Control de voltaje de múltiples microrredes basado en optimización distribuida

dc.contributor.advisorMojica Nava, Eduardo Aliriospa
dc.contributor.authorRodriguez Gil, Jhojan Alexisspa
dc.contributor.researchgroupPrograma de Investigacion sobre Adquisicion y Analisis de Señales Paas-Unspa
dc.date.accessioned2024-04-16T18:49:47Z
dc.date.available2024-04-16T18:49:47Z
dc.date.issued2023
dc.descriptionilustraciones, diagramasspa
dc.description.abstractEsta tesis estudia el uso de control distribuido predictivo basado en el Método de Mul- tiplicadores de Direcciones Alternantes (ADMM) para obtener la regulación de voltaje en microrredes interconectadas. Este problema es modelado mediante una función global de costo y este trabajo propone un algoritmo que lo soluciona usando decisiones locales. Así mismo, la función global de costo es formada por una suma de funciones locales de costo. El problema global es solucionado de manera local usando Control Predictivo Basado en Modelo (MPC). De esta manera, la solución del problema se obtiene de manera distribuida. Además, este trabajo presenta un estudio de la convergencia del algoritmo propuesto. Final- mente, para probar el algoritmo propuesto se utilizan dos casos de simulación. Primero, una simulación numérica en MATLAB® se usa en el problema de regulación de voltaje en micro- rredes interconectadas. Segundo, se usan unos dispositivos discretos para emular el sistema interconectado de una simulación Hardware-in-the-Loop (HIL). Los resultados muestran la efectividad del algoritmo propuesto para solucionar el problema de regulación de voltaje para microrredes interconectadas. (Texto tomado de la fuente).spa
dc.description.abstractThis dissertation studies a distributed predictive control approach based on the Alterna- ting Direction Method of Multipliers (ADMM) to achieve voltage regulation on networked microgrids. The control problem considers a global cost function. So, this work proposes an algorithm to solve it using local decisions. Likewise, the global cost function contains a set of local functions. The global local problem is solved in a local way using Model Pre- dictive Control (MPC). In this way, we can obtain the problem solution in a distributed approach. Also, this work shows a convergence study of the proposed algorithm. Finally, to test the proposed algorithm, there are two simulation cases. First, a numerical simulation in MATLAB® is used to study the voltage regulation problem in networked microgrids. Se- cond, discrete devices are used to emulate the networked system and individual controllers in a Hardware-in-the-Loop (HIL) fashion. Results show the effectiveness of the proposed algorithm in solving the voltage regulation problem for networked microgrids.eng
dc.description.degreelevelMaestríaspa
dc.description.degreenameMagíster en Ingeniería - Automatización Industrialspa
dc.description.researchareaTeoría y aplicación de controlspa
dc.description.sponsorshipAgradezco al apoyo recibido por parte de la Universidad Nacional de Colombia y el Ministerio de Ciencias, Tecnología e Innovación con el proyecto “Programa de Investigación en Tecnologías Emergentes para Microrredes Eléctricas Inteligentes con Alta Penetración de Energías Renovables” mediante el contrato 80740-542-2020.spa
dc.format.extent88 páginasspa
dc.format.mimetypeapplication/pdfspa
dc.identifier.instnameUniversidad Nacional de Colombiaspa
dc.identifier.reponameRepositorio Institucional Universidad Nacional de Colombiaspa
dc.identifier.repourlhttps://repositorio.unal.edu.co/spa
dc.identifier.urihttps://repositorio.unal.edu.co/handle/unal/85928
dc.language.isospaspa
dc.publisherUniversidad Nacional de Colombiaspa
dc.publisher.branchUniversidad Nacional de Colombia - Sede Bogotáspa
dc.publisher.facultyFacultad de Ingenieríaspa
dc.publisher.placeBogotá, Colombiaspa
