Demand Response Program Implementation Methodology: A Colombian Study Case
| dc.contributor.author | Molina, Juan D. | eng |
| dc.contributor.author | Buitrago, Luisa F. | eng |
| dc.contributor.author | Tellez, Sandra Milena | eng |
| dc.contributor.author | Giraldo, Sandra | eng |
| dc.contributor.author | Uribe, Jaime A. | eng |
| dc.date.accessioned | 2022-03-23 00:00:00 | |
| dc.date.accessioned | 2025-05-21T19:15:45Z | |
| dc.date.available | 2022-03-23 00:00:00 | |
| dc.date.issued | 2022-03-23 | |
| dc.description.abstract | The industrialization and urbanization are responsible for Greenhouse Gas (GHG) emissions and could generate energy shortage problems. The application of Demand Response (DR) programs enables the user to be empowered towards a conscious consumption of energy, allowing the reduction or displacement of the demand for electrical energy, contributing to the sustainable development of the sector and the operational efficiency of the electrical system, among others. A reference framework for this type of program is detailed along with a literature survey applied to the Colombian case. The considerations on the design of a methodology to the implementation of the DR pilot, considering if the pilot is in an interconnected system zone or non-interconnected system zone and the application of the design methodology in the modeling of three DR pilots in Colombia is presented. For the modeling of the pilots, the characteristics of the area and the base consumption of the users are considered, and the characteristics and assumptions of the pilot are also defined. Furthermore, the DR pilot in each zone considering four types of users is detailed. The results show the potential for energy reduction and displacement in different time bands for each zone, which allows determining the assessment of the benefits from a technical, financial, and environmental point of view, and the costs of each pilot in monetary terms, it not to compare the pilots with each other, but to illustrate the values that must be taken into account in those analyses. The sensitivity analysis of each pilot was also carried out, considering the variation of the benefit/cost relationship with the energy rate in peak hours vs. off-peak hours and the base energy rate in the area. The sensitivity analysis shows that, when varying the level of energy demand response and the number of pilot participants, the values are presented when the benefit/cost ratio is greater than 1. In addition, the paper provides specific recommendations related to the design of a methodology and the implementation in a pilot DR using simulation. | eng |
| dc.format.mimetype | application/pdf | eng |
| dc.identifier.doi | 10.32397/tesea.vol3.n1.3 | |
| dc.identifier.eissn | 2745-0120 | |
| dc.identifier.uri | https://hdl.handle.net/20.500.12585/13501 | |
| dc.identifier.url | https://doi.org/10.32397/tesea.vol3.n1.3 | |
| dc.language.iso | eng | eng |
| dc.publisher | Universidad Tecnológica de Bolívar | eng |
| dc.relation.bitstream | https://revistas.utb.edu.co/tesea/article/download/465/363 | |
| dc.relation.citationedition | Núm. 1 , Año 2022 : Transactions on Energy Systems and Engineering Applications | eng |
| dc.relation.citationendpage | 19 | |
| dc.relation.citationissue | 1 | eng |
| dc.relation.citationstartpage | 13 | |
| dc.relation.citationvolume | 3 | eng |
| dc.relation.ispartofjournal | Transactions on Energy Systems and Engineering Applications | eng |
| dc.relation.references | Leo Raju, A Swetha, C K Shruthi, and J Shruthi. Implementation of demand response management in microgrids using iot and machine learning. In 2021 5th International Conference on Intelligent Computing and Control Systems (ICICCS), pages 455–463, 2021. | eng |
| dc.relation.references | E.A.M. Klaassen, R.J.F. van Gerwen, J. Frunt, and J.G. Slootweg. A methodology to assess demand response benefits from a system perspective: A dutch case study. Utilities Policy, 44:25–37, 2017. | eng |
| dc.relation.references | L.A. Arias, E. Rivas, and F. Santamaría. Preparation of demand response management: Case study. In 2018 IEEE ANDESCON, pages 1–6, 2018. | eng |
| dc.relation.references | Kotchakorn Maneebang, Kanokpol Methapatara, and Jasada Kudtongngam. A demand side management solution: Fully automated demand response using openadr2.0b coordinating with bems pilot project. In 2020 International Conference on Smart Grids and Energy Systems (SGES), pages 30–35, 2020. | eng |
