Academic literature on the topic 'Thermal energy demand forecast'
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Journal articles on the topic "Thermal energy demand forecast"
Liu, Yujing, Ruoyun Du, and Dongxiao Niu. "Forecast of Coal Demand in Shanxi Province Based on GA—LSSVM under Multiple Scenarios." Energies 15, no. 17 (September 5, 2022): 6475. http://dx.doi.org/10.3390/en15176475.
Full textLucas Segarra, Eva, Hu Du, Germán Ramos Ruiz, and Carlos Fernández Bandera. "Methodology for the Quantification of the Impact of Weather Forecasts in Predictive Simulation Models." Energies 12, no. 7 (April 5, 2019): 1309. http://dx.doi.org/10.3390/en12071309.
Full textMaliarenko, O. Ye, N. Yu Maistrenko, and V. V. Horskyi. "Forecast of fuel and coal consumption in Ukraine until 2040 by a complex method of forecasting energy consumption." Problems of General Energy 2021, no. 3 (September 23, 2021): 28–35. http://dx.doi.org/10.15407/pge2021.03.028.
Full textDargahi, Ali, Khezr Sanjani, Morteza Nazari-Heris, Behnam Mohammadi-Ivatloo, Sajjad Tohidi, and Mousa Marzband. "Scheduling of Air Conditioning and Thermal Energy Storage Systems Considering Demand Response Programs." Sustainability 12, no. 18 (September 7, 2020): 7311. http://dx.doi.org/10.3390/su12187311.
Full textGuzhov, S. V. "Forecast of demand for the rmal energy for buildings of secondary educational institutions based on the properties of heteromorphism of their energy systems." Power engineering: research, equipment, technology 22, no. 5 (December 24, 2020): 18–27. http://dx.doi.org/10.30724/1998-9903-2020-22-5-18-27.
Full textYousefi, Hossein, Mohammad Hasan Ghodusinejad, and Armin Ghodrati. "Multi-Criteria Future Energy System Planning and Analysis for Hot Arid Areas of Iran." Energies 15, no. 24 (December 12, 2022): 9405. http://dx.doi.org/10.3390/en15249405.
Full textNiederau, Jan, Johanna Fink, and Moritz Lauster. "Connecting Dynamic Heat Demands of Buildings with Borehole Heat Exchanger Simulations for Realistic Monitoring and Forecast." Advances in Geosciences 56 (October 6, 2021): 45–56. http://dx.doi.org/10.5194/adgeo-56-45-2021.
Full textLiu, Dunnan, Mengjiao Zou, Yue Zhang, Lingxiang Wang, Tingting Zhang, and Mingguang Liu. "Market clearing price forecast for power peak shaving auxiliary service." E3S Web of Conferences 237 (2021): 02007. http://dx.doi.org/10.1051/e3sconf/202123702007.
Full textSzul, Tomasz, and Stanisław Kokoszka. "Application of Rough Set Theory (RST) to Forecast Energy Consumption in Buildings Undergoing Thermal Modernization." Energies 13, no. 6 (March 11, 2020): 1309. http://dx.doi.org/10.3390/en13061309.
Full textLucas Segarra, Eva, Germán Ramos Ruiz, and Carlos Fernández Bandera. "Probabilistic Load Forecasting Optimization for Building Energy Models via Day Characterization." Sensors 21, no. 9 (May 10, 2021): 3299. http://dx.doi.org/10.3390/s21093299.
Full textDissertations / Theses on the topic "Thermal energy demand forecast"
Thomas, Arthur. "The Econometrics of Energy Demand : identification and Forecast." Thesis, Nantes, 2020. http://www.theses.fr/2020NANT3021.