dc.publisher.programBogotá - Ingeniería - Maestría en Ingeniería - Automatización Industrialspa
dc.relation.referencesS. Boyd, N. Parikh, E. Chu, B. Peleato, and J. Eckstein, “Distributed optimization and statistical learning via the alternating direction method of multipliers,” Foundations and Trends® in Machine Learning, vol. 3, no. 1, pp. 1–122, 2011.spa
dc.relation.referencesT. Goldstein, B. O’Donoghue, S. Setzer, and R. Baraniuk, “Fast alternating direction optimization methods,” SIAM Journal on Imaging Sciences, vol. 7, no. 3, pp. 1588– 1623, 2014.spa
dc.relation.referencesS. Anderson, P. Hidalgo-Gonzalez, R. Dobbe, and C. J. Tomlin, “Distributed model predictive control for autonomous droop-controlled inverter-based microgrids,” in 2019 IEEE 58th Conference on Decision and Control (CDC), 2019, pp. 6242–6248.spa
dc.relation.referencesK. Rahbar, C. C. Chai, and R. Zhang, “Energy cooperation optimization in microgrids with renewable energy integration,” IEEE Transactions on Smart Grid, vol. 9, no. 2, pp. 1482–1493, 2018.spa
dc.relation.referencesX. Dou, P. Xu, Q. Hu, W. Sheng, X. Quan, Z. Wu, and B. Xu, “A distributed voltage control strategy for multi-microgrid active distribution networks considering economy and response speed,” IEEE Access, vol. 6, pp. 31 259–31 268, 2018.spa
dc.relation.referencesN. Priyadharshini, S. Gomathy, and M. Sabarimuthu, “A review on microgrid archi- tecture, cyber security threats and standards,” Materials Today: Proceedings, 2020.spa
dc.relation.referencesC. Wang, P. Yang, C. Ye, Y. Wang, and Z. Xu, “Voltage control strategy for three/single phase hybrid multimicrogrid,” IEEE Transactions on Energy Conversion, vol. 31, no. 4, pp. 1498–1509, 2016.spa
dc.relation.referencesM. N. Alam, S. Chakrabarti, and A. Ghosh, “Networked microgrids: State-of-the-art and future perspectives,” IEEE Transactions on Industrial Informatics, vol. 15, no. 3, pp. 1238–1250, 2019.spa
dc.relation.referencesM. Savaghebi, A. Jalilian, J. C. Vasquez, and J. M. Guerrero, “Secondary control scheme for voltage unbalance compensation in an islanded droop-controlled microgrid,” IEEE Transactions on Smart Grid, vol. 3, no. 2, pp. 797–807, 2012.spa
dc.relation.referencesF. Guo, C. Wen, J. Mao, and Y.-D. Song, “Distributed secondary voltage and frequency restoration control of droop-controlled inverter-based microgrids,” IEEE Transactions on Industrial Electronics, vol. 62, no. 7, pp. 4355–4364, 2015.spa
dc.relation.referencesS. A. Arefifar, M. Ordonez, and Y. A.-R. I. Mohamed, “Voltage and current contro- llability in multi-microgrid smart distribution systems,” IEEE Transactions on Smart Grid, vol. 9, no. 2, pp. 817–826, 2018.spa
dc.relation.referencesD. O. Amoateng, M. Al Hosani, M. S. Elmoursi, K. Turitsyn, and J. L. Kirtley, “Adap- tive voltage and frequency control of islanded multi-microgrids,” IEEE Transactions on Power Systems, vol. 33, no. 4, pp. 4454–4465, 2018.spa
dc.relation.referencesJ. W. Simpson-Porco, Q. Shafiee, F. Dörfler, J. C. Vasquez, J. M. Guerrero, and F. Bu- llo, “Secondary frequency and voltage control of islanded microgrids via distributed ave- raging,” IEEE Transactions on Industrial Electronics, vol. 62, no. 11, pp. 7025–7038, 2015.spa
dc.relation.referencesJ. Rocabert, A. Luna, F. Blaabjerg, and P. Rodríguez, “Control of power converters in ac microgrids,” IEEE Transactions on Power Electronics, vol. 27, no. 11, pp. 4734– 4749, 2012.spa
dc.relation.referencesJ. M. Guerrero, J. C. Vasquez, J. Matas, L. G. de Vicuna, and M. Castilla, “Hierarchical control of droop-controlled ac and dc microgrids—a general approach toward standar- dization,” IEEE Transactions on Industrial Electronics, vol. 58, no. 1, pp. 158–172, 2011.spa
