Power system operation considering detailed modelling of energy storage systems
The power system operation considering energy storage systems (ESS) and renew-able power represents a challenge. In a 24-hour economic dispatch, the generationresources are dispatched to meet demand requirements considering network restric-tions. The uncertainty and unpredictability associated with...
- Autores:
-
Cantillo Luna, Sergio Alejandro
Moreno-Chuquen, Ricardo
- Tipo de recurso:
- Article of journal
- Fecha de publicación:
- 2020
- Institución:
- Universidad Autónoma de Occidente
- Repositorio:
- RED: Repositorio Educativo Digital UAO
- Idioma:
- eng
- OAI Identifier:
- oai:red.uao.edu.co:10614/13263
- Acceso en línea:
- https://hdl.handle.net/10614/13263
- Palabra clave:
- Almacenamiento de energía
Producción de energía eléctrica
Energy storage
Wind power
Electric power production
Energy storage systems
Generation dispatch
Optimal power flow
Renewables sources
- Rights
- openAccess
- License
- https://creativecommons.org/licenses/by-nc-nd/4.0/
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Power system operation considering detailed modelling of energy storage systems |
| title |
Power system operation considering detailed modelling of energy storage systems |
| spellingShingle |
Power system operation considering detailed modelling of energy storage systems Almacenamiento de energía Producción de energía eléctrica Energy storage Wind power Electric power production Energy storage systems Generation dispatch Optimal power flow Renewables sources |
| title_short |
Power system operation considering detailed modelling of energy storage systems |
| title_full |
Power system operation considering detailed modelling of energy storage systems |
| title_fullStr |
Power system operation considering detailed modelling of energy storage systems |
| title_full_unstemmed |
Power system operation considering detailed modelling of energy storage systems |
| title_sort |
Power system operation considering detailed modelling of energy storage systems |
| dc.creator.fl_str_mv |
Cantillo Luna, Sergio Alejandro Moreno-Chuquen, Ricardo |
| dc.contributor.author.none.fl_str_mv |
Cantillo Luna, Sergio Alejandro Moreno-Chuquen, Ricardo |
| dc.subject.armarc.spa.fl_str_mv |
Almacenamiento de energía Producción de energía eléctrica |
| topic |
Almacenamiento de energía Producción de energía eléctrica Energy storage Wind power Electric power production Energy storage systems Generation dispatch Optimal power flow Renewables sources |
| dc.subject.armarc.eng.fl_str_mv |
Energy storage Wind power Electric power production |
| dc.subject.proposal.eng.fl_str_mv |
Energy storage systems Generation dispatch Optimal power flow Renewables sources |
| description |
The power system operation considering energy storage systems (ESS) and renew-able power represents a challenge. In a 24-hour economic dispatch, the generationresources are dispatched to meet demand requirements considering network restric-tions. The uncertainty and unpredictability associated with renewable resources andstorage systems represents challenges for power system operation due to operationaland economical restrictions. This paper developed a detailed formulation to modelenergy storage systems (ESS) and renewable sources for power system operation in aDCOPF approach considering a 24-hour period. The model is formulated and evalu-ated with two different power systems (i.e. 5-bus and IEEE modified 24-bus systems).Wind availability patterns and scenarios are used to assess the ESS performance un-der different operational circumstances. With regard to the systems proposed, thereare scenarios in order to evaluate ESS performance. In one of them, the increase incapacity did not represent significant savings or performance for the system, while inthe other it was quite the opposite especially during peak load periods |
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2020 |
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2020-02 |
| dc.date.accessioned.none.fl_str_mv |
2021-09-27T01:18:18Z |
| dc.date.available.none.fl_str_mv |
2021-09-27T01:18:18Z |
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Artículo de revista |
