Transmission Expansion Planning using loss of capacity probability tables in the generation-transmission model

Authors

DOI:

https://doi.org/10.15332/iteckne.v20i1.3071

Keywords:

DC power flow, reliability indices, generation and transmission expansion planning (G&TEP), mixed integer linear programming (MILP), , capacity outage probability table

Abstract

Electrical power systems, in the generation transmission stage, have great importance worldwide. These systems are the way to distribute large amounts of electrical energy from the electrical generation centers to different kind of consumers. The generation-transmission system expansion planning is highly representative, so meeting the demand response and its growth is the challenge for companies which are in this line of business. In this work, the generation-transmission system expansion planning is carried out in a test system through two phases. In the first phase, an algorithm is developed to build capacity loss probability tables and use reliability criteria to determine new generation projects necessary to
cover demand and have the necessary reserve for a defined planning horizon year. Using the results of the first stage, the second phase begins, in this stage an optimization algorithm is used for a mixed integer linear problem and
application of the optimal DC power flow to determine the transmission projects necessary to connect, to the base system, the new generation projects determined in the first phase and their optimal power dispatch to minimize
investment and operating costs.

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Author Biographies

Santiago Javier Maita-Sánchez, Universidad Politécnica Salesiana

Ingeniero Eléctrico, Escuela Politécnica Nacional: Quito, EC. Magister en Electricidad, Universidad Politécnica Salesiana - Sede Quito: Quito, Pichincha, EC

Carlos Andrés Barrera-Singaña, Universidad Politécnica Salesiana

Ingeniero Eléctrico, Escuela Politécnica Nacional: Quito, Pichincha, EC. Maestría en Energías Renovables y Eficiencia Energética, Universidad de Zaragoza: Zaragoza, Aragón, ES. Maestría en Métodos Matemáticos y Simulación Numérica en Ingeniería Qualification, Universidad Politécnica Salesiana del Ecuador: Quito, Ecuador, EC. Doctorado en Energías Renovables y Eficiencia Energética Education, Universidad de Zaragoza: Zaragoza, Aragón, ES.

 

References

[1] H. Sadeghi, M. Rashidinejad, and A. Abdollahi, “A comprehensive sequential review study through the generation expansion planning”, Renew. Sustain. Energy Rev., vol. 67, no. September 2016, pp. 1369-1394, 2017.

[2] A. N. de Paula, E. J. de Oliveira, L. W. Oliveira, and C. A. Moraes, “Reliability-constrained dynamic transmission expansion planning considering wind power generation”, Electr. Eng., vol. 102, no. 4, pp. 2583-2593, 2020.

[3] J. Oteng-Adjei, A. M. I. Malori, and E. K. Anto, “Generation System Expansion Planning Using Loss of Load Expectation Criterion”, 2020 IEEE PES/IAS PowerAfrica, PowerAfrica 2020, pp. 1–5, 2020.

[4] N. Gideon Ude, H. Yskandar, and R. Coneth Graham, “A Comprehensive State-of-the-Art Survey on the Transmission Network Expansion Planning Optimization Algorithms”, IEEE Access, vol. 7, pp. 123158–123181, 2019.

[5] M. Malakoti-Moghadam, A. Askarzadeh, and M. Rashidinejad, “Transmission and generation expansion planning of energy hub by an improved genetic algorithm”, Energy Sources, Part A Recover. Util. Environ. Eff., vol. 41, no. 24, pp. 3112-3126, 2019.

[6] S. A. Mansouri and M. S. Javadi, “A robust optimisation framework in composite generation and transmission expansion planning considering inherent uncertainties”, J. Exp. Theor. Artif. Intell., vol. 29, no. 4, pp. 717-730, 2017.

[7] E. A. Martínez Ceseña, T. Capuder, and P. Mancarella, “Flexible distributed multienergy generation system expansion planning under uncertainty”, IEEE Trans. Smart Grid, vol. 7, no. 1, pp. 348-357, 2016.

[8] P. Suriya, S. Subramanian, S. Ganesan, and M. Hariprasath, “Multi-objective generation expansion and retirement planning using chaotic grasshopper optimisation algorithm”, Aust. J. Electr. Electron. Eng., vol. 16, no. 3, pp. 136-148, 2019.

[9] S. P. Torres, C. A. Castro, R. M. Pringles, and W. Guaman, “Comparison of particle swarm based meta-heuristics for the electric transmission network expansion planning problem”, IEEE Power Energy Soc. Gen. Meet., pp. 1-7, 2011.

[10] G. Latorre, R. Darío Cruz, J. M. Areiza, and A. Villegas, “Classification of publications and models on transmission expansion planning”, IEEE Trans. Power Syst., vol. 18, no. 2, pp. 938-946, 2003.

[11] G. Slipac, M. Zeljko, and D. Šljivac, “Importance of reliability criterion in power system expansion planning”, Energies, vol. 12, no. 9, 2019.

