Interdisciplinarity Applied to the Optimized Dispatch of Integrated Electricity and Natural Gas Networks using the Genetic Algorithm

Authors

DOI:

https://doi.org/10.33448/rsd-v10i2.12641

Keywords:

Interdisciplinarity; Electric Power Generation; Genetic Algorithm; Natural gas.

Abstract

This paper proposes a method based on genetic algorithm (GA) for the security-constrained optimal dispatch of integrated natural gas and electricity networks, considering operating scenarios in both energy systems, demonstrating the importance of interdisciplinary teaching in the academic contents of Mathematics, Physics and Computing in modeling engineering problems. The mathematical formulation of the optimization problem consists of a multi-objective function which aims to minimize both costs of thermal generation (using processes based on diesel oil and natural gas) as well as the production and transportation of natural gas. The joint gas-electricity system is modeled by two separate groups of nonlinear equation, which are solved by the combination of Newton's method with the GA. The applicability of the proposed method is tested in the Belgian gas network integrated with the IEEE 14-bus test system and a 15-node natural gas network integrated with the IEEE 118-bus test system. The results demonstrate, with excellent levels of precision and accuracy, that the proposed method provides efficient and secure solutions for different operating scenarios in both energy systems, henceforth the case study carried out by the research group Gradient de Mathematical Modeling and Computational Simulation - GM²SC, linked to the Federal Institute of Education, Science and Technology of Pará - IFPA Campus Ananindeua.

Author Biographies

Heictor Alves de Oliveira Costa, College Estácio Belém

Graduating, in the last period, in Computer Engineering; member of the research group Gradiente de Mathematical Modeling and Computational Simulation - GM²SC; develops research in the area of ​​quantum computing and topology applied to the implementation of computational models.

Denis Carlos Lima Costa, Instituto Federal de Educação, Ciência e Tecnologia do Pará

Doctor in Energy Systems; professor at the Federal Institute of Education, Science and Technology of Pará; leader of the research group Gradient of Mathematical Modeling and Computational Simulation - GM²SC, member of the research group LICTI.

Lair Aguiar de Meneses, Instituto Federal de Educação, Ciência e Tecnologia do Pará

Master in Electrical Engineering; professor at the Federal Institute of Education, Science and Technology of Pará; member of the Gradiente research group on Mathematical Modeling and Computational Simulation - GM²SC.

References

An, S., Li, Q., & Gedra, T. W., (2003). Natural gas and electricity optimal power flow, in Proc. IEEE/PES Transmission and Distribution Conf. Expo. vol. 1, pp. 7–12.

Arnold, M. & Andersson, G. (2008). Decomposed electricity and natural gas optimal power Flow. Proceedings of 16th Power Systems Computation Conf. (PSCC), Glasgow, Scotland.

Bernades, D. M., Celeste, W. C., Diniz Chaves, G. de L. (2020). Energy efficiency in urban public lighting: literature review of equipment and technologies. Research, Society and Development, [S. l.], v. 9, n°. 7, p. e606973957. DOI: 10.33448/rsd-v9i7.3957. Available in: https://rsdjournal.org/index.php/rsd/article/view/3957.

Chaudry, M., Jenkins, N. & Strbac, G. (2008). Multi-time period combined gas and electricity network optimization. Elec. Power Syst. Research, Vol. 78, n°. 7, pp. 1265-1279. 2008.

Costa, Denis C. L., Nunes, Marcus V.A., Vieira, João P.A. & Bezerra, Ubiratan H. (2016). Decision tree-based security dispatch application in integrated electric power and natural-gas networks. Electric Power Systems Research 141 (2016) 442–449.

Cruz, H. M. Da., Barros, R. M., Santos, I. F. S. dos, Tiago Filho, G. L. (2019). Study of the potential of generation of electric energy from the biogas of digestion anaerobia of food residues. Research, Society and Development, [S. l.], v. 8, n°. 5, p. e3785811. DOI: 10.33448/rsd-v8i5.811. Available in: https://rsdjournal.org/index.php/rsd/article/view/811.

El-Mahdy, O. F. M., Ahmed, M. E. H. and Metwalli, S. (2010). Computer aided optimization of natural gas pipe networks using genetic algorithm. Applied Soft Computing, Vol 10, n° 4. pp. 1141-1150.

Geidl, M. & Andersson, G. (2007). Optimal power flow of multiple energy carriers. IEEE Trans. Power Syst. Vol. 22, n°. 1, pp. 145-155.

IDEC, Brazilian Institute of Consumer Protection, 2020. Published by: Climate and Society Institute - ICS. Available: www.idec.org.br.