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http://purl.org/coar/resource_type/c_2df8fbb1 |
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http://purl.org/coar/resource_type/c_6501 |
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http://purl.org/redcol/resource_type/ART |
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20888708 |
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eng |
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eng |
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Volumen 11, número 1 (2020) |
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200 |
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1 |
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182 |
| dc.relation.citationvolume.spa.fl_str_mv |
Volumen 11 |
| dc.relation.cites.eng.fl_str_mv |
Cantillo Luna, S.A., Moreno, R. (2020). Power system operation considering detailed modelling of energy storage systems. International Journal of Electrical and Computer Engineering. (Vol. 11 (1), pp. 182-200. DOI: 10.11591/ijece.v11i1.pp182-200 |
| dc.relation.ispartofjournal.eng.fl_str_mv |
International Journal of Electrical and Computer Engineering |
| dc.relation.references.spa.fl_str_mv |
U. S. DOE, “Staff report to the secretary on electricity markets and reliability,” U.S. Department of Energy, 2017. O. Ellabban, H. Abu-Rub, and F. Blaabjerg, “Renewable energy resources: Current status, future prospects and their enabling technology,” Renewable and Sustainable Energy Reviews, vol. 39, pp. 748- 764, 2014. L. E. Jones, “Renewable energy integration: practical management of variability, uncertainty, and flexibility in power grids,” Academic Press, 2017. A. Foley and I. D. Lobera, “Impacts of compressed air energy storage plant on an electricity market with a large renewable energy portfolio,” Energy, vol. 57, pp. 85-94, 2013. A. Foley and A. G. Olabi, “Renewable energy technology developments, trends and policy implications that can underpin the drive for global climate change,” Renewable and Sustainable Energy Reviews, vol. 68, 2017. I. E. Agency, Renewables Information 2019. OECD Publishing, 2019. [Online]. Available: https://www.oecd-ilibrary.org/content/publication/fa89fd56-en J. M. Morales, A. J. Conejo, and J. Perez-Ruiz, “Short-term trading for a wind power producer,” IEEE Transactions on Power Systems, vol. 25, no. 1, pp. 554-564, 2010. S. S. Sakthi, R. Santhi, N. M. Krishnan, S. Ganesan, and S. Subramanian, “Wind integrated thermal unit commitment solution using grey wolf optimizer,” International Journal of Electrical and Computer Engineering (IJECE), vol. 7, no. 5, pp. 2309-2320, 2017. K. Rabyi and H. Mahmoudi, “Energy storage of dfig based wind farm using d-statcom,” International Journal of Electrical and Computer Engineering (IJECE), vol. 9, no. 2, pp. 761-770, 2019. A. Abdulla and T. Jiang, “Impact of compressed air energy storage system into diesel power plant with wind power penetration,” International Journal of Electrical and Computer Engineering (IJECE), vol. 9, no. 3, pp. 1553-1560, 2019. N. T. A. Nguyen, “Optimal planning of energy storage systems considering uncertainty,” Ph.D. dissertation, Politecnico di Milano, 2016. F. Nadeem, et al., “Comparative review of energy storage systems, their roles, and impacts on future power systems,” IEEE Access, vol. 7, pp. 4555–4585, 2018. X. Yu, X. Dong, S. Pang, L. Zhou, and H. Zang, “Energy storage sizing optimization and sensitivity analysis based on wind power forecast error compensation,” Energies, vol. 12, no. 24, 2019. J. Rugolo and M. J. Aziz, “Electricity storage for intermittent renewable sources,” Energy and Environmental Science, vol. 5, no. 5, pp. 7151-7160, 2012. N. Chowdhury, F. Pilo, and G. Pisano, “Optimal energy storage system positioning and sizing with robust optimization,” Energies, vol. 13, no. 3, p. 512, 2020. C. K. Das, O. Bass, G. Kothapalli, T. S. Mahmoud, and D. Habibi, “Overview of energy storage systems in distribution networks: Placement, sizing, operation, and power quality,” Renewable and Sustainable Energy Reviews, vol. 91, pp. 1205-1230, 2018. R. Moreno-Chuquen and J. Obando-Ceron, “Network topological notions for power systems security assessment,” International Review of Electrical Engineering (IREE), vol. 