Demand-side management strategies based on energy key perfomance indicators in real-time: Case study
Abstract
This paper sets out features of traditional Energy Key Performance Indicators (KPIs) employed in energy management programs; then, new indicators are proposed based on Advanced Metering Infrastructure (AMI) usage. These indicators make it possible to directly relate the amount of energy, type of end use and user consumption patterns. Analysis of AMI system information enables planning for differentiated Demand-Side Management (DSM) strategies. A case study developed at Universidad Nacional de Colombia - Bogotá campus is presented, which proposes new Energy Key Performance Indicators in Real Time. These indicators enable information analysis and DSM strategies that are appropriate for new technologies and that are aimed at increasing energy efficiency. Additionally, this paper presents the factors that have to be taken into account when implementing KPIs (Key Performance Indicators) and the decision-making process. This results in variable overall energy savings between 5 and 40%, according to the DSM strategy implemented.
References
Palensky, P., & Dietrich, D, Demand Side Management: Demand Response, Intelligent Energy Systems, and Smart Loads, IEEE Transaction on Industrial Informatics, 2011, 7 (3), 381–388.
Gelazanskas, L., & Gamage, K. A. A, Demand side management in smart grid: A review and proposals for future direction, Sustainable Cities and Society, 2014, 11, 22–30, https://doi.org/10.1016/j.scs.2013.11.001
United States Department of Energy - DOE, Benefits of Demand Response in Electricity Markets and Recommendations for Achieving Them, 2006, (February), 122. https://doi.org/citeulike-article-id:10043893
IEA DSM, IEA DSM TASK 25: Business models for a more effective market uptake of EE energy services for SMEs and communities. [Online]. Avalaible: http://www.ieadsm.org/task/task-25-business-models-for-a-more-effective-uptake/
S Téllez, S., & Duarte, Gestión de la Demanda en redes eléctricas inteligentes: Revisión y futuras estrategias, V CIUREE: Congreso de Eficiencia y Gestión Energética, Cartagena – Colombia, 2016.
Profaizer, P., Zapater, M. H., Valdavida, M. A., Já, A., & Bribián, I. Z, Information and Communications Technologies (ICTs) for energy efficiency in building: Review and analysis of results from EU pilot projects, 2016, 127, 128–137. https://doi.org/10.1016/j.enbuild.2016.05.064
Lee, D., & Cheng, C., Energy savings by energy management systems: A review, Renewable and Sustainable Energy Reviews, 2016, 56, 760–777. https://doi.org/10.1016/j.rser.2015.11.067.
Goldstein, D. B., & Almaguer, J. A, Developing a Suite of Energy Performance Indicators (EnPIs) to Optimize Outcomes, 2013, ACEEE Summer Study on Energy Efficiency in Industry, Washington DC. – EEUU.
Norma Técnica Colombiana, NTC-ISO 50001, 2015.
Fiedler, T., & Mircea, P. M., Energy management systems according to the ISO 50001 standard - Challenges and benefits, International Conference on Applied and Theoretical Electricity, ICATE, 2012.
Lee, D., & Cheng, C. Energy savings by energy management systems: A review. Renewable and Sustainable Energy Reviews, 2016, 56, 760–777.
https://doi.org/10.1016/j.rser.2015.11.067
Socolow, H. R. Field studies of energy savings in buildings: a tour of a 15-year research program at Princeton University. Energy, 1987, 12(10), 29–43
Chou SK, Wong YW, Chang WL, Y. C. Efficient energy performance of large commercial buildings in tropical climates. Energy Conversion Management, 1994, 35(9), 751–763
Friedrichs, K. (2013). Energy Key Performance Indicators: A European Benchmark and Assessment of Meaningful Indicators for the Use of Energy in Large Corporations. MsC in Economics and business administration, Major in energy. HEC Paris – Hautes Études Commerciales de Paris/NHH – Norges Handelshøyskole, Paris/Bergen, 2013
Burdová, E. K., & Vilčeková, S. Energy performance indicators developing. Energy Procedia, 2012, 14, 1175–1180. https://doi.org/10.1016/j.egypro.2011.12.887
Carretero Peña, A. C., & García Sánchez, J. M. Gestión de la eficiencia energética: cálculo del consumo, indicadores y mejora. Madrid, España: Aenor Ediciones, 2012
Bunse, K., Vodicka, M., Schönsleben, P., Brülhart, M., & Ernst, F. O. Integrating energy efficiency performance in production management gap analysis between industrial needs and scientific literature. Journal of Cleaner Production, 2011, 19(6–7), 667–679. https://doi.org/10.1016/j.jclepro.2010.11.011
Tronchin, L., Tommasino, M. C., & Fabbri, K. On the cost-optimal levels of energy-performance requirements for buildings: A case study with economic evaluation in Italy. International Journal of Sustainable Energy Planning and Management, 2014, 3, 49–62. https://doi.org/10.5278/ijsepm.2014.3.5
Mohassel, R., Fung, A., Mohammadi, F., & Raahemifar, K. Electrical Power and Energy Systems A survey on Advanced Metering Infrastructure, International Journal of Electrical Power and Energy Systems, 2014, 63, 473–484. https://doi.org/10.1016/j.ijepes.2014.06.025
Rahman, M., & Amanullah, M. Chapter 5, ‘Smart Meter’ in Smart Grids: Opportunities, Developments, and Trends, Shawkat Ali Ed. London: Springer-Verlag, 2013, p. 230
SmartGrid.Gov. Advanced Metering Infrastructure and Customer Systems. [Online]. Avalaible: https://www.smartgrid.gov/recovery_act/deployment_status/ami_and_customer_systems.html#%23SmartMetersDeployed
Téllez Gutiérrez, S. M., Rosero García, J., & Céspedes, R. Sistemas de medición avanzada en Colombia: beneficios, retos y oportunidades. Ingeniería y Desarrollo, 2018, 36 (Julio-diciembre), 469–488, https://doi.org/ISSN: 0122-3461
WattPlan - Clean Power Research, 5 Characteristics of Great Utility Customer Engagement, [Online]. Avalaible: www.cleanpower.com/wattplan.