dc.relation.referencesJ. M. Guerrero, M. Chandorkar, T.-L. Lee, and P. C. Loh, “Advanced control architec- tures for intelligent microgrids—part i: Decentralized and hierarchical control,” IEEE Transactions on Industrial Electronics, vol. 60, no. 4, pp. 1254–1262, 2013.spa
dc.relation.referencesR. H. Lasseter, “Smart distribution: Coupled microgrids,” Proceedings of the IEEE, vol. 99, no. 6, pp. 1074–1082, 2011.spa
dc.relation.referencesM. Marzband, N. Parhizi, M. Savaghebi, and J. M. Guerrero, “Distributed smart decision-making for a multimicrogrid system based on a hierarchical interactive ar- chitecture,” IEEE Transactions on Energy Conversion, vol. 31, no. 2, pp. 637–648, 2016.spa
dc.relation.referencesH. Han, X. Hou, J. Yang, J. Wu, M. Su, and J. M. Guerrero, “Review of power sharing control strategies for islanding operation of ac microgrids,” IEEE Transactions on Smart Grid, vol. 7, no. 1, pp. 200–215, 2016.spa
dc.relation.referencesA. Q. Huang, M. L. Crow, G. T. Heydt, J. P. Zheng, and S. J. Dale, “The future rene- wable electric energy delivery and management (freedm) system: The energy internet,” Proceedings of the IEEE, vol. 99, no. 1, pp. 133–148, 2011.spa
dc.relation.referencesJ. Hu, Y. Shan, J. M. Guerrero, A. Ioinovici, K. W. Chan, and J. Rodriguez, “Model predictive control of microgrids – an overview,” Renewable and Sustainable Energy Reviews, vol. 136, p. 110422, 2021.spa
dc.relation.referencesN. Bazmohammadi, A. Tahsiri, A. Anvari-Moghaddam, and J. M. Guerrero, “Sto- chastic predictive control of multi-microgrid systems,” IEEE Transactions on Industry Applications, vol. 55, no. 5, pp. 5311–5319, 2019.spa
dc.relation.referencesF. Milano, F. Dörfler, G. Hug, D. J. Hill, and G. Verbič, “Foundations and challenges of low-inertia systems (invited paper),” in 2018 Power Systems Computation Conference (PSCC), 2018, pp. 1–25.spa
dc.relation.referencesC. A. Macana, E. Mojica-Nava, H. R. Pota, J. M. Guerrero, and J. C. Vasquez, “A novel compact dq-reference frame model for inverter-based microgrids,” Electronics, vol. 8, no. 11, 2019.spa
dc.relation.referencesU. Tamrakar, T. M. Hansen, R. Tonkoski, and D. A. Copp, “Model predictive frequency control of low inertia microgrids,” in 2019 IEEE 28th International Symposium on Industrial Electronics (ISIE), 2019, pp. 2111–2116.spa
dc.relation.referencesA. Parisio, C. Wiezorek, T. Kyntäjä, J. Elo, K. Strunz, and K. H. Johansson, “Coope- rative mpc-based energy management for networked microgrids,” IEEE Transactions on Smart Grid, vol. 8, no. 6, pp. 3066–3074, 2017.spa
dc.relation.referencesR. H. M. Zargar and M. H. Yaghmaee, “Energy exchange cooperative model in sdn-based interconnected multi-microgrids,” Sustainable Energy, Grids and Networks, vol. 27, p. 100491, 2021.spa
dc.relation.referencesH. Zou, S. Mao, Y. Wang, F. Zhang, X. Chen, and L. Cheng, “A survey of energy management in interconnected multi-microgrids,” IEEE Access, vol. 7, pp. 72 158– 72 169, 2019.spa
dc.relation.referencesF. Bandeiras, E. Pinheiro, M. Gomes, P. Coelho, and J. Fernandes, “Review of the cooperation and operation of microgrid clusters,” Renewable and Sustainable Energy Reviews, vol. 133, p. 110311, 2020.spa
dc.relation.referencesY. Guo, Q. Wu, H. Gao, S. Huang, B. Zhou, and C. Li, “Double-time-scale coordinated voltage control in active distribution networks based on mpc,” IEEE Transactions on Sustainable Energy, vol. 11, no. 1, pp. 294–303, 2020.spa
dc.relation.referencesK. E. Antoniadou-Plytaria, I. N. Kouveliotis-Lysikatos, P. S. Georgilakis, and N. D. Hatziargyriou, “Distributed and decentralized voltage control of smart distribution networks: Models, methods, and future research,” IEEE Transactions on Smart Grid, vol. 8, no. 6, pp. 2999–3008, 2017.spa
dc.relation.referencesH. Sun, Q. Guo, J. Qi, V. Ajjarapu, R. Bravo, J. Chow, Z. Li, R. Moghe, E. Nasr- Azadani, U. Tamrakar, G. N. Taranto, R. Tonkoski, G. Valverde, Q. Wu, and G. Yang, “Review of challenges and research opportunities for voltage control in smart grids,” IEEE Transactions on Power Systems, vol. 34, no. 4, pp. 2790–2801, 2019.spa