13, no. 3, pp. 237-258, 2018. R. Moreno-Chuquen and O. Florez-Cediel, “Online dynamic assessment of system stability in power systems using the unscented kalman filter,” International Review of Electrical Engineering (IREE), vol. 14, no. 6, 2019. H. R. Chamorro, et al., “Non-synchronous generation impact on power systems coherency,” IET Generation, Transmission and Distribution, vol. 10, no. 10, pp. 2443-2453, 2016. U. S. DOE, “Solving challenges in energy storage,” U.S. Department of Energy, 2018. A. Conejo and L. Baringo, ”Power System Operations,” Springer, 2018. H. Chamorro, M. Ghandhari, and R. Eriksson, “Wind power impact on power system frequency response,” North American Power Symposium (NAPS), pp. 1-6, 2013. Z. Li, Y. Cao, L. V. Dai, X. Yang, T. T. Nguyen et al., “Optimal power flow for transmission power networks using a novel metaheuristic algorithm,” Energies, vol. 12, no. 22, 2019. A. Gabash and P. Li, “Active-reactive optimal power flow in distribution networks with embedded generation and battery storage,” IEEE Transactions on Power Systems, vol. 27, no. 4, pp. 2026-2035, 2012. L. Ran, L. Zhengyu, and C. Zhen, “Economic dispatch of off-grid photovoltaic generation system with hybrid energy storage,” 2nd IEEE Conference on Energy Internet and Energy System Integration (EI2), pp. 1-6, 2018. L. Zhou, Y. Huang, K. Guo, and Y. Feng, “A survey of energy storage technology for micro grid,” Power System Protection and Control, vol. 39, no. 7, pp. 147-152, 2011. I. Yahyaoui, ”Advances in Renewable Energies and Power Technologies: Volume 1: Solar and Wind Energies,” Elsevier, 2018. R. A. Jabr, “Adjustable robust OPF with renewable energy sources,” IEEE Transactions on Power Systems, vol. 28, no. 4, pp. 4742-4751, 2013. A. Castillo and D. F. Gayme, “Profit maximizing storage allocation in power grids,” 52nd IEEE Conference on Decision and Control, pp. 429-435, 2013. T. Geetha and V. Jayashankar, “Generation dispatch with storage and renewables under availability based tariff,” TENCON 2008-2008 IEEE Region 10 Conference, pp. 1-6, 2008. A. Castillo and D. F. Gayme, “Evaluating the effects of real power losses in optimal power flow-based storage integration,” IEEE Transactions on Control of Network Systems, vol. 5, no. 3, pp. 1132-1145, 2018. H. Sharifzadeh, N. Amjady, and H. Zareipour, “Multi-period stochastic security-constrained opf considering the uncertainty sources of wind power, load demand and equipment unavailability,” Electric Power Systems Research, vol. 146, pp. 33-42, 2017. C. Boonchuay, K. Tomsovic, F. Li, and W. Ongsakul, “Robust optimization-based DC optimal power flow for managing wind generation uncertainty,” AIP Conference Proceedings, vol. 1499. pp. 31-35, 2012. J. Obando-Ceron and R. Moreno-Chuquen, “Impacts of demand response under wind power uncertainty in network-constrained electricity markets,” IEEE ANDESCON, pp. 1-5, 2018. R. Azami, M. Sadegh Javadi, and G. Hematipour, “Economic load dispatch and DC-optimal power flow problem-PSO versus LR,” International Journal of Multidisciplinary Sciences and Engineering, vol. 2, no. 9, pp. 8-13, 2011. K. Seong-Cheol and S. R. Salkuti, “Optimal power flow based congestion management using enhanced genetic algorithms,” International Journal of Electrical and Computer Engineering (IJECE), vol. 9, no. 2, pp. 875-883, 2019. J. S. Obando, G. Gonzalez, and R. Moreno, “Quantification of operating reserves with high penetration of wind power considering extreme values,” International Journal of Electrical and Computer Engineering, vol. 10, no. 2, pp. 1693-1700, 2020. R. Subramanian, K. Thanushkodi, and A. Prakash, “An efficient meta heuristic algorithm to solve economic load dispatch problems,” Iranian Journal of Electrical and Electronic Engineering, vol. 9, no. 4, pp. 246-252, 2013. H. Sadeghian and M. Ardehali, “A novel approach for optimal economic dispatch scheduling of integrated combined heat and power systems for maximum economic profit and minimum environmental emissions based on benders decomposition,” Energy, vol. 102, pp. 1-23, 2016. E. Mojica-Nava, S. Rivera, and N. Quijano, “Game-theoretic dispatch control in microgrids considering network losses and renewable distributed energy resources integration,” IET