Full textThe prevention of climate change is one of the priorities of the world energy policy that aims to massively reduce greenhouse gas emissions. Faced with these challenges, it is striking to note that our knowledge of energy demand modeling remains limited because it is largely based on old empirical work and methodologies that are now dated. Therefore, the objective of our work is twofold. First, we analyze quantitatively the economic determinants of energy demand. Second, we develop new forecasting models. This thesis is structured in four chapters. The first chapter shows that natural gas consumption in France can be predicted using a simple model which only includes public information that is available to market's participants. This chapter proves the existence of a long-term relationship between demand and prices of other energies and provides estimates of their marginal impacts on observed demand levels. The second chapter empirically investigates the role of temperature in forecasting gas prices in the US. It develops a methodology to build a new monthly index based on temperature. This index captures variations in residual demand for natural gas in real time. It is used as an additional exogenous variable in structural models (VAR) to improve forecasts and we show that, in our case, predictive models derived from a structural model are enhanced relying on true real-time (not subject to revisions) data. The third chapter proposes to use, in the case of oil market, a structural model capturing expectations in a noncausal VAR framework, and to properly identify the reactions of oil key variables to supply news shock. The fourth chapter revisits the predictive power of oil and gas convenience yield by incorporating expectations into an empirical specification through non-causal VAR based on the theory of storage which delivers very competitive price predictions in a simple bivariate setting
MENDES, EVANDRO LUIZ. "INTERVENTION MODELS TO FORECAST MONTHLY DEMAND OF ELETRIC ENERGY, CONSIDERING THE RATIONING SCENERY." PONTIFÍCIA UNIVERSIDADE CATÓLICA DO RIO DE JANEIRO, 2002. http://www.maxwell.vrac.puc-rio.br/Busca_etds.php?strSecao=resultado&nrSeq=3336@1.
Full textNesta dissertação é desenvolvida uma metodologia para previsão de demanda mensal de energia elétrica considerando cenários de racionamento. A metodologia usada consiste em, a partir das taxas de crescimento da série temporal, identificar e eliminar os efeitos do racionamento de energia elétrica através da aplicação de Modelos Lineares Dinâmicos. São analisadas também estruturas de intervenção nos modelos estatísticos de Box & Jenkins e Holt & Winters. Os modelos são então comparados segundo alguns critérios, basicamente no que tange à sua eficiência preditiva. Conclui-se ao final sobre a eficiência da metodologia proposta, dado a grande dificuldade para solucionar o problema a partir dos modelos estatísticos de Box & Jenkins e Holt & Winters. Esta solução é então proposta como a mais viável para criar cenários de racionamento e pósracionamento de energia para ser utilizado por agentes do sistema elétrico nacional.
In this dissertation, a methodology is developed to forecast monthly demand of electric energy, considering the rationing scenery. The methodology is based on, taking the growth rate from the time series, identify and eliminate the effects of electric energy rationing, using Dynamic Linear Models. It is also analyzed intervention structures in the statistics models of Box & Jenkins and Holt & Winters. The models are compared according to some criterions, mainly forecast accuracy. At the end, we concluded that the methodology proposed is more efficient, due to the difficult to solve the problem using the statistics models with intervention. This solution is proposed as the best among them to create scenery during the energy rationing and after energy rationing, to be used by the national electric system agents.
Zhao, Zhiheng. "Thermal Inertia In Residential Buildings For Demand Response." Thesis, The University of Sydney, 2016. http://hdl.handle.net/2123/16018.
Full textCowan, David. "Understanding and modelling thermal energy demand and emissions in urban environments." Thesis, London South Bank University, 2017. http://researchopen.lsbu.ac.uk/1863/.
Full textWang, Hao. "Numerical study of cooling demand and thermal performance for different wall constructions." Thesis, Högskolan i Gävle, Avdelningen för bygg- energi- och miljöteknik, 2015. http://urn.kb.se/resolve?urn=urn:nbn:se:hig:diva-19175.
Full textSivabavanandan, Sivalingam. "Thermal energy storage application for load shifting and electrical demand management in Saudi Arabia." Thesis, Kingston University, 2005. http://eprints.kingston.ac.uk/35780/.
Full textHøseggen, Rasmus Z. "Dynamic use of the building structure - energy performance and thermal environment." Doctoral thesis, Norwegian University of Science and Technology, Department of Energy and Process Engineering, 2008. http://urn.kb.se/resolve?urn=urn:nbn:no:ntnu:diva-1998.
Full textThe main objectives of this thesis have been to evaluate how, under which premises, and to what extent building thermal mass can contribute to reduce the net energy demand in office buildings. The thesis also assesses the potential thermal environmental benefits of utilizing thermal mass in office buildings, i.e. reduction of temperature peaks, reduction of temperature swings, and the reduction in the number of hours with excessive operative temperatures. This has been done by literature searches, and experimental and analytical assessments. This thesis mainly concerns office buildings in the Norwegian climate. However, the methods used and the results obtained from this work are transferable to other countries with similar climates and building codes.