Kaplan, S. M. (2010). Displacing coal with generation from existing natural gas-fired power Plants. CRS Report for Congress, 7-5700, R41027. Available: http://assets.opencrs.com/rpts.

Liu, C., Shahidehpour, M., Fu, Y., & Z. Li. (2009). Security-constrained unit commitment with natural gas transmission constraints. IEEE Trans. Power Syst., vol. 24, n°. 3, pp. 1523–1536.

Maimoni, F. P., Cardoso, R. B. (2020). Economic feasibility analysis for alternatives to use solar energy in homes in the State of Minas Gerais, Brazil. Research, Society and Development, [S. l.], v. 9, n°. 8, p. e853986221. DOI: 10.33448/rsd-v9i8.6221. Available in: https://rsdjournal.org/index.php/rsd/article/view/6221.

Mares, A. M. & Esquivel, C. R. F. (2012). A unified gas and power flow analysis in natural gas and electricity coupled networks. IEEE Trans. Power Syst., vol. 27, n°. 4, pp. 2156–2166.

Munoz, J., Jimenez-Redondo, N., Perez-Ruiz, J. & Barquin, J. (2003). Natural gas network modeling for power systems reliability studies. in Proc. IEEE/PES General Meeting, vol. 4, pp. 23–26.

Nascimento, B. Z., Catelan, T. C., Chaves, G. de L. D., Celeste, W. C. (2019). Evaluation of the Viability of Implementation of Renewable Hybrid Systems for Energy Access in the Amazon Region. Research, Society and Development, [S. l.], v. 8, n°. 10, p. e448101415. DOI: 10.33448/rsd-v8i10.1415. Available in: https://rsdjournal.org/index.php/rsd/article/view/1415.

Osiadacz, A. J. (1987). Simulation and analysis of gas networks. London: E. & F. N. Spon. pp. 273.

Pereira, A. S., Shitsuka, D. M., Parreira, F. J. & Shitsuka, R. (2018). Metodologia da pesquisa científica. [e-book]. 1ª Ed. Santa Maria, RS. Universidade Federal de Santa Maria – UFSM. Núcleo de Tecnologia Educacional - NTE. Disponível em: https://repositorio.ufsm.br/bitstream/handle/1/15824/Lic_Computacao_Metodologia-Pesquisa-Cientifica.pdf?sequence=1.

PSTCA. Power Systems Test Case Archive. (1993). Available: http://www.ee.washington.edu/research/pstca/.

Quelhas, A., Gil, E., McCalley, J. D. & Ryan, S. M. (2007). A multiperiod generalized network flow model of the U.S. integrated energy system: Part I - Model description. IEEE Trans. Power Syst., vol. 22, n°. 2, pp. 829–836.

Shahidehpour, M., Fu, Y. & Wiedman, T. (2005). Impact of natural gas infrastructure on electric power systems. Proc. IEEE, vol. 93, n°. 5, pp. 1042–1056.

Spinola, L., Almeida, F. C. P. de, Menezes, M. A., Facó, J. F. B. (2020). Contextualizing interdisciplinarity: a case study at the Federal University of ABC. Research, Society and Development, [S. l.], v. 9, n. 3, p. e81932456. DOI: 10.33448/rsd-v9i3.2456. Disponível em: https://rsdjournal.org/index.php/rsd/article/view/2456.

Tao, L., Eremia, M. & Shahidehpour, M. (2008). Interdependency of natural gas network and power systems security. IEEE Trans. Power Syst., vol. 23, n°. 4, pp. 1817–1824.

Unsihuay, C., Lima, J. W. Marangon, & Souza, A. C. Zambroni. (2007). Modeling the integrated natural gas and electricity optimal power flow. in Proc. IEEE/PES General Meeting, pp. 24–28.

Wolf, D. & Smeers, Y. (1996). Optimal dimensioning of pipe networks with application to gas transmission networks. Operations Research, vol. 44, n°. 4, pp. 596-608.

Wolf, D. & Smeers, Y. (2000). The Gas transmission problem solved by an extension of the simplex algorithm. Management Science, vol. 46, n°. 11, pp. 1454-1465.

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Published

21/02/2021

How to Cite

COSTA, H. A. de O.; COSTA, D. C. L.; MENESES, L. A. de. Interdisciplinarity Applied to the Optimized Dispatch of Integrated Electricity and Natural Gas Networks using the Genetic Algorithm. Research, Society and Development, [S. l.], v. 10, n. 2, p. e42110212641, 2021. DOI: 10.33448/rsd-v10i2.12641. Disponível em: https://www.rsdjournal.org/index.php/rsd/article/view/12641. Acesso em: 20 apr. 2024.

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Section

Engineerings