dc.relation.referencesF. Dörfler, S. Bolognani, J. W. Simpson-Porco, and S. Grammatico, “Distributed con- trol and optimization for autonomous power grids,” in 2019 18th European Control Conference (ECC), 2019, pp. 2436–2453.spa
dc.relation.referencesY. Guo, Q. Wu, H. Gao, X. Chen, J. Østergaard, and H. Xin, “Mpc-based coordinated voltage regulation for distribution networks with distributed generation and energy storage system,” IEEE Transactions on Sustainable Energy, vol. 10, no. 4, pp. 1731– 1739, 2019.spa
dc.relation.referencesX. Wu, C. Shen, and R. Iravani, “A distributed, cooperative frequency and voltage control for microgrids,” IEEE Transactions on Smart Grid, vol. 9, no. 4, pp. 2764– 2776, 2018.spa
dc.relation.referencesJ. Schiffer, T. Seel, J. Raisch, and T. Sezi, “Voltage stability and reactive power sharing in inverter-based microgrids with consensus-based distributed voltage control,” IEEE Transactions on Control Systems Technology, vol. 24, no. 1, pp. 96–109, 2016.spa
dc.relation.referencesY. Shan, J. Hu, Z. Li, and J. M. Guerrero, “A model predictive control for renewable energy based ac microgrids without any pid regulators,” IEEE Transactions on Power Electronics, vol. 33, no. 11, pp. 9122–9126, 2018.spa
dc.relation.referencesA. Parisio, E. Rikos, and L. Glielmo, “A model predictive control approach to microgrid operation optimization,” IEEE Transactions on Control Systems Technology, vol. 22, no. 5, pp. 1813–1827, 2014.spa
dc.relation.referencesD. A. Martínez, E. Mojica-Nava, A. S. Al-Sumaiti, and S. Rivera, “A distortion-based potential game for secondary voltage control in micro-grids,” IEEE Access, vol. 8, pp. 110 611–110 622, 2020.spa
dc.relation.referencesS. Mhanna, G. Verbič, and A. C. Chapman, “Adaptive admm for distributed ac optimal power flow,” IEEE Transactions on Power Systems, vol. 34, no. 3, pp. 2025–2035, 2019.spa
dc.relation.referencesJ. Xu, H. Sun, and C. J. Dent, “Admm-based distributed opf problem meets stochastic communication delay,” IEEE Transactions on Smart Grid, vol. 10, no. 5, pp. 5046– 5056, 2019.spa
dc.relation.referencesNorth American Electric Realiability Corporation, “Fast frequency response concepts and bps reliability needs,” North American Electric Realiability Corporation, Tech. Rep., 2020.spa
dc.relation.referencesA. Nedić, “Convergence rate of distributed averaging dynamics and optimization in networks,” Foundations and Trends® in Systems and Control, vol. 2, no. 1, pp. 1–100, 2015.spa
dc.relation.referencesA. Nedić and J. Liu, “Distributed optimization for control,” Annual Review of Control, Robotics, and Autonomous Systems, vol. 1, no. 1, pp. 77–103, 2018.spa
dc.relation.referencesF. Morbidi, “Functions of the laplacian matrix with application to distributed formation control,” IEEE Transactions on Control of Network Systems, vol. 9, no. 3, pp. 1459–1467, 2022.spa
dc.relation.referencesM. Mesbahi and M. Egerstedt, Graph Theoretic Methods in Multiagent Networks. Princeton: Princeton University Press, 2010.spa
dc.relation.referencesS. P. Boyd and L. Vandenberghe, Convex optimization. Cambridge university press, 2004.spa
dc.relation.referencesMathWorks® , “Quadratic programming - MATLAB quadprog,” Accessed May. 01, 2022 [Online]. Available: https://www.mathworks.com/help/optim/ug/quadprog. html.spa
dc.relation.referencesY. Okuyama, Discrete control systems. Springer, 2014.spa
dc.relation.referencesK. Ogata, Sistemas de control en tiempo discreto. Pearson educación, 1996.spa
dc.relation.referencesQ. Zhou, M. Shahidehpour, A. Paaso, S. Bahramirad, A. Alabdulwahab, and A. Abusorrah, “Distributed control and communication strategies in networked microgrids,” IEEE Communications Surveys Tutorials, vol. 22, no. 4, pp. 2586–2633, 2020.spa