Within the limitations of this thesis and based on the findings from all parts and papers this thesis comprises, it is shown that utilization of thermal mass in office buildings reduces the daytime peak temperature, reduces the diurnal temperature swing, decreases the number of hours with excessive temperatures, and increases the ability of a space to handle daytime heat loads. Exposed thermal mass also contributes to decrease the net cooling demand in buildings. However, thermal mass is found to have only a minor influence on the heating demand in office buildings.
The quantity of the achievements is dependent on the amount of exposed thermal mass, night ventilation strategy, and airflow rates. In addition, parameters such as set point temperatures, control ranges, occupancy patterns, daytime ventilation airflow rates, and prevailing convection regimes are influential for the achieved result. The importance of these parameters are quantified and discussed.
Hovedmålene med denne avhandlingen har vært å evaluere hvordan, under hvilke forutsetninger og i hvilken utstrekning termisk masse kan bidra til å redusere netto energibehov i kontorbygninger. Avhandlingen vurderer også hvilke potensielle fordeler termisk masse har for det termiske inneklimaet, dvs. reduksjon av maksimumstemperatur, temperatursvingninger og antall timer med overtemperaturer. Disse undersøkelsene er gjort gjennom søk i litteraturen, feltstudier og analytiske metoder. Avhandlingen omfatter i hovedsak kontorbygninger under norske forhold, men metodene og resultatene er overførbare til andre land med sammenlignbare klimatiske forhold og byggeskikk.
Innenfor avgrensningene gjort i avhandlingen og basert funnene i de ulike delene og artiklene avhandlingen består av, er det vist at utnyttelse av termisk masse i kontorbygg bidrar til å redusere netto energibehov. Termisk masse reduserer også maksimumstemperaturen dagtid, demper temperaturvariasjonene over døgnet og reduserer antall timer med overtemperaturer. Utnyttelse av termisk masse bidrar også til at rom kan tåle en høyere intern varmelast enn lette rom uten at dette går ut over den termiske komforten. Termisk masse har imidlertid liten betydning for energibehovet for oppvarming i kontorbygg.
Gevinsten med å utnytte termisk masse avhenger av tilgjengeligheten av eksponerte tunge materialer, strategi for nattventilasjon og ventilasjonsluftmengder. I tillegg innvirker parametere som settpunkttemperaturer, dødbånd og kontrollintervaller for ventilasjonen og bruksmønster. Innvirkningen av disse parametrene er diskutert og kvantifisert.
Olsson, Martin. "Thermal Shape Factor : The impact of the building shape and thermal properties on the heating energy demand in Swedish climates." Thesis, Umeå universitet, Institutionen för tillämpad fysik och elektronik, 2016. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-125076.
Full textKettenis, Christos. "Electrical supply and demand in Cyprus : optimal use of renewable energy sources in electricity production." Thesis, University of Manchester, 2016. https://www.research.manchester.ac.uk/portal/en/theses/electrical-supply-and-demand-in-cyprus-optimal-use-of-renewable-energy-sources-in-electricity-production(3861cfcb-8a74-4087-a114-4e0dc9557202).html.
Full textMotuzienė, Violeta. "Complex analysis of the influence of glazing on energy demand of public buildings." Doctoral thesis, Lithuanian Academic Libraries Network (LABT), 2010. http://vddb.laba.lt/obj/LT-eLABa-0001:E.02~2010~D_20101228_125700-05528.
