RESIDENTIAL DEMAND FORECASTING METHODOLOGY FOR LONG-TERM ENERGY PLANNING IN PERU
DOI:
https://doi.org/10.21754/tecnia.v30i2.862Keywords:
residential demand, stock turnover, substitution, multicriteria, GHG mitigationAbstract
Globally there are demand projection models that serve as the basis for energy planning since the 1970s. However, as most of these models affected to developed countries such models must be evaluated, complemented and improved in order to identify the Methodologies that best adapt to the particularities of a developing country such as Peru and at the same time meet the challenges posed by current energy systems such as the emergence of disruptive technologies and an international context to combat climate change. The objective of this article is to define a model of projection of the demand of the residential sector by integrating the end-use models through the rotation of stocks and the substitution model through multicriteria evaluation, which was specially designed for developing countries. They have identified the factors of net present value, investment cost, presentation quality and environmental impact in the model through multicriteria evaluation so that the levels of penetration and regression by sources can be obtained and integrated into a LEAP energy model and thus evaluate the entire energy matrix as a whole. The model was applied to the case study of the residential sector in Peru and the evolution of the energy consumption equipment park was determined; the level of replacement by source and technology; as well as its comparison with the results obtained through economic models and optimization of the end use.
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References
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[7] J. Meza and J. E. Luyo, “Modelos de planeamiento energético aplicados en Perú: una revisión y propuesta metodológica”, Revista ECIPerú, vol. 17, no. 1, pp. 11–19, feb. 2020.
[8] C.G. Heaps, (2020), LEAP: The Low Emissions Analysis Platform. [Software version: 2020.1.19] Stockholm Environment Institute. Somerville, MA, USA. Available: https://leap.sei.org
[9] L. Suganthi and A. Samuel, “Energy models for demand forecasting - A review”, Renewable and Sustainable Energy Reviews, vol. 16, no. 2, pp. 1223–1240, feb. 2012.
[10] K. B. Debnath and M. Mourshed, “Forecasting methods in energy planning models”, Renewable and Sustainable Energy Reviews, vol. 88, pp. 297–325, mar. 2018.
[11] S. C. Bhattacharyya and G.R. Timilsina, “Energy Demand Models for Policy Formulation: A comparative Study of Energy Demand Models”, World Bank Policy Research Working Paper WPS4866, mar. 2009.
[12] H. S. Houthakker, “Some Calculations on Electricity Consumption in Great Britain”, Journal of the Royal Statistical Society. Series A (General), vol. 114, no. 3, pp. 359–371, 1951.
[13] R. S. Pindyck, The structure of world energy demand, Cambridge, Massachusetts, USA: The MIT Press, 1979.
[14] D. L. Mcfadden, “Conditional logit analysis in quantitative choice behaviour”, Frontiers of Econometrics, P. Zaremka, Ed. New York, USA: Academic Press, 1973, pp. 105–142.
[15] M. P. Clements and R. Madlener, “Seasonality, cointegration and forecasting UK residential energy demand”, Scottish J. of Political Economy, vol. 46, no. 2, pp. 185–206, 1999.
[16] E. Ziramba, “The demand for residential electricity in South Africa”, Energy Policy, vol. 36, no. 9, pp. 3460–3466, 2008.
[17] F. Halicoglou, “Residential electricity demand dynamics in Turkey”, Energy Economics, vol. 29, no. 9, pp. 199–210, 2007.
[18] International Energy Agency. Methodology for Energy Access Analysis, WEO Model Documentation. 2019 Version [Online]. Available: http://www.worldenergyoutlook.org/weomodel/documentation
[19] International Energy Agency, “Energy and the Sustainable Development Goals”, en World Energy Outlook 2019, pp. 81–132.
[20] W. McAleer, “A regional end use energy demand model”, Omega, vol. 10, no. 6, pp. 629–639, 1982.
[21] H. Farahbakhsh, V. I. Ugursal and A. S. Fung, “A Residential End-Use Energy Consumption Model for Canada”, International Journal of Energy Research, vol. 22, no. 13, pp. 1133–1143, 1998.
[22] S. Tanatvanit, B. Limmeechokchai and S. Chungpaibulpatana, “Sustainable energy development strategies: implications of energy demand management and renewable energy in Thailand”, Renewable and Sustainable Energy Reviews, vol. 7, no. 5, pp. 367–395, 2003.
[23] H. C. Liao, and T. F. Chang, “Space-heating and water-heating energy demands of the aged in the US”, Energy Economics, vol. 24, no. 3, pp. 267–284, 2002.
[24] T. Ekholm, V. Krey, S. Pachauri, & K. Riahi, “Determinants of household energy consumption in India”, Energy Policy, vol. 38, no. 10, pp. 5696–5707, 2010.
[25] S. Pachauri, B. van Ruijven, Y. Nagai, K. Riahi, D. van Vuuren, A. Brew-Hammond and N. Nakicenovic, “Pathways to achieve universal household access to modern energy by 2030”, Environmental Research Letters, vol. 8, no. 2, pp. 1–7, 2013.
[26] Stockholm Environment Institute. Web Version: LEAP Help, Updated for LEAP2020. [Online]. Available:
https://www.energycommunity.org/Help/leap.htm#t=Concepts%2FIntroduction.htm
[27] M. A. McNeil, V. E. Letschert, S. de la Rue du Can and J. Ke, “Bottom–Up Energy Analysis System (BUENAS) - an international
appliance efficiency policy tool”, Energy Efficiency, vol. 6, pp. 191–217, 2013.
[28] V. E. Letschert, N. Bojda, J. Ke and M. A. McNeil, "Estimate of Cost-Effective Potential for Minimum Efficiency Performance Standards in 13 Major World Economies Energy Savings, Environmental and Financial Impacts", Technical Report LBNL-5723E, United States, Jul 2012.