Generation, Transmission and Distribution, vol. 11, no. 6, pp. 1583–1590, 2017. R. Jabr and B. Pal, “Intermittent wind generation in optimal power flow dispatching,” IET Generation, Transmission and Distribution, vol. 3, pp. 66-74, 2009. H. Zhang and P. Li, “Probabilistic analysis for optimal power flow under uncertainty,” IET Generation, Transmission and Distribution, vol. 4, pp. 553-561, 2010. R. Entriken, A. Tuohy, and D. Brooks, “Stochastic optimal power flow in systems with wind power,” 2011 IEEE Power and Energy Society General Meeting, pp. 1-5, 2011. C. Saunders, “Point estimate method addressing correlated wind power for probabilistic optimal power flow,” IEEE Transactions on, Power Systems, vol. 29, pp. 1045-1054, 2014. A. Papavasiliou and S. Oren, “Multi-area stochastic unit commitment for high wind penetration in a transmission constrained network,” Operations Research, vol. 61, 2011. J. Obando-Ceron and R. Moreno-Chuquen, “Quantification of operating reserves with wind power in day-ahead dispatching,” IEEE ANDESCON, pp. 1-5, 2018. R. Moreno, J. Obando, and G. Gonzalez, “An integrated opf dispatching model with wind power and demand response for day-ahead markets,” International Journal of Electrical and Computer Engineering (IJECE), vol. 9, no. 4, pp. 2794-2802, 2019. A. Soroudi, ”Power System Optimization Modeling in GAMS,” Springer, 2017. M. Asaduz-Zaman, M. H. Rahaman, M. S. Reza, and M. M. Islam, “Coordinated control of interconnected microgrid and energy storage system,” International Journal of Electrical and Computer Engineering (IJECE), vol. 8, no. 6, pp. 4781-4789, 2018. B. Banhthasit, C. Jamroen, and S. Dechanupaprittha, “Optimal generation scheduling of power system for maximum renewable energy harvesting and power losses minimization,” International Journal of Electrical and Computer Engineering (IJECE), vol. 8, no. 4, pp. 1954-1966, 2018. R. Jabr, S. Karaki, and J. Korbane, “Robust multi-period opf with storage and renewables,” IEEE Transactions on Power Systems, vol. 30, pp. 2790-2799, 2015. Z. Wang, J. Zhong, D. Chen, Y. Lu, and K. Men, “A multi-period optimal power flow model including battery energy storage,” IEEE Power and Energy Society General Meeting, pp. 1-5, 2003. Y. Levron, J. M. Guerrero, and Y. Beck, “Optimal power flow in microgrids with energy storage,” IEEE Transactions on Power Systems, vol. 28, no. 3, pp. 3226–3234, 2013. A. Gonzalez-Castellanos, D. Pozo, and A. Bischi, “Detailed li-ion battery characterization model for economic operation,” International Journal of Electrical Power and Energy Systems, vol. 116, 2020. B. Eldridge, R. O’Neill, and A. 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Lubin, “Jump: A modeling language for mathematical optimization,” SIAM Review, vol. 59, no. 2, pp. 295-320, 2017 |
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J. Lujano-Rojas, G. Osorio, J. Matias, and J. Catal-ao, “A heuristic methodology to economic dispatch problem incorporating renewable power forecasting error and system reliability,” Renewable Energy, vol. 87, pp. 731-743, 2016. |
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Cantillo Luna, Sergio Alejandro83f94fa4be72d6c8cf3b1410b45cfe2bMoreno-Chuquen, Ricardof36efacf1d947d7410ab7d332d4147532021-09-27T01:18:18Z2021-09-27T01:18:18Z2020-0220888708https://hdl.handle.net/10614/13263The power system operation considering energy storage systems (ESS) and renew-able power represents a challenge. In a 24-hour economic dispatch, the generationresources are dispatched to meet demand requirements considering network restric-tions. The uncertainty and unpredictability associated with renewable resources andstorage systems represents challenges for power system operation due to operationaland economical restrictions. This paper developed a detailed formulation to modelenergy storage systems (ESS) and renewable sources for power system operation in aDCOPF approach considering a 24-hour period. The model is formulated and evalu-ated with two different power systems (i.e. 5-bus and IEEE modified 24-bus systems).Wind availability patterns and scenarios are used to assess the ESS performance un-der different operational circumstances. With regard to the systems proposed, thereare scenarios in order