Full textDisertacijoje, taikant dinaminį pastatų energijos poreikių modeliavimą, nag-rinėjamos viešosios paskirties pastatų energinio efektyvumo problemos. Pagrin-dinis tyrimo objektas yra viešosios paskirties pastato fasado įstiklinimo įtaka energijos poreikiams. Greta savo pagrindinės funkcijos – pakankamo natūralaus apšvietimo užtikrinimo, fasado įstiklinimas privalo būti energiškai efektyvus. Tai prieštaringi reikalavimai. Pagrindinis disertacijos tikslas – įvertinant natūralaus apšvietimo poreikį, kompleksiškai išanalizuoti viešosios paskirties pastato įstiklinimo charakteristi-kų įtaką pastato mikroklimato ir apšvietimo sistemų energijos poreikiams bei nustatyti, kokioms pastato įstiklinimo charakteristikoms esant, Lietuvoje bei pa-našaus klimato šalyse pastato energijos poreikius galima būtų sumažinti iki ma-žai energijos vartojančio pastato lygio. Darbe sprendžiami du pagrindiniai užda-viniai: pirmasis – atliekama įstiklinimo įtakos kondicionuojamo pastato energijos poreikiams analizė; antrasis – nustatomos efektyvios energiškai efek-tyvaus pastato įstiklinimo charakteristikos. Disertaciją sudaro įvadas, keturi skyriai, rezultatų apibendrinimas, naudotos literatūros ir autoriaus publikacijų disertacijos tema sąrašai. Įvadiniame skyriuje aptariama tiriamoji problema, darbo aktualumas, apra-šomas tyrimų objektas, formuluojamas darbo tikslas bei uždaviniai, aprašoma tyrimų metodika, darbo mokslinis naujumas, darbo rezultatų praktinė reikšmė, ginamieji teiginiai, pristatomos... [toliau žr. visą tekstą]
Books on the topic "Thermal energy demand forecast"
Kavalec, Chris. California energy demand 2010-2020: Staff revised forecast : staff final report. 2nd ed. [Sacramento, Calif.]: California Energy Commission, 2009.
Find full textCavalec, Chris, and Tom Gorin. California energy demand 2010-2020: Staff revised forecast : staff final report. [Sacramento, Calif.]: California Energy Commission, 2009.
Find full textRoger, Fouquet, and Surrey Energy Economics Centre, eds. The S. E. E. C. United Kingdom Energy Demand Forecast (1994-2000). Guildford: Department of Economics, University of Surrey, 1995.
Find full textEstomin, Steven. Updated load forecast of energy and peak demand on the Delmarva Peninsula. Bethesda, Md. (4550 Montgomery Ave., Bethesda 20814): Exeter Associates, 1986.
Find full textNew Zealand. Ministry of Commerce. and New Zealand Institute of Economic Research., eds. An Energy baseline forecast to 2020: Supply and demand interactions in New Zealand's energy markets : a report. Wellington, N.Z: Research and Information Unit, Energy Policy Group, Energy and Resources Division, Ministry of Commerce, 1992.
Find full textNew Technology Demonstration Program (Federal Energy Management Program) and Pacific Northwest National Laboratory (U.S.), eds. Thermal energy storage for space cooling: Technology for reducing on-peak electricity demand and cost. [Washington, D.C.]: Federal Energy Management Program, 2000.
Find full text1969-, Mösle Peter, and Schwarz Michael 1961-, eds. Green building: Konzepte für nachhaltige Architektur. München: Callwey, 2007.
Find full text1969-, Mösle Peter, and Schwarz Michael 1961-, eds. Green building: Guidebook for sustainable architecture. Heidelberg: Springer, 2010.
Find full textAdvanced Optimization Methods and Big Data Applications in Energy Demand Forecast. MDPI, 2021. http://dx.doi.org/10.3390/books978-3-0365-0863-4.
Full textKonstantinou, Thaleia, Nataša Ćuković Ignjatović, and Martina Zbašnik-Senegačnik. ENERGY: resources and building performance. TU Delft Bouwkunde, 2018. http://dx.doi.org/10.47982/bookrxiv.25.
Full textBook chapters on the topic "Thermal energy demand forecast"
Garrity, Thomas F. "U.S. and World Electric Generation Forecast." In Global Energy Demand in Transition, 41–49. Boston, MA: Springer US, 1995. http://dx.doi.org/10.1007/978-1-4899-1048-6_4.
Full textLangmo, A., and C. Braun. "Forecast of the Global Electricity Market." In Global Energy Demand in Transition, 71–88. Boston, MA: Springer US, 1995. http://dx.doi.org/10.1007/978-1-4899-1048-6_7.
