Literatur Review Tantangan dan Teknologi dalam Pengembangan Advance Metering Infrastructure (AMI)
Abstract
The fundamental challenges related to the inability of traditional metering infrastructure to provide accurate and fast data and the lack of visibility to manage electricity usage information have driven the development of smart metering solutions. Smart metering, which is part of the smart grid architecture, has evolved over the years along with the needs of the electric power system infrastructure that requires efficient energy management initiatives. Advanced Metering Infrastructure (AMI) is one of the technologies being developed as a smart metering infrastructure. AMI consists of systems and networks, which are responsible for collecting and analyzing data received from smart meters. In addition, AMI also manages various electricity-related applications and services based on data collected from smart meters. The implementation of AMI has been proven to provide various positive results for both energy service providers and consumers. AMI is able to increase the accuracy of energy consumption recording by up to ±0.5% and reduce billing errors by up to 95%. Therefore, AMI plays an important role in the smooth functioning of the smart grid. In developing AMI technology, of course, there are challenges. Therefore, this paper provides an overview of smart metering technology, its design requirements, protocols and challenges, and policy issues.
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References
[1] Oladipo, M.A. and Olusesan, T.K. (2017) ‘A model unavailability perspective of existing nigerian township electricity distribution’, International Journal of Electrical and Computer Engineering (IJECE), Vol. 7, No. 1, pp.77–85.
[2] Sanni, T.F., Ayo, O.O., Adoghe, A.U. and Ibhaze, A.E. (2017) ‘A hybrid thermo-electric solar based system for energy efficiency in microgrids’, IEEE PES PowerAfrica, pp.518–522.
[3] Hart, G. (1989) ‘Residential energy monitoring and computerized surveillance via utility power flows’, IEEE Technol. Soc. Mag., Vol. 8, No. 2, pp.12–19.
[4] Chan, M., Campo, E., Estève, D. and Fourniols, J-Y. (2009) ‘Smart homes – current features and future perspectives’, Maturitas, Vol. 64, No. 2, pp.90–97.
[5] AlAbdulkarim, L. and Lukszo, Z. (2011) ‘Impact of privacy concerns on consumers’ acceptance of smart metering in the Netherlands’, IEEE International Conference on Networking, Sensing and Control, pp.287–292.
[6] McKenna, E., Richardson, I. and Thomson, M. (2012) ‘Smart meterdata: balancing consumer privacy concerns with legitimate applications’, Energy Policy, Vol. 41, pp.807–814.
[7] Wilson, C., Hargreaves, T. and Hauxwell-Baldwin, R. (2017) ‘Benefits and risks of smart home technologies’, Energy Policy, Vol. 103, pp.72–83.
[8] Bhati, A., Hansen, M. and Chan, C.M. (2017) ‘Energy conservation through smart homes in a smart city: a lesson for Singapore households’, Energy Policy, Vol. 104, pp.230–239.
[9] PBB (2015) Paris Agreement, United Nations.
[10] Buchanan, K., Banks, N., Preston, I. and Russo, R. (2016) ‘The British public’s perception of the UK smart metering initiative: threats and opportunities’, Energy Policy, Vol. 91, pp.87–97.
[11] Guo, P., Li, V.O.K. and Lam, J.C.K. (2017) ‘Smart demand response in China: challenges and drivers’, Energy Policy, Vol. 107, pp.1–10.
[12] Faruqui, A., Harris, D. and Hledik, R. (2010) ‘Unlocking the h53 billion savings from smart meters in the EU: how increasing the adoption of dynamic tariffs could make or break the EU’s smart grid investment’, Energy Policy, Vol. 38, pp.6222–6231.
[13] Jennings, G.M. (2013) ‘A smarter plan? A policy comparison between Great Britain and Ireland’s deployment strategies for rolling out new metering technologