engineering, vol. 65, pp. 54–662, 2014.

    Article  Google Scholar 

  51. K. Poncelet, H. Höschle, E. Delaru, A. Virag, and W. D’haeseleer, “Selecting representative days for capturing the implications of integrating intermittent renewables in generation expansion planning problems,” IEEE Transactions on Power Systems, vol. 32, no. 3, pp. 1936–1948, 2017.

    Google Scholar 

  52. K. Poncelet, A. van Stiphout, J. Meus, E. Delarue, and W. D’haeseleer, “Lusym invest: a generation expansion planning model with a high level of temporal and technical detail,” tech. rep., KU Leuven, 2018. TME Working Paper WP EN2018-07.

    Google Scholar 

  53. D. Tejada-Arango, M. Domeshek, S. Wogrin, and E. Centeno, “Enhanced representative days and system states modeling for energy storage investment analysis,” IEEE Transactions on Power Systems, vol. 33, no. 6, pp. 6534–6544, 2018.

    Article  Google Scholar 

  54. G. Micheli, M. Vespucci, M. Stabile, and A. Cortazzi, “Selecting and initializing representative days for generation and transmission expansion planning with high shares of renewables,” in Graphs and combinatorial optimization: from theory to applications - CTW2020 proceedings (C. Gentile, G. Stecca, and P. Ventura, eds.), pp. 321–334, Springer, 2020.

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Management, Information and Production Engineering, University of Bergamo, via Marconi 5, 24044, Dalmine, BG, Italy

    Giovanni Micheli & Maria Teresa Vespucci

Authors
  1. Giovanni Micheli
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Maria Teresa Vespucci
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Maria Teresa Vespucci .

Editor information

Editors and Affiliations

  1. Department of Mathematics, Sultan Qaboos University, Muscat, Oman

    Mehiddin Al-Baali

  2. Department of Mathematics, Sultan Qaboos University, Muscat, Oman

    Anton Purnama

  3. DIMES, University of Calabria, Arcavacada di Rende, Cosenza, Italy

    Lucio Grandinetti

Rights and permissions

Reprints and permissions

Copyright information

© 2021 The Author(s), under exclusive license to Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Micheli, G., Vespucci, M.T. (2021). A Survey on Modeling Approaches for Generation and Transmission Expansion Planning Analysis. In: Al-Baali, M., Purnama, A., Grandinetti, L. (eds) Numerical Analysis and Optimization. NAO 2020. Springer Proceedings in Mathematics & Statistics, vol 354. Springer, Cham. https://doi.org/10.1007/978-3-030-72040-7_9

Download citation

Publish with us

Policies and ethics

Search

Navigation