to evaluate ESS performance. In one of them, the increase incapacity did not represent significant savings or performance for the system, while inthe other it was quite the opposite especially during peak load periods19 páginasapplication/pdfengInternational Journal of Electrical and Computer Engineeringhttps://creativecommons.org/licenses/by-nc-nd/4.0/info:eu-repo/semantics/openAccessAtribución-NoComercial-SinDerivadas 4.0 Internacional (CC BY-NC-ND 4.0)http://purl.org/coar/access_right/c_abf2Power system operation considering detailed modelling of energy storage systemsArtículo de revistahttp://purl.org/coar/resource_type/c_6501http://purl.org/coar/resource_type/c_2df8fbb1Textinfo:eu-repo/semantics/articlehttp://purl.org/redcol/resource_type/ARTinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/version/c_970fb48d4fbd8a85Almacenamiento de energíaProducción de energía eléctricaEnergy storageWind powerElectric power productionEnergy storage systemsGeneration dispatchOptimal power flowRenewables sourcesVolumen 11, número 1 (2020)2001182Volumen 11Cantillo Luna, S.A., Moreno, R. (2020). Power system operation considering detailed modelling of energy storage systems. International Journal of Electrical and Computer Engineering. (Vol. 11 (1), pp. 182-200. DOI: 10.11591/ijece.v11i1.pp182-200International Journal of Electrical and Computer EngineeringU. S. DOE, “Staff report to the secretary on electricity markets and reliability,” U.S. Department of Energy, 2017.O. Ellabban, H. Abu-Rub, and F. Blaabjerg, “Renewable energy resources: Current status, future prospects and their enabling technology,” Renewable and Sustainable Energy Reviews, vol. 39, pp. 748- 764, 2014.L. E. Jones, “Renewable energy integration: practical management of variability, uncertainty, and flexibility in power grids,” Academic Press, 2017.A. Foley and I. D. Lobera, “Impacts of compressed air energy storage plant on an electricity market with a large renewable energy portfolio,” Energy, vol. 57, pp. 85-94, 2013.A. Foley and A. G. Olabi, “Renewable energy technology developments, trends and policy implications that can underpin the drive for global climate change,” Renewable and Sustainable Energy Reviews, vol. 68, 2017.I. E. Agency, Renewables Information 2019. OECD Publishing, 2019. [Online]. Available: https://www.oecd-ilibrary.org/content/publication/fa89fd56-enJ. M. Morales, A. J. Conejo, and J. Perez-Ruiz, “Short-term trading for a wind power producer,” IEEE Transactions on Power Systems, vol. 25, no. 1, pp. 554-564, 2010.S. S. Sakthi, R. Santhi, N. M. Krishnan, S. Ganesan, and S. Subramanian, “Wind integrated thermal unit commitment solution using grey wolf optimizer,” International Journal of Electrical and Computer Engineering (IJECE), vol. 7, no. 5, pp. 2309-2320, 2017.K. Rabyi and H. Mahmoudi, “Energy storage of dfig based wind farm using d-statcom,” International Journal of Electrical and Computer Engineering (IJECE), vol. 9, no. 2, pp. 761-770, 2019.A. Abdulla and T. Jiang, “Impact of compressed air energy storage system into diesel power plant with wind power penetration,” International Journal of Electrical and Computer Engineering (IJECE), vol. 9, no. 3, pp. 1553-1560, 2019.N. T. A. Nguyen, “Optimal planning of energy storage systems considering uncertainty,” Ph.D. dissertation, Politecnico di Milano, 2016.F. Nadeem, et al., “Comparative review of energy storage systems, their roles, and impacts on future power systems,” IEEE Access, vol. 7, pp. 4555–4585, 2018.X. Yu, X. Dong, S. Pang, L. Zhou, and H. Zang, “Energy storage sizing optimization and sensitivity analysis based on wind power forecast error compensation,” Energies, vol. 12, no. 24, 2019.J. Rugolo and M. J. Aziz, “Electricity storage for intermittent renewable sources,” Energy and Environmental Science, vol. 5, no. 5, pp. 7151-7160, 2012.N. Chowdhury, F. Pilo, and G. Pisano, “Optimal energy storage system positioning and sizing with robust optimization,” Energies, vol. 13, no. 3, p. 512, 2020.C. K. Das, O. Bass, G. Kothapalli, T. S. Mahmoud, and D. Habibi, “Overview of energy storage systems in distribution networks: Placement, sizing, operation, and power quality,” Renewable and Sustainable Energy Reviews, vol. 91, pp. 1205-1230, 