Full textFranco, Giovanna, and Marco Cartesegna. "Thermal Behaviour and Energy Demand." In Historical Buildings and Energy, 133–65. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-52615-7_7.
Full textCao, Jing, and Xinpeng Zhou. "China’s Energy Demand Forecast Based on Combination Model." In Proceedings of the Sixth International Forum on Decision Sciences, 129–45. Singapore: Springer Singapore, 2019. http://dx.doi.org/10.1007/978-981-13-8229-1_12.
Full textGutiérrez-García, Francisco José, and Ángel Arcos-Vargas. "Forecast of EV Derived Electrical Demand. The Spanish Case." In The Role of the Electric Vehicle in the Energy Transition, 25–43. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-50633-9_2.
Full textQureshi, Waqar A., Nirmal-Kumar C. Nair, and Mohammed M. Farid. "Impact of Energy Storage in Buildings on Electricity Demand Side Management." In Thermal Energy Storage with Phase Change Materials, 176–97. Boca Raton: CRC Press, 2021. http://dx.doi.org/10.1201/9780367567699-14.
Full textMoldovan, Macedon, Ion Visa, and Daniela Ciobanu. "Towards nZEB—Sustainable Solutions to Meet Thermal Energy Demand in Office Buildings." In Springer Proceedings in Energy, 115–33. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-09707-7_10.
Full textVidyarthi, Harishankar. "A Critical Analysis of Nuclear Power Development in India and Uranium Demand Forecast: A Case Study." In Energy Security and Development, 211–21. New Delhi: Springer India, 2015. http://dx.doi.org/10.1007/978-81-322-2065-7_13.
Full textViloria, Amelec, Alberto Roncallo Pichon, Hugo Hernandez-P, Osman Redondo Bilbao, Omar Bonerge Pineda Lezama, and Jesús Vargas. "Forecast of the Demand for Hourly Electric Energy by Artificial Neural Networks." In Lecture Notes in Electrical Engineering, 471–77. Singapore: Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-3125-5_46.
Full textSong, Meng, and Ciwei Gao. "Thermal Battery Modeling of TCLs for Demand Response." In Integration of Distributed Resources in Smart Grids for Demand Response and Transactive Energy, 129–56. Singapore: Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-16-7170-8_6.
Full textConference papers on the topic "Thermal energy demand forecast"
Deka, Angshuman, Nima Hamta, Behzad Esmaeilian, and Sara Behdad. "Predictive Modeling Techniques to Forecast Energy Demand in the United States: A Focus on Economic and Demographic Factors." In ASME 2015 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. American Society of Mechanical Engineers, 2015. http://dx.doi.org/10.1115/detc2015-47474.
Full textSong, Li, Ik-Seong Joo, and Subroto Gunawan. "Minimizing On-Peak and Off-Peak Demands for a Thermal Storage System: Forecast Model Analysis to Predict Next Day Daily Average Load and Model Application." In ASME 2010 4th International Conference on Energy Sustainability. ASMEDC, 2010. http://dx.doi.org/10.1115/es2010-90472.
Full textGutie´rrez, Estatio, Jorge E. Gonza´lez, Robert Bornstein, Mark Arend, and Alberto Martilli. "A New Modeling Approach to Forecast Building Energy Demands During Extreme Heat Events in Complex Cities." In ASME 2011 5th International Conference on Energy Sustainability. ASMEDC, 2011. http://dx.doi.org/10.1115/es2011-54844.
Full textBaldwin, Christopher, and Cynthia A. Cruickshank. "Using Forecasted Daily Maximum Temperatures to Control a Chiller Thermal Storage System." In ASME 2018 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 2018. http://dx.doi.org/10.1115/imece2018-88307.
Full textMcGaughy, Mitchell, Eric Boessneck, Thomas Salem, and John Wagner. "Critical Design Elements for Traveling Wave Thermoacoustic Engines." In ASME 2018 Power Conference collocated with the ASME 2018 12th International Conference on Energy Sustainability and the ASME 2018 Nuclear Forum. American Society of Mechanical Engineers, 2018. http://dx.doi.org/10.1115/power2018-7376.
Full textSchellong, Wolfgang, and Francois Hentges. "Energy demand forecast for a cogeneration system." In 2011 International Conference on Clean Electrical Power (ICCEP). IEEE, 2011. http://dx.doi.org/10.1109/iccep.2011.6036344.