dc.relation.referencesB. Zhou, J. Zou, C. Y. Chung, H. Wang, N. Liu, N. Voropai, and D. Xu, “Multimicrogrid energy management systems: Architecture, communication, and scheduling strategies,” Journal of Modern Power Systems and Clean Energy, vol. 9, no. 3, pp. 463–476, 2021.spa
dc.relation.referencesA. Hirsch, Y. Parag, and J. Guerrero, “Microgrids: A review of technologies, key drivers, and outstanding issues,” Renewable and Sustainable Energy Reviews, vol. 90, pp. 402–411, 2018.spa
dc.relation.referencesA. Cagnano, E. De Tuglie, and P. Mancarella, “Microgrids: Overview and guidelines for practical implementations and operation,” Applied Energy, vol. 258, p. 114039, 2020.spa
dc.relation.referencesN. Pogaku, M. Prodanovic, and T. C. Green, “Modeling, analysis and testing of autonomous operation of an inverter-based microgrid,” IEEE Transactions on Power Electronics, vol. 22, no. 2, pp. 613–625, 2007.spa
dc.relation.referencesM. Ahmed, L. Meegahapola, A. Vahidnia, and M. Datta, “Stability and control aspects of microgrid architectures–a comprehensive review,” IEEE Access, vol. 8, pp. 144 730–144 766, 2020.spa
dc.relation.referencesN. S., S. K.N., J. E.A., and T. P. I. Ahamed, “Comparative analysis of communication assisted grid synchronization methods in microgrids,” IEEE Systems Journal, vol. 14, no. 1, pp. 1007–1014, 2020.spa
dc.relation.referencesD. Kumar, F. Zare, and A. Ghosh, “Dc microgrid technology: System architectures, ac grid interfaces, grounding schemes, power quality, communication networks, applications, and standardizations aspects,” IEEE Access, vol. 5, pp. 12 230–12 256, 2017.spa
dc.relation.referencesI. Serban, S. Céspedes, C. Marinescu, C. A. Azurdia-Meza, J. S. Gómez, and D. S. Hueichapan, “Communication requirements in microgrids: A practical survey,” IEEE Access, vol. 8, pp. 47 694–47 712, 2020.spa
dc.relation.referencesW.-J. Ma, J. Wang, V. Gupta, and C. Chen, “Distributed energy management for networked microgrids using online admm with regret,” IEEE Transactions on Smart Grid, vol. 9, no. 2, pp. 847–856, 2018.spa
dc.relation.referencesH. Wang and J. Huang, “Incentivizing energy trading for interconnected microgrids,” IEEE Transactions on Smart Grid, vol. 9, no. 4, pp. 2647–2657, 2018.spa
dc.relation.referencesL. Mariam, M. Basu, and M. F. Conlon, “Microgrid: Architecture, policy and future trends,” Renewable and Sustainable Energy Reviews, vol. 64, pp. 477–489, 2016.spa
dc.relation.referencesA. Ahl, M. Yarime, K. Tanaka, and D. Sagawa, “Review of blockchain-based distributed energy: Implications for institutional development,” Renewable and Sustainable Energy Reviews, vol. 107, pp. 200–211, 2019.spa
dc.relation.referencesP. Vorobev, P. Huang, M. Al Hosani, J. L. Kirtley, and K. Turitsyn, “High-fidelity model order reduction for microgrids stability assessment,” IEEE Transactions on Power Systems, vol. 33, no. 1, pp. 874–887, 2018.spa
dc.relation.referencesZ. Li, S. Bahramirad, A. Paaso, M. Yan, and M. Shahidehpour, “Blockchain for decentralized transactive energy management system in networked microgrids,” The Electricity Journal, vol. 32, no. 4, pp. 58–72, 2019, special Issue on Strategies for a sustainable, reliable and resilient grid.spa
dc.relation.referencesY. Wang, T.-L. Nguyen, Y. Xu, Q.-T. Tran, and R. Caire, “Peer-to-peer control for networked microgrids: Multi-layer and multi-agent architecture design,” IEEE Transactions on Smart Grid, vol. 11, no. 6, pp. 4688–4699, 2020.spa
dc.relation.referencesX. Zhou, L. Zhou, Y. Chen, J. M. Guerrero, A. Luo, W. Wu, and L. Yang, “A microgrid cluster structure and its autonomous coordination control strategy,” International Journal of Electrical Power & Energy Systems, vol. 100, pp. 69–80, 2018.spa