Smart Grid Consumer Collaborative, Effective Communication with Consumers on the Smart Grid Value Proposition - Communications Toolkit, [Online]. Avalaible: http://smartenergycc.org/wp-content/uploads/2017/02/SGCC-Smart-Grid-CVP-Communications-Toolkit-Final.pdf
Davito, B., Tai, H., & Uhlaner, R, The smart grid and the promise of demand-side management, 2010, McKinsey on Smart Grid, 38–44.
Dzene, I, Polikarpova, I., Zogla, L., & Rosa, M, “Application of ISO 50001 for Implementation of Sustainable Energy Action Plans, Energy Procedia, 2015, 72, 111–118. https://doi.org/10.1016/j.egypro.2015.06.016.
Pinzón, J., Corredor, A., Santamaría, F., Hernández, J., & Trujillo, C., Implementación de indicadores energéticos en centros educativos. Caso de estudio: Edificio Alejandro, Revista EAN, 2014, 77, 184–201
Campos, J. C., Rodriguez, C., & Merino, L, Evaluación de indicadores energéticos para sistemas de transporte de productos refinados del petróleo V CIUREE: Congreso de Eficiencia y Gestión Energética, Cartagena – Colombia, 2016.
Salazar, J. Modelo de gestión energética para la optimización del consumo de energía en la planta Mariquita Ecopetrol S.A., MsC Thesis, Maestría en ingeniería industrial, Facultad de Ingeniería y Arquitectura, Departamento de Ingeniería Industrial, Universidad Nacional de Colombia, Manizales, 2011.
Song, C., Li, M., Wen, Z., He, Y. L., Tao, W. Q., Li, Y., Wei, X., Yin, X., Huang, X, Research on energy efficiency evaluation based on indicators for industry sectors in China, Applied Energy, 2014, 134, 550–562. https://doi.org/10.1016/j.apenergy.2014.08.049
May, G., Barletta, I., Stahl, B., Taisch, M., Energy management in production: A novel method to develop key performance indicators for improving energy efficiency, Applied Energy, 2015, 149, 46–61. https://doi.org/10.1016/j.apenergy.2015.03.065.
Entrop, A. G., Brouwers, H. J. H., & Reinders, A. H. M. E, Evaluation of energy performance indicators and financial aspects of energy saving techniques in residential real estate, Energy and Buildings, 2010, 42(5), 618–629. https://doi.org/10.1016/j.enbuild.2009.10.032
Corsini, A., Bonacina, F., Feudo, S., Lucchetta, F., & Marchegiani, A, Multivariate KPI for energy management of cooling systems in food industry, Energy Procedia, 2016, 101(September), 297–304. https://doi.org/10.1016/j.egypro.2016.11.038
Cascella, G. L., Cupertino, F., & Davide, C, Energy metering optimization in flour mill plants for ISO 50001 implementation, IEEE Workshop on Environmental, Energy, and Structural Monitoring Systems EESMS 2016, Bari-Italy, 2016.
Campos, J. C, Herramientas de caracterización energética, Diplomado Gestión Energética Avanzada - Programa SGIE, Universidad Nacional de Colombia, Bogotá, 2011.
Proskuryakova, L., & Kovalev, A, Measuring energy efficiency: Is energy intensity a good evidence base?, Applied Energy, 2015, 138, 450–459. https://doi.org/10.1016/j.apenergy.2014.10.060
Montaño, W., Desarrollo de una plataforma computacional para modelos de flujo de potencia en tiempo real, utilizando medición inteligente y un sistema de gestión de información, MsC Thesis, Maestría en automatización industrial, Facultad de Ingeniería, Departamento de Ingeniería Eléctrica y Electrónica, Universidad Nacional de Colombia, Bogotá, 2017.
Tellez, S., Alvarez, D., Montano, W., Vargas, C., Cespedes, R., Parra, E., & Rosero, J. (2014). National Laboratory of Smart Grids (LAB+i) at the National University of Colombia-Bogotá Campus. IEEE PES Transmission and Distribution Conference and Exposition, PES T&D-LA, Medellín – Colombia, 2014. https://doi.org/10.1109/TDC-LA.2014.6955185
Céspedes, R, A reference model for the electrical energy system based on Smart Grids, Sixth IEEE/PES Transmission and Distribution: Latin America Conference and Exposition (T&D-LA), Medellín – Colombia, 2012.
Maya, S. R. De, & Lopez, I. Metodología del Diseño Experimental. In Métodos de investigación social y de la empresa, 2013, (1°, pp. 485–502). Murcia, España: Ediciones Pirámide.
Oficina de Gestión Ambiental. Universidad Nacional de Colombia - Sede Bogotá, Programa Gestión Integral de Energía, [Online]. Avalaible: http://oga.bogota.unal.edu.co/programas/gestion-integral-de-energia/
North American Electric Reliability Corporation - NERC, 2011 Demand Response Availability Report, [Online]. Avalaible: https://www.nerc.com/docs/pc/dadswg/2011%20DADS%20Report.pdf
Downloads
