Alocação e dimensionamento ótimos de subestações elétricas por meio do algoritmo de busca corvo
DOI:
https://doi.org/10.21712/lajer.2024.v11.n2.p31-52Palavras-chave:
Subestações Elétricas, Planejamento de Sistemas Elétricos de Distribuição, Otimização, Meta-heurísticas, Crow Search AlgorithmResumo
O aumento contínuo na demanda global por energia elétrica tem gerado um significativo impulso no setor energético em escala mundial. Conforme destacado no relatório mais recente da International Energy Agency (2022), a demanda por energia elétrica em 2021 alcançou a marca expressiva de 24.700 TWh, apresentando um crescimento de 6% em relação ao ano anterior, representando o maior incremento desde 2010. Este contexto tem enfatizado a necessidade de um sistema de distribuição de energia elétrica robusto e confiável, que possa atender a essa crescente consumo sem comprometer o serviço por possíveis inadequações do sistema. Dessa maneira, este artigo propõe uma nova abordagem para enfrentar o desafio da alocação e dimensionamento de subestações elétricas em sistemas elétricos de distribuição, baseada na inteligência dos corvos, por meio do algoritmo de otimização Crow Search Algorithm (CSA). Além disso, o método desenvolvido também organiza a conexão das subestações elétricas aos centros de carga. O objetivo central é a minimização dos custos globais do projeto de alocação e dimensionamento de subestações elétricas, considerando um conjunto de objetivos e restrições técnicas e operacionais. Os testes na metaheurística foram realizados em um sistema elétrico de distribuição apresentado na literatura, que possui 38 centros de carga e 6 subestações elétricas já existentes, que permitiu estabelecer diferentes cenários de aplicação do método. Dessa forma, o CSA se mostrou um método promissor de aplicação no problema de alocação e dimensionamento de subestações elétricas.
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Referências
Askarzadeh, A., 2016. A novel metaheuristic method for solving constrained engineering optimization problems: Crow search algorithm. Computers & Structures, 169, pp.1–12. https://doi.org/10.1016/j.compstruc.2016.03.001.
Behzadi, S. & Bagheri, A., 2023. A Convex Micro-Grid-Based Optimization Model for Planning of Resilient and Sustainable Distribution Systems Considering Feeders Routing and Siting/Sizing of Substations and DG Units. Sustainable Cities and Society, 97, p.104787. https://doi.org/10.1016/j.scs.2023.104787.
El-Fouly, T.H.M. et al., 2008. A new optimization model for distribution substation siting, sizing, and timing. International Journal of Electrical Power & Energy Systems, 30(5), pp.308–315. https://doi.org/10.1016/j.ijepes.2007.10.002.
Hongwei, D. et al., 1993. Optimal planning of distribution substation locations and sizes-model and algorithm. In Proceedings of TENCON '93. IEEE Region 10 International Conference on Computers, Communications and Automation. IEEE. https://doi.org/10.1109/TENCON.1993.320655.
Hussien, A.G. et al., 2020. Crow Search Algorithm: Theory, Recent Advances, and Applications. IEEE Access, 8, pp.173548–173565. https://doi.org/10.1109/ACCESS.2020.3024108.
Ismael, S.M., Aleem, S.H.E.A. & Abdelaziz, A.Y., 2018. Optimal sizing and placement of distributed generation in Egyptian radial distribution systems using crow search algorithm. 2018 International Conference on Innovative Trends in Computer Engineering (ITCE). IEEE. https://doi.org/10.1109/ITCE.2018.8316646.
Jalilzade, S. & Bagheri, A., 2010. A new approach for Subtransmission System expansion planning with genetic algorithm. In International Congress on Ultra Modern Telecommunications and Control Systems. IEEE. https://doi.org/10.1109/ICUMT.2010.5676609.
Lavorato, M. et al., 2010. A Constructive Heuristic Algorithm for Distribution System Planning. IEEE Transactions on Power Systems, 25(3), pp.1734–1742. https://doi.org/10.1109/TPWRS.2009.2038164.
Li, L.-L. et al., 2018. Biogeography-based optimization based on population competition strategy for solving the substation location problem. Expert Systems with Applications, 97, pp.290–302. https://doi.org/10.1016/j.eswa.2017.12.039.