| dc.relation.references | Liga Kurevska, Antans Sauhats, Gatis Junghans, and Valent¯ıns Lavrinovcs. Measuring the impact of demand response services on electricity prices in latvian electricity market. In 2020 IEEE 61th International Scientific Conference on Power and Electrical Engineering of Riga Technical University (RTUCON), pages 1–4, 2020. | eng |
| dc.relation.references | The World Bank. World bank open data, 2021. | eng |
| dc.relation.references | R.R. Hernandez. Apagar si pagó. In CIDET, volume Nov., pages 1–14, 2017. | eng |
| dc.relation.references | Colombia Inteligente. Respuesta de la demanda: Estrategia para la mitigación de gases de efecto invernadero. 2019. | eng |
| dc.relation.references | Xie Zhihan, Chen Tieyi, Xue Li, Liu Kai, Chen Songsong, and Yuan Jindou. Research on the implementation architecture and demand response controlling strategy for adjustable load. In 2020 IEEE 2nd International Conference on Circuits and Systems (ICCS), pages 59–63, 2020. | eng |
| dc.relation.references | Daniela Valencia-L, Sandra X Carvajal Quintero, and Jairo Pineda-Agudelo. Design of demand management programs for the efficient use of electricity by industrial users. Ingeniería y competitividad, 19:207 – 218, 06 2017. | eng |
| dc.relation.references | Juan D. Molina, Luisa F. Buitrago, and Jaime A. Zapata. Design of demand response programs: Customer preferences experiences in colombia. In 2020 IEEE PES Transmission Distribution Conference and Exhibition - Latin America (T D LA), pages 1–6, 2020. | eng |
| dc.relation.references | DOE. Customer acceptance , retention , and response to time- based rates from the consumer behavior studies,. 2016. | eng |
| dc.relation.references | Colombia Inteligente. Fomento programas rd. 2020. | eng |
| dc.relation.references | Deepan Muthirayan, Dileep Kalathil, Kameshwar Poolla, and Pravin Varaiya. Baseline estimation and scheduling for demand response. In 2018 IEEE Conference on Decision and Control (CDC), pages 4857–4862, 2018. | eng |
| dc.relation.references | República Congreso. Ley 1715 de 2014: Por medio de la cual se regula la integración de las energías renovables no convencionales al sistema energético nacional. 2014. | eng |
| dc.relation.references | CREG. Resolución número 203 de 2013. 2014. | eng |
| dc.relation.references | CREG. Resolución número 029 de 2016. por la cual se define un esquema de tarifas diferenciales para establecer los costos de prestación del servicio de energía eléctrica a usuarios regulados en el sin para promover el ahorro voluntario de energía. 2016. | eng |
| dc.relation.references | CREG. Resolución número 039 de 2016. por la cual se modifica, aclara y simplifica la resolución creg 029 de 2016. 2016. | eng |
| dc.relation.references | CREG. Resolución número 049 de 2016. por la cual se aclara la resolución creg 025 de 2016 y la resolución creg 029 de 2016. 2016. | eng |
| dc.relation.references | UPME. Desarrollo de una metodología para determinar los costos de racionamiento de los sectores de electricidad y gas natural. 2015. | eng |
| dc.rights | Juan D. Molina, Luisa F. Buitrago, Sandra M. Téllez, Sandra Giraldo, Jaime A. Uribe - 2022 | eng |
| dc.rights.accessrights | info:eu-repo/semantics/openAccess | eng |
| dc.rights.coar | http://purl.org/coar/access_right/c_abf2 | eng |
| dc.rights.creativecommons | This work is licensed under a Creative Commons Attribution 4.0 International License. | eng |
| dc.rights.uri | https://creativecommons.org/licenses/by/4.0 | eng |
| dc.source | https://revistas.utb.edu.co/tesea/article/view/465 | eng |
| dc.subject | Demand Response | eng |
| dc.subject | Demand Response Programs | eng |
| dc.subject | pilot design | eng |
| dc.subject | energy management | eng |
| dc.title | Demand Response Program Implementation Methodology: A Colombian Study Case | spa |
| dc.title.translated | Demand Response Program Implementation Methodology: A Colombian Study Case | spa |
| dc.type | Artículo de revista | spa |
| dc.type.coar | http://purl.org/coar/resource_type/c_6501 | eng |
| dc.type.coarversion | http://purl.org/coar/version/c_970fb48d4fbd8a85 | eng |
| dc.type.content | Text | eng |
| dc.type.driver | info:eu-repo/semantics/article | eng |
| dc.type.local | Journal article | eng |
| dc.type.version | info:eu-repo/semantics/publishedVersion | eng |