[29] V. E. Letschert, M. A. McNeil and W. F. Luts, "Design of Standards and Labeling programs in Chile: Techno-Economic Analysis for Refrigerators ", Technical Report LBNL-6295E, United States, May 2013
[30] Fundación Bariloche, "Modelo de Sustituciones entre Fuentes Energéticas", Technical Report, San Carlos de Bariloche, Argentina, Jun 2014.
[31] D. Rios, Sensitivity Analysis in Multiobjective Decision Making. Heidelberg, Berlin, Germany: Springer, 1990.
[32] Z. Xu, Uncertain Multi-Attribute Decision Making: Methods and Application. Heidelberg, Berlin, Germany: Springer, 2015.
[33] Grupo Intergubernamental de Expertos sobre Cambio Climático, 2019 Refinement to the 2006 IPCC Guidelines for National Greenhouse Gas Inventories, IGES, Japón, 2019.
[34] J. A. Nieves, A. J. Aristizabal, I. Dyner, O. Baez and D. H. Ospina, “Energy demand and greenhouse gas emissions analysis in Colombia: A LEAP model application”, Energy, vol. 169, pp. 380–397, 2019.
[35] Gerencia de Regulación Tarifaria, Modelo PERSEO 2.0, Perú, 2018 [Online]. Available:
https://www.osinergmin.gob.pe/seccion/institucional/regulacion-tarifaria/informacion-tecnica/modelo-perseo2
[36] Instituto Nacional de Estadística e Informática, “Estimaciones y Proyecciones de Población Total, por Años Calendario y Edades Simples 1950-2050”, Lima, Perú, Boletín Especial N°17, 2009. [Online]. Available: https://n9.cl/iqxs
[37] Instituto Nacional de Estadística e Informática, “Perú: Estimaciones y Proyecciones de Población, 1950-2050, Urbana – Rural 1970-2025”, Lima, Perú, Boletín de Análisis Demográfico N°35, 2001. . [Online]. Available: https://bit.ly/33jAQEb
[38] Instituto Nacional de Estadística e Informática, “Perú: Perfil Sociodemográfico Informe Nacional, Censos Nacionales 2017: XII de Población, VII de Vivienda y III de Comunidades Indígenas”, Lima, Perú, Lib1539, 2018. [Online]. Available: https://bit.ly/37cHdKl
[39] Instituto Nacional de Estadística e Informática, Series Nacionales [Online]. Available:
http://webapp.inei.gob.pe:8080/sirtod-series/
[40] Banco Mundial BIRF-AIF, Datos [Online]. Available:
https://datos.bancomundial.org/indicador/NY.GDP.PCAP.PP.KD?locations=PE
[41] Ministerio de Economía y Finanzas, “Marco Macroeconómico Multianual 2020”, Lima, Perú, 2019. [Online]. Available:
https://bit.ly/2JasUhq
[42] Banco Central de Reserva del Perú, “Reporte de Inflación diciembre 2019: Panorama actual y proyecciones macroeconómicas 2019 – 2021”, Lima, Perú, ISSN 1816-4412, 2018. [Online]. Available:
https://bit.ly/3q484kC
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[44] Instituto Nacional de Estadística e Informática, “Perú: Encuesta Demográfica y de Salud Familiar – ENDES 2019”, Lima, Perú, ENDES2019, 2020. [Online]. Available:
https://www.inei.gob.pe/media/MenuRecursivo/publicaciones_digitales/Est/Endes2019/
[45] Ministerio de Energía y Minas, “Balance Nacional de Energía Útil 2013”, Lima, Perú, 2016. [Online]. Available:
http://www.minem.gob.pe/_publicacion.php?idSector=12&idPublicacion=540
[46] Ministerio de Energía y Minas, “Etiquetado de Eficiencia Energética: Parque y Tenencia de Equipos”, Lima, Perú, 2016. [Online]. Available:
http://etiquetaenergetica.minem.gob.pe/
[47] Ministerio de Energía y Minas, “Estudio de Mercado de Iluminación en el Perú”, Lima, Perú, 2015. [Online]. Available: https://bit.ly/2Jiggww
[48] Ministerio de Energía y Minas, “Balance Nacional de Energía 2018”, Lima, Perú, 2020. [Online]. Available:
https://sinia.minam.gob.pe/download/file/fid/66509
[49] Comité de Operación Económica del Sistema, “Anuario Estadístico de Operación 2019”, Lima, Perú, 2020. [Online]. Available: https://www.coes.org.pe/Portal/publicaciones/estadisticas/estadistica2019#
[50] Organismo Supervisor de la Inversión en Energía y Minería, “Reporte de Información comercial año 2019”, Lima, Perú, 2020. [Online]. Available:
http://www2.osinerg.gob.pe/Publicaciones/pdf/InfoComercial/IC2019T4.pdf
[51] Organismo Supervisor de la Inversión en Energía y Minería, “Reporte Semestral de Monitoreo del Mercado de Gas Natural”, Lima, Perú, 2019. [Online]. Available: https://bit.ly/366CtXw
[52] Ministerio de Energía y Minas, “Programa para la gestión eficiente y sostenible de recursos energéticos del Perú, Presentación Sistema de Planificación Energética”, Lima, Perú, 2019. [Online]. Available: https://bit.ly/2KB3I42
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2020-11-27
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J. N. Meza Segura and J. Luyo-Kuong, “RESIDENTIAL DEMAND FORECASTING METHODOLOGY FOR LONG-TERM ENERGY PLANNING IN PERU”, TECNIA, vol. 30, no. 2, pp. 33–45, Nov. 2020.
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