Nageswararao, M. et al., 2017. Multiple DG allocation by crow search algorithm for power loss reduction. 2017 IEEE International Conference on Power, Control, Signals and Instrumentation Engineering (ICPCSI). IEEE. https://doi.org/10.1109/ICPCSI.2017.8391822.
Najafi, S. et al., 2009. Optimal distribution substation locating in large distribution systems. In 2009 Transmission & Distribution Conference & Exposition: Asia and Pacific. IEEE. https://doi.org/10.1109/TD-ASIA.2009.5357019.
Najafi, S. & Gholizadeh, R., 2013. On optimal sizing, siting and timing of distribution substations. 18th Electric Power Distribution Conference. IEEE. https://doi.org/10.1109/EPDC.2013.6565964.
Osaba, E. et al., 2021. A Tutorial On the design, experimentation and application of metaheuristic algorithms to real-World optimization problems. Swarm and Evolutionary Computation, 64, p.100888. https://doi.org/10.1016/j.swevo.2021.100888.
Pandey, A.K. & Kirmani, S., 2019. Placement of distributed generator in distribution systems using Crow search algorithm. 2019 International Conference on Electrical, Electronics and Computer Engineering (UPCON). IEEE. https://doi.org/10.1109/UPCON47278.2019.8980157.
Queiroz, L.M.O. et al., 2012. Energy Losses Estimation in Power Distribution Systems. IEEE Transactions on Power Systems, 27(4), pp.1879–1887. https://doi.org/10.1109/TPWRS.2012.2188107.
QXG Technology, 2024. Power Transformer. Disponível em: https://www.qxgelec.com/110kv220kv-oil-immersed-power-transformer?gad_source=1&gclid=CjwKCAjwjqWzBhAqEiwAQmtgT5MUo7DCwCTG9HXY6ByI5vLh599-uriueDc92nWFRilOzcDnKiEF-hoC7WYQAvD_BwE [Acessado em 13 Jun. 2024].
Ravadanegh, S.N. & Roshanagh, R.G., 2013. A heuristic algorithm for optimal multistage sizing, siting and timing of MV distribution substations. Electric Power Systems Research, 105, pp.134–141. https://doi.org/10.1016/j.epsr.2013.07.019.
Sun, L. et al., 2018. Optimal Allocation of Smart Substations in a Distribution System Considering Interruption Costs of Customers. IEEE Transactions on Smart Grid, 9(4), pp.3773–3782. https://doi.org/10.1109/TSG.2016.2642163.
Tassi Souza Silva, F., Ramos Araujo, L. & Rosana Ribeiro Penido, D., 2018. Optimal Substation Placement in Distribution Systems using Artificial Immune Systems. IEEE Latin America Transactions, 16(2), pp.505–513. https://doi.org/10.1109/TLA.2018.8327406.
Temraz, H.K. & Salama, M.M.A., 2002. A planning model for siting, sizing and timing of distribution substations and defining the associated service area. Electric Power Systems Research, 62(2), pp.145–151. https://doi.org/10.1016/S0378-7796(02)00040-8.
Vahedi, S., Banejada, M. & Assili, M., 2015. Optimal location, sizing and allocation of subtransmission substations using K-means algorithm. In 2015 IEEE Power & Energy Society General Meeting. IEEE. https://doi.org/10.1109/PESGM.2015.7286220.
Wang, F. et al., 2021. Research on Optimal Sizing and Location of Substation According to Point Load Forecast Based on BIM. In 2021 IEEE 5th Conference on Energy Internet and Energy System Integration (EI2). IEEE. https://doi.org/10.1109/EI252483.2021.9712985.
Ye, Y. et al., 2023. Substation Location Planning Based on Multi-strategy Improved Marine Predators Algorithm. In 2023 18th International Conference on Intelligent Systems and Knowledge Engineering (ISKE). IEEE. https://doi.org/10.1109/ISKE60036.2023.10481305.
Zheng, N. et al., 2021. The Multi-Stage Substation Coordinated Planning Method Considering the Overall Economy. In 2021 IEEE 5th Conference on Energy Internet and Energy System Integration (EI2). IEEE. https://doi.org/10.1109/EI252483.2021.9713264.
Zhou Quan et al., 2002. GIS based distribution system spatial load forecasting and the optimal planning of substation location and capacity. In Proceedings. International Conference on Power System Technology. IEEE. https://doi.org/10.1109/ICPST.2002.1047527.
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