dc.relation.referencesZ. Tang, P. Zhang, W. O. Krawec, and Z. Jiang, “Programmable quantum networked microgrids,” IEEE Transactions on Quantum Engineering, vol. 1, pp. 1–13, 2020.spa
dc.relation.referencesH. Farzin, M. Fotuhi-Firuzabad, and M. Moeini-Aghtaie, “Enhancing power system resilience through hierarchical outage management in multi-microgrids,” IEEE Transactions on Smart Grid, vol. 7, no. 6, pp. 2869–2879, 2016.spa
dc.relation.referencesY. Wang, A. O. Rousis, and G. Strbac, “On microgrids and resilience: A comprehensive review on modeling and operational strategies,” Renewable and Sustainable Energy Reviews, vol. 134, p. 110313, 2020.spa
dc.relation.referencesW. Xu, J. Li, M. Dehghani, and M. GhasemiGarpachi, “Blockchain-based secure energy policy and management of renewable-based smart microgrids,” Sustainable Cities and Society, vol. 72, p. 103010, 2021.spa
dc.relation.referencesR. Aboli, M. Ramezani, and H. Falaghi, “A hybrid robust distributed model for short-term operation of multi-microgrid distribution networks,” Electric Power Systems Research, vol. 177, p. 106011, 2019.spa
dc.relation.referencesM. A. Jirdehi, V. S. Tabar, S. Ghassemzadeh, and S. Tohidi, “Different aspects of microgrid management: A comprehensive review,” Journal of Energy Storage, vol. 30, p. 101457, 2020.spa
dc.relation.referencesV. K. Sood and H. Abdelgawad, “Chapter 1 - microgrids architectures,” in Distributed Energy Resources in Microgrids, R. K. Chauhan and K. Chauhan, Eds. Academic Press, 2019, pp. 1–31.spa
dc.relation.referencesE. Bullich-Massagué, F. Díaz-González, M. Aragüés-Peñalba, F. Girbau-Llistuella, P. Olivella-Rosell, and A. Sumper, “Microgrid clustering architectures,” Applied Energy, vol. 212, pp. 340–361, 2018.spa
dc.relation.referencesY. C. C. Wong, C. S. Lim, M. D. Rotaru, A. Cruden, and X. Kong, “Consensus virtual output impedance control based on the novel droop equivalent impedance concept for a multi-bus radial microgrid,” IEEE Transactions on Energy Conversion, vol. 35, no. 2, pp. 1078–1087, 2020.spa
dc.relation.referencesF. Dörfler, J. W. Simpson-Porco, and F. Bullo, “Breaking the hierarchy: Distributed control and economic optimality in microgrids,” IEEE Transactions on Control of Network Systems, vol. 3, no. 3, pp. 241–253, 2016.spa
dc.relation.referencesU. Orji, C. Schantz, S. B. Leeb, J. L. Kirtley, B. Sievenpiper, K. Gerhard, and T. McCoy, “Adaptive zonal protection for ring microgrids,” IEEE Transactions on Smart Grid, vol. 8, no. 4, pp. 1843–1851, 2017.spa
dc.relation.referencesZ. Tang, Y. Qin, Z. Jiang, W. O. Krawec, and P. Zhang, “Quantum-secure microgrid,” IEEE Transactions on Power Systems, vol. 36, no. 2, pp. 1250–1263, 2021.spa
dc.relation.referencesA. Renjit, “Chapter 10 - communications, cybersecurity, and the internet of things for microgrids,” in Distributed Energy Resources in Microgrids, R. K. Chauhan and K. Chauhan, Eds. Academic Press, 2019, pp. 275–290.spa
dc.relation.referencesY. Han, K. Zhang, H. Li, E. A. A. Coelho, and J. M. Guerrero, “Mas-based distributed coordinated control and optimization in microgrid and microgrid clusters: A comprehensive overview,” IEEE Transactions on Power Electronics, vol. 33, no. 8, pp. 6488–6508, 2018.spa
dc.relation.referencesM. Starke, A. Herron, D. King, and Y. Xue, “Implementation of a publish-subscribe protocol in microgrid islanding and resynchronization with self-discovery,” IEEE Transactions on Smart Grid, vol. 10, no. 1, pp. 361–370, 2019.spa
dc.relation.referencesS. A. Alavi, K. Mehran, Y. Hao, A. Rahimian, H. Mirsaeedi, and V. Vahidinasab, “A distributed event-triggered control strategy for dc microgrids based on publish-subscribe model over industrial wireless sensor networks,” IEEE Transactions on Smart Grid, vol. 10, no. 4, pp. 4323–4337, 2019.spa