[12] E. Lannoye, D. Flynn, and M. O’Malley, “Transmission, variable generation, and power system flexibility”, IEEE Trans. Power Syst., vol. 30, no. 1, pp. 57-66, 2015.

[13] M. Dicorato, M. Trovato, C. Vergine, C. Gadaleta, B. Aluisio, and G. Forte, “Extended flow-based security assessment for real-sized transmission network planning”, Energies, vol. 13, no. 13, 2020.

[14] L. Bahiense, G. C. Oliveira, M. Pereira, and S. Granville, “A mixed integer disjunctive model for transmission network expansion”, IEEE Trans. Power Syst., vol. 16, no. 3, pp. 560-565, 2001.

[15] N. Alguacil, A. L. Motto, and A. J. Conejo, “Transmission expansion planning: A mixed-integer LP approach”, IEEE Trans. Power Syst., vol. 18, no. 3, pp. 1070-1077, 2003.

[16] B. Alizadeh and S. Jadid, “Reliability constrained coordination of generation and transmission expansion planning in power systems using mixed integer programming”, IET Gener. Transm. Distrib., vol. 5, no. 9, pp. 948-960, 2011.

[17] B. Mohammadi-Ivatloo, A. Rabiee, and A. Soroudi, “Nonconvex dynamic economic power dispatch problems solution using hybrid immune-genetic algorithm”, IEEE Syst. J., vol. 7, no. 4, pp. 777-785, 2013.

[18] Y. Huang et al., “Multi-stage transmission network planning considering transmission congestion in the power market”, Energies, vol. 13, no. 18, 2020.

[19] Y. Zhan and Q. P. Zheng, “A multistage decision-dependent stochastic bilevel programming approach for power generation investment expansion planning”, IISE Trans., vol. 50, no. 8, pp. 720-734, 2018.

[20] M. J. Rider, A. V. Garcia, and R. Romero, “Power system transmission network expansion planning using AC model”, IET Gener. Transm. Distrib., vol. 1, no. 5, pp. 731-742, 2007.

[21] A. Moreira, G. Strbac, R. Moreno, A. Street, and I. Konstantelos, “A five-level MILP model for flexible transmission network planning under uncertainty: A min-max regret approach”, IEEE Trans. Power Syst., vol. 33, no. 1, pp. 486-501, 2018.

[22] Z. Zhou et al., “Reliability-constrained AC power flow-based co-optimization planning of generation and transmission systems with uncertainties”, IEEE Access, vol. 8, pp. 194218-194227, 2020.

[23] A. Ahmadi, H. Mavalizadeh, A. Esmaeel Nezhad, P. Siano, H. A. Shayanfar, and B. Hredzak, “A robust model for generation and transmission expansion planning with emission constraints”, Simulation, vol. 96, no. 7, pp. 605-621, 2020.

[24] J. T. Jiménez, J. L. Guardado, N. G. Cabrera, J. R. Rodríguez, and F. Figueroa, “Transmission expansion planning systems using algorithm genetic with multi-objective criterion”, IEEE Lat. Am. Trans., vol. 15, no. 3, pp. 563-568, 2017.

[25] A. M. Al-Shaalan, “Reliability evaluation in generation expansion planning based on the expected energy not served”, J. King Saud Univ. - Eng. Sci., vol. 24, no. 1, pp. 11-18, 2012.

[26] H. Park, “Generation capacity expansion planning considering hourly dynamics of renewable resources”, Energies, vol. 13, no. 21, 2020.

[27] A. Moreira, D. Pozo, A. Street, and E. Sauma, “Reliable Renewable Generation and Transmission Expansion Planning: Co-Optimizing System’s Resources for Meeting Renewable Targets”, IEEE Trans. Power Syst., vol. 32, no. 4, pp. 3246-3257, 2017.[28] R. Hemmati, R. A. Hooshmand, and A. Khodabakhshian, “Comprehensive review of generation and transmission expansion planning”, IET Gener. Transm. Distrib., vol. 7, no. 9, pp. 955-964, 2013.

[29] Y. Tohidi, M. R. Hesamzadeh, and F. Regairaz, “Planning with Strategic Generation Investments”, IEEE Trans. Power Syst., vol. 32, no. 4, pp. 2521-2534, 2017.

[30] P. Cazanova and J. Salazar, “Software en MATLAB para la Expansión de Generación Aplicando Criterios de Confiabilidad”, Rev. Técnica “Energía”, vol. 8, no. 1, pp. 21-27,
2012.
[31] A. Soroudi, Power system optimization modeling in GAMS. 2017
Carátula

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Published

2023-07-11

How to Cite

Maita-Sánchez, S. J., & Barrera-Singaña, C. A. (2023). Transmission Expansion Planning using loss of capacity probability tables in the generation-transmission model. ITECKNE, 20(1), 7–16. https://doi.org/10.15332/iteckne.v20i1.3071

Issue

Vol. 20 No. 1 (2023)

Section

Research and Innovation Articles

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