Full textFesenko, Galina, Vladimir Kuznetsov, and Vladimir Usanov. "Framework for Assessing Transition Scenarios to Sustainable Nuclear Energy Systems." In 2014 22nd International Conference on Nuclear Engineering. American Society of Mechanical Engineers, 2014. http://dx.doi.org/10.1115/icone22-30224.
Full textXiaoyang Zhou, Nanpeng Yu, Weixin Yao, and Raymond Johnson. "Forecast load impact from demand response resources." In 2016 IEEE Power and Energy Society General Meeting (PESGM). IEEE, 2016. http://dx.doi.org/10.1109/pesgm.2016.7741992.
Full textBakken, Lars E., and Roald Skorping. "Optimum Operation and Maintenance of Gas Turbines Offshore." In ASME 1996 International Gas Turbine and Aeroengine Congress and Exhibition. American Society of Mechanical Engineers, 1996. http://dx.doi.org/10.1115/96-gt-273.
Full textWang, Yan-Hui. "Research on Energy Demand Forecast in Baoding City." In 2016 International Conference on Management Science and Management Innovation. Paris, France: Atlantis Press, 2016. http://dx.doi.org/10.2991/msmi-16.2016.78.
Full textReports on the topic "Thermal energy demand forecast"
Mintz, M. M., and A. D. Vyas. Forecast of transportation energy demand through the year 2010. Office of Scientific and Technical Information (OSTI), April 1991. http://dx.doi.org/10.2172/5349780.
Full textSalonvaara, Mikael, Emishaw Iffa, Andre Desjarlais, and Jerald Atchley. Impact of Mass Wood Walls on Building Energy Use, Peak Demand, and Thermal Comfort. Office of Scientific and Technical Information (OSTI), June 2022. http://dx.doi.org/10.2172/1883909.
Full textAuthor, Not Given. Thermal energy storage for space cooling. Technology for reducing on-peak electricity demand and cost. Office of Scientific and Technical Information (OSTI), December 2000. http://dx.doi.org/10.2172/770996.
Full textExner, Dagmar, Jørgen Rose, Élodie Héberlé, and Sara Mauri. Conservation compatible energy retrofit technologies: Part II: Documentation and assessment of conventional and innovative solutions for conservation and thermal enhancement of window systems in historic buildings. Edited by Alexander Rieser. IEA SHC Task 59, October 2021. http://dx.doi.org/10.18777/ieashc-task59-2021-0005.
Full textJohnston, Sweyn, John McGlynn, Veronica R. Prado, and Joseph Williams. Ocean Energy in the Caribbean: Technology Review, Potential Resource and Project Locational Guidance. Inter-American Development Bank, November 2021. http://dx.doi.org/10.18235/0003783.
Full textVargas-Herrera, Hernando, Juan Jose Ospina-Tejeiro, Carlos Alfonso Huertas-Campos, Adolfo León Cobo-Serna, Edgar Caicedo-García, Juan Pablo Cote-Barón, Nicolás Martínez-Cortés, et al. Monetary Policy Report - April de 2021. Banco de la República de Colombia, July 2021. http://dx.doi.org/10.32468/inf-pol-mont-eng.tr2-2021.
Full textPag, F., M. Jesper, U. Jordan, W. Gruber-Glatzl, and J. Fluch. Reference applications for renewable heat. IEA SHC Task 64, January 2021. http://dx.doi.org/10.18777/ieashc-task64-2021-0002.
Full textMeiri, Noam, Michael D. Denbow, and Cynthia J. Denbow. Epigenetic Adaptation: The Regulatory Mechanisms of Hypothalamic Plasticity that Determine Stress-Response Set Point. United States Department of Agriculture, November 2013. http://dx.doi.org/10.32747/2013.7593396.bard.
Full textAvis, William. Drivers, Barriers and Opportunities of E-waste Management in Africa. Institute of Development Studies (IDS), December 2021. http://dx.doi.org/10.19088/k4d.2022.016.
Full textMonetary Policy Report - April 2022. Banco de la República, June 2022. http://dx.doi.org/10.32468/inf-pol-mont-eng.tr2-2022.
Full text