dc.relation.referencesK. Umer, Q. Huang, M. Khorasany, M. Afzal, and W. Amin, “A novel communication efficient peer-to-peer energy trading scheme for enhanced privacy in microgrids,” Applied Energy, vol. 296, p. 117075, 2021.spa
dc.relation.referencesY. Zhou, J. Wu, C. Long, and W. Ming, “State-of-the-art analysis and perspectives for peer-to-peer energy trading,” Engineering, vol. 6, no. 7, pp. 739–753, 2020.spa
dc.relation.referencesC. Zhang, J. Wu, Y. Zhou, M. Cheng, and C. Long, “Peer-to-peer energy trading in a microgrid,” Applied Energy, vol. 220, pp. 1–12, 2018.spa
dc.relation.referencesA. Werth, A. André, D. Kawamoto, T. Morita, S. Tajima, M. Tokoro, D. Yanagidaira, and K. Tanaka, “Peer-to-peer control system for dc microgrids,” IEEE Transactions on Smart Grid, vol. 9, no. 4, pp. 3667–3675, 2018.spa
dc.relation.referencesJ. Lai, X. Lu, F. Wang, P. Dehghanian, and R. Tang, “Broadcast gossip algorithms for distributed peer-to-peer control in ac microgrids,” IEEE Transactions on Industry Applications, vol. 55, no. 3, pp. 2241–2251, 2019.spa
dc.relation.referencesJ. Lai, X. Lu, X. Yu, and A. Monti, “Stochastic distributed secondary control for ac microgrids via event-triggered communication,” IEEE Transactions on Smart Grid, vol. 11, no. 4, pp. 2746–2759, 2020.spa
dc.relation.referencesL. Ding, Q.-L. Han, and X.-M. Zhang, “Distributed secondary control for active power sharing and frequency regulation in islanded microgrids using an event-triggered communication mechanism,” IEEE Transactions on Industrial Informatics, vol. 15, no. 7, pp. 3910–3922, 2019.spa
dc.relation.referencesZ. Tang, Y. Qin, Z. Jiang, W. O. Krawec, and P. Zhang, “Quantum-secure networked microgrids,” in 2020 IEEE Power Energy Society General Meeting (PESGM), 2020, pp. 1–5.spa
dc.relation.referencesA. Meeuw, S. Schopfer, A. Wörner, V. Tiefenbeck, L. Ableitner, E. Fleisch, and F. Wortmann, “Implementing a blockchain-based local energy market: Insights on communication and scalability,” Computer Communications, vol. 160, pp. 158–171, 2020.spa
dc.relation.referencesS. Sen and V. Kumar, “Microgrid modelling: A comprehensive survey,” Annual Reviews in Control, vol. 46, pp. 216–250, 2018.spa
dc.relation.referencesZ. Shuai, Y. Peng, X. Liu, Z. Li, J. M. Guerrero, and Z. J. Shen, “Dynamic equivalent modeling for multi-microgrid based on structure preservation method,” IEEE Transactions on Smart Grid, vol. 10, no. 4, pp. 3929–3942, 2019.spa
dc.relation.referencesY. Li, Z. Wang, J. Yang, X. Wang, and J. Feng, “Dynamic equivalence modeling for microgrid cluster by using physical-data-driven method,” IEEE Transactions on Applied Superconductivity, vol. 31, no. 8, pp. 1–4, 2021.spa
dc.relation.referencesC. Cai, H. Liu, Y. Tao, Z. Deng, W. Dai, and J. Chen, “Microgrid equivalent modeling based on long short-term memory neural network,” IEEE Access, vol. 8, pp. 23120–23133, 2020.spa
dc.relation.referencesM. Sharifzadeh, A. Sikinioti-Lock, and N. Shah, “Machine-learning methods for integrated renewable power generation: A comparative study of artificial neural networks, support vector regression, and gaussian process regression,” Renewable and Sustainable Energy Reviews, vol. 108, pp. 513–538, 2019.spa
dc.relation.referencesK. P. Kumar and B. Saravanan, “Recent techniques to model uncertainties in power generation from renewable energy sources and loads in microgrids – a review,” Renewable and Sustainable Energy Reviews, vol. 71, pp. 348–358, 2017.spa
dc.relation.referencesH. Xiao, W. Pei, W. Deng, L. Kong, H. Sun, and C. Tang, “A comparative study of deep neural network and meta-model techniques in behavior learning of microgrids,” IEEE Access, vol. 8, pp. 30 104–30 118, 2020.spa
dc.relation.referencesJ. Schiffer, D. Zonetti, R. Ortega, A. M. Stanković, T. Sezi, and J. Raisch, “A survey on modeling of microgrids—From fundamental physics to phasors and voltage sources,” Automatica, vol. 74, pp. 135–150, 2016.spa
