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Quantification and analysis of flexibility in a power distribution network with penetration of non-conventional renewable sources
Cuantificación y análisis de la flexibilidad en una red de distribución de energía eléctrica con penetración de fuentes renovables no convencionales
DOI:
https://doi.org/10.15446/dyna.v91n231.110974Palabras clave:
flexibility; power distribution networks; renewable energy sources; electrical energy storage systems (en)flexibilidad; redes de distribución de energía eléctrica; fuentes de energía renovable; sistemas de almacenamiento de energía eléctrica. (es)
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This work shows the quantification of the flexibility in power distribution systems in the scenario in which non-conventional renewable sources are connected to it. From a set of metrics available in the literature, one is selected based on its applicability to operational and distribution system planning scenarios. The theoretical foundation and detail of its computational implementation is shown. On the basis of this, its calculation is addressed for a distribution system in which non-conventional renewable sources and storage systems are present. From the results it is possible to identify quantifiable characteristics of flexibility to the variation in the operation of this type of systems.
Este trabajo muestra la cuantificación de la flexibilidad en sistemas de distribución de energía eléctrica en el escenario en el cual se tienen fuentes renovables no convencionales conectados al mismo. A partir de un conjunto de métricas disponibles en la literatura, se selecciona una basada en su aplicabilidad a escenarios operativos y de planeación de sistemas de distribución. Se muestra el fundamento teórico y el detalle de su implementación computacional. Con base en esta, se aborda su cálculo para el caso de un sistema de distribución en el cual se tiene presencia de fuentes renovables no convencionales y sistemas de almacenamiento. A partir de los resultados es posible identificar características cuantificables de la flexibilidad ante la variación en la operación de este tipo de sistemas.
Referencias
Modi, A., Bühler, F., Andreasen, J.G., and Haglind, F., A review of solar energy-based heat and power generation systems, Renewable and Sustainable Energy Reviews, 67, pp. 1047–1064, 2017. DOI: https://doi.org/10.1016/j.rser.2016.09.075 DOI: https://doi.org/10.1016/j.rser.2016.09.075
Jha, S.K., Bilalovic, J., Jha, A., Patel, N., and Zhang, H., Renewable energy: present research and future scope of artificial intelligence, Renewable and Sustainable Energy Reviews, 77(May), pp. 297–317, 2017. DOI: https://doi.org/10.1016/j.rser.2017.04.018 DOI: https://doi.org/10.1016/j.rser.2017.04.018
Mohandes, B., Moursi, M.S.E., Hatziargyriou, N., and Khatib, S.E., A review of power system flexibility with high penetration of renewables, IEEE Transactions on Power Systems, 34(4), pp. 3140–3155, 2019. DOI: https://doi.org/10.1109/TPWRS.2019.2897727 DOI: https://doi.org/10.1109/TPWRS.2019.2897727
Raimi, D., Campbell, E., Newell, R., Prest, B., Villanueva, S. and Wingenroth, J., Global Energy Outlook 2022: turning points and tension in the energy transition a global energy outlook 2022: turning points and tension in the energy transition, N.A., 2022. [Online]. Available at: https://www.rff.org/publications/reports/global-energy-outlook-2022/
Bird, L., Cochran, J., and Wang, X., Wind and solar energy curtailment: experience and practices in the United States, National Renewable Energy Laboratory (NREL) (March), 2014, 58P, [Online]. Available at: http://www.osti.gov/servlets/purl/1126842/ DOI: https://doi.org/10.2172/1126842
Equipo Analitica XM ESP, “Pydataxm API XM.” GitHub, Inc., Medellin, 2022. [Online]. Available at: https://github.com/EquipoAnaliticaXM/API_XM
Eurelectric, Recommendations on the use of flexibility in distribution networks, (April), pp. 1–14, 2020, [Online]. Available at: https://www.eurelectric.org/media/4410/recommendations-on-the-use-of-flexibility-in-distribution-networks_proof-h-86B1B173.pdf
Papalexopoulos, A., Hansen, C., Frowd, R., Tuohy, A., and Lannoye, E., Impact of the transmission grid on the operational system flexibility, in 2016 Power Systems Computation Conference (PSCC), Genoa, Italy: IEEE, Jun. 2016, pp. 1–10. https://doi.org/10.1109/PSCC.2016.7541027. DOI: https://doi.org/10.1109/PSCC.2016.7541027
Abdin, I.F., and Zio, E., An integrated framework for operational flexibility assessment in multi-period power system planning with renewable energy production, Applied Energy, 222(April), pp. 898–914, 2018. DOI: https://doi.org/10.1016/j.apenergy.2018.04.009. DOI: https://doi.org/10.1016/j.apenergy.2018.04.009
Nosair, H., Member, S., Bouffard, F., and Member, S., Flexibility envelopes for power system operational planning, IEEE Transactions on Sustainable Energy, 6(3), pp. 800–809, 2015. DOI: https://doi.org/10.1109/TSTE.2015.2410760. DOI: https://doi.org/10.1109/TSTE.2015.2410760
Grid Modernization Laboratory Consortium, Grid Modernization: Metrics Analysis (GMLC1.1), 4(May), 2017. DOI: https://doi.org/10.13140/RG.2.2.31320.39681.