2018.R. Moreno-Chuquen and J. Obando-Ceron, “Network topological notions for power systems security assessment,” International Review of Electrical Engineering (IREE), vol. 13, no. 3, pp. 237-258, 2018.R. Moreno-Chuquen and O. Florez-Cediel, “Online dynamic assessment of system stability in power systems using the unscented kalman filter,” International Review of Electrical Engineering (IREE), vol. 14, no. 6, 2019.H. R. Chamorro, et al., “Non-synchronous generation impact on power systems coherency,” IET Generation, Transmission and Distribution, vol. 10, no. 10, pp. 2443-2453, 2016.U. S. DOE, “Solving challenges in energy storage,” U.S. Department of Energy, 2018.A. Conejo and L. Baringo, ”Power System Operations,” Springer, 2018.H. Chamorro, M. Ghandhari, and R. Eriksson, “Wind power impact on power system frequency response,” North American Power Symposium (NAPS), pp. 1-6, 2013.Z. Li, Y. Cao, L. V. Dai, X. Yang, T. T. Nguyen et al., “Optimal power flow for transmission power networks using a novel metaheuristic algorithm,” Energies, vol. 12, no. 22, 2019.A. Gabash and P. Li, “Active-reactive optimal power flow in distribution networks with embedded generation and battery storage,” IEEE Transactions on Power Systems, vol. 27, no. 4, pp. 2026-2035, 2012.L. Ran, L. Zhengyu, and C. Zhen, “Economic dispatch of off-grid photovoltaic generation system with hybrid energy storage,” 2nd IEEE Conference on Energy Internet and Energy System Integration (EI2), pp. 1-6, 2018.L. Zhou, Y. Huang, K. Guo, and Y. Feng, “A survey of energy storage technology for micro grid,” Power System Protection and Control, vol. 39, no. 7, pp. 147-152, 2011.I. Yahyaoui, ”Advances in Renewable Energies and Power Technologies: Volume 1: Solar and Wind Energies,” Elsevier, 2018.R. A. Jabr, “Adjustable robust OPF with renewable energy sources,” IEEE Transactions on Power Systems, vol. 28, no. 4, pp. 4742-4751, 2013.A. Castillo and D. F. Gayme, “Profit maximizing storage allocation in power grids,” 52nd IEEE Conference on Decision and Control, pp. 429-435, 2013.T. Geetha and V. Jayashankar, “Generation dispatch with storage and renewables under availability based tariff,” TENCON 2008-2008 IEEE Region 10 Conference, pp. 1-6, 2008.A. Castillo and D. F. Gayme, “Evaluating the effects of real power losses in optimal power flow-based storage integration,” IEEE Transactions on Control of Network Systems, vol. 5, no. 3, pp. 1132-1145, 2018.H. Sharifzadeh, N. Amjady, and H. 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Catal-ao, “A heuristic methodology to economic dispatch problem incorporating renewable power forecasting error and system reliability,” Renewable Energy, vol. 87, pp. 731-743, 2016.GeneralPublicationLICENSElicense.txtlicense.txttext/plain; charset=utf-81665https://dspace7-uao.metacatalogo.com/bitstreams/9ddd2ab9-d417-4940-8547-3bd47788e0e8/download20b5ba22b1117f71589c7318baa2c560MD52ORIGINAL00392_Power system operation considering detailed modelling of energy storage systems.pdf00392_Power system operation considering detailed modelling of energy storage systems.pdfTexto archivo completo del artículo de revista, PDFapplication/pdf1755640https://dspace7-uao.metacatalogo.com/bitstreams/a8861c31-24e5-470b-8cce-67012f0c799a/downloadf6015dead9ca2452a5a48585633e10a6MD53TEXT00392_Power system operation considering detailed modelling of energy storage systems.pdf.txt00392_Power system operation considering detailed modelling of energy storage systems.pdf.txtExtracted texttext/plain49464https://dspace7-uao.metacatalogo.com/bitstreams/a73a47f9-bf8e-41a9-a784-dda13fc10d60/download6fc5056c2676157e5bcd38975be33a51MD54THUMBNAIL00392_Power system operation considering detailed modelling of energy storage systems.pdf.jpg00392_Power system operation considering detailed modelling of energy storage systems.pdf.jpgGenerated Thumbnailimage/jpeg13112https://dspace7-uao.metacatalogo.com/bitstreams/663fef50-d3fd-4344-b640-0c64244b73f0/downloadf107e506e7910363966edf08c4ea0ac7MD5510614/13263oai:dspace7-uao.metacatalogo.com:10614/132632024-01-19 17:34:26.168https://creativecommons.org/licenses/by-nc-nd/4.0/open.accesshttps://dspace7-uao.metacatalogo.comRepositorio UAOrepositorio@uao.edu.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 |