dc.relation.referencesU. B. Tayab, M. A. B. Roslan, L. J. Hwai, and M. Kashif, “A review of droop control techniques for microgrid,” Renewable and Sustainable Energy Reviews, vol. 76, pp. 717–727, 2017.spa
dc.relation.referencesT. Yang, X. Yi, J. Wu, Y. Yuan, D. Wu, Z. Meng, Y. Hong, H. Wang, Z. Lin, and K. H. Johansson, “A survey of distributed optimization,” Annual Reviews in Control, vol. 47, pp. 278–305, 2019.spa
dc.relation.referencesD. K. Molzahn, F. Dörfler, H. Sandberg, S. H. Low, S. Chakrabarti, R. Baldick, and J. Lavaei, “A survey of distributed optimization and control algorithms for electric power systems,” IEEE Transactions on Smart Grid, vol. 8, no. 6, pp. 2941–2962, 2017.spa
dc.relation.referencesJ. Wangni, J. Wang, J. Liu, and T. Zhang, “Gradient sparsification for communicationefficient distributed optimization,” Advances in Neural Information Processing Systems, vol. 31, 2018.spa
dc.relation.referencesL. Grüne and J. Pannek, Nonlinear Model Predictive Control. Springer International Publishing, 2017.spa
dc.relation.referencesL. Yang, J. Luo, Y. Xu, Z. Zhang, and Z. Dong, “A distributed dual consensus ADMM based on partition for DC-DOPF with carbon emission trading,” IEEE Transactions on Industrial Informatics, vol. 16, no. 3, pp. 1858–1872, 2020.spa
dc.relation.referencesE. De Din, M. Josevski, M. Pau, F. Ponci, and A. Monti, “Distributed model predictive voltage control for distribution grid based on relaxation and successive distributed decomposition,” IEEE Access, vol. 10, pp. 50 508–50 522, 2022.spa
dc.relation.referencesY. Wang, S. Wang, and L. Wu, “Distributed optimization approaches for emerging power systems operation: A review,” Electric Power Systems Research, vol. 144, pp. 127–135, 2017.spa
dc.relation.referencesW. Jiang and T. Charalambous, “Distributed alternating direction method of multipliers using finite-time exact ratio consensus in digraphs,” in 2021 European Control Conference (ECC), 2021, pp. 2205–2212.spa
dc.relation.referencesV. Khatana and M. V. Salapaka, “D-DistADMM: A O(1/k) distributed ADMM for distributed optimization in directed graph topologies,” in 2020 59th IEEE Conference on Decision and Control (CDC), 2020, pp. 2992–2997.spa
dc.rights.accessrightsinfo:eu-repo/semantics/openAccessspa
dc.rights.licenseAtribución-NoComercial 4.0 Internacionalspa
dc.rights.urihttp://creativecommons.org/licenses/by-nc/4.0/spa
dc.subject.ddc620 - Ingeniería y operaciones afines::629 - Otras ramas de la ingenieríaspa
dc.subject.proposalOptimizaciónspa
dc.subject.proposalMicrorredes Interconectadasspa
dc.subject.proposalADMMspa
dc.subject.proposalMPCspa
dc.subject.proposalOptimizationeng
dc.subject.proposalNetworked Microgridseng
dc.subject.proposalADMMeng
dc.subject.proposalMPCeng
dc.subject.wikidataSistema de control distribuidospa
dc.subject.wikidatadistributed control systemeng
dc.subject.wikidataTensión (electricidad)spa
dc.subject.wikidatavoltageeng
dc.subject.wikidataMicrogridspa
dc.subject.wikidatamicrogrideng
dc.titleControl de voltaje de múltiples microrredes basado en optimización distribuidaspa
dc.title.translatedVoltage control of networked microgrids based on distributed optimizationeng
dc.typeTrabajo de grado - Maestríaspa
dc.type.coarhttp://purl.org/coar/resource_type/c_bdccspa
dc.type.coarversionhttp://purl.org/coar/version/c_ab4af688f83e57aaspa
dc.type.contentTextspa
dc.type.driverinfo:eu-repo/semantics/masterThesisspa
dc.type.redcolhttp://purl.org/redcol/resource_type/TMspa
dc.type.versioninfo:eu-repo/semantics/acceptedVersionspa
dcterms.audience.professionaldevelopmentInvestigadoresspa
dcterms.audience.professionaldevelopmentPúblico generalspa
oaire.accessrightshttp://purl.org/coar/access_right/c_abf2spa

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