Hsieh, E., and Anderson, R., Grid flexibility: the quiet revolution, Electricity Journal, 30(2), pp. 1–8, 2017. DOI: https://doi.org/10.1016/j.tej.2017.01.009 DOI: https://doi.org/10.1016/j.tej.2017.01.009
North American Electric Reliability Corporation., Flexibility requirements and metrics for variable generation: implications for system planning studies, (NERC), North American Electric Reliability Corporation, Village Blvd, August, 2010. [Online]. Available at: https://www.nerc.com/pa/RAPA/ra/Reliability%20Assessments%20DL/IVGTF_Task_1_4_Final.pdf
Liu, X., Research on flexibility evaluation method of distribution system based on renewable energy and electric vehicles, IEEE Access, 8, pp. 109249–109265, 2020. DOI: https://doi.org/10.1109/ACCESS.2020.3000685 DOI: https://doi.org/10.1109/ACCESS.2020.3000685
Gonzalez-Salazar, M.A., Kirsten, T., and Prchlik, L., Review of the operational fl exibility and emissions of gas- and coal- fi red power plants in a future with growing renewables, Renewable and Sustainable Energy Reviews, 82(July), pp. 1497–1513, 2018. DOI: https://doi.org/10.1016/j.rser.2017.05.278. DOI: https://doi.org/10.1016/j.rser.2017.05.278
CREG, Medidas para la promocion de la competencia en el mercado de electricidad mayorista, 2010, 33P, [Online]. Available at: https://acolgen.org.co/portfolio/medidas-para-la-promocion-de-la-competencia-en-el-mercado-de-electricidad-mayorista
Kondziella, H., and Bruckner, T., Flexibility requirements of renewable energy-based electricity systems - A review of research results and methodologies, Renewable and Sustainable Energy Reviews, 53, pp. 10–22, 2016. DOI: https://doi.org/10.1016/j.rser.2015.07.199. DOI: https://doi.org/10.1016/j.rser.2015.07.199
Lannoye, E., Flynn, D., and O’Malley, M., Power system flexibility assessment State of the art, IEEE Power and Energy Society General Meeting, 2012. DOI: https://doi.org/10.1109/PESGM.2012.6345375.
Lannoye, E., Flynn, D., and O’Malley, M., Power system flexibility assessment State of the art, IEEE Power and Energy Society General Meeting, 2012. DOI: https://doi.org/10.1109/PESGM.2012.6345375. DOI: https://doi.org/10.1109/PESGM.2012.6345375
Kinoshita, S., Yamaguchi, N., Sato, F., and Ohtani, S., Impact of demand response price signal on battery state of charge management at office buildings, in: SEST 2021 - 4th International Conference on Smart Energy Systems and Technologies, 2021. DOI: https://doi.org/10.1109/SEST50973.2021.9543140. DOI: https://doi.org/10.1109/SEST50973.2021.9543140
Cao, Y. et al., Hydrogen production using solar energy and injection into a solid oxide fuel cell for CO2 emission reduction; Thermoeconomic assessment and tri-objective optimization, Sustainable Energy Technologies and Assessments, 50(November), art. 101767, 2022. DOI: https://doi.org/10.1016/j.seta.2021.101767. DOI: https://doi.org/10.1016/j.seta.2021.101767
Thurner, L. et al., Pandapower — An Open-Source Python tool for convenient modeling, analysis, and optimization of electric power systems, IEEE Transactions on Power Systems, 33(6), pp. 6510–6521, 2018. DOI: https://doi.org/10.1109/TPWRS.2018.2829021. DOI: https://doi.org/10.1109/TPWRS.2018.2829021
Lannoye, E., Flynn, D., and O’Malley, M., Evaluation of power system flexibility, IEEE Transactions on Power Systems, 27(2), pp. 922–931, 2012. DOI: https://doi.org/10.1109/TPWRS.2011.2177280. DOI: https://doi.org/10.1109/TPWRS.2011.2177280
Thatte A.A., and Xie, L., A metric and market construct of inter-temporal flexibility in time-coupled economic dispatch, IEEE Transactions on Power Systems, 31(5), pp. 3437–3446, 2016. DOI: https://doi.org/10.1109/TPWRS.2015.2495118. DOI: https://doi.org/10.1109/TPWRS.2015.2495118
Ma, J., Silva, V., Belhomme, R., Kirschen, D.S., and Ochoa, L.F., Exploring the use of flexibility indices in low carbon power systems, IEEE PES Innovative Smart Grid Technologies Conference Europe (2), pp. 1–5, 2012. DOI: https://doi.org/10.1109/ISGTEurope.2012.6465757. DOI: https://doi.org/10.1109/ISGTEurope.2012.6465757
Makarov, Y.V., Etingov, P., Huang, Z., Ma, J., Chakrabarti, B., Subbarao, K., Loutan, C., and Guttromson, R., Integration of wind generation and load forecast uncertainties into power grid operations. in: Transmission and Distribution Conference and Exposition, 2010, pp. 1-8. DOI: https://doi.org/10.1109/TDC.2010.5484201 DOI: https://doi.org/10.2172/985583
Li, H., Wang, Z., Hong, T. and Piette, M.A., Energy flexibility of residential buildings: a systematic review of characterization and quantification methods and applications, Advances in Applied Energy, 3(July), art. 100054, 2021. DOI: https://doi.org/10.1016/j.adapen.2021.100054. DOI: https://doi.org/10.1016/j.adapen.2021.100054
Mills, A., and Seel, J., Flexibility inventory for western resource planners, Berkeley National Laboratory, 2015. [Online]. Available at: https://eta-publications.lbl.gov/sites/default/files/lbnl-1003750.pdf
Guo, Z., Zheng, Y., and Li, G., Power system flexibility quantitative evaluation based on improved universal generating function method: a case study of Zhangjiakou, Energy, 205, art. 117963, 2020. DOI: https://doi.org/10.1016/j.energy.2020.117963. DOI: https://doi.org/10.1016/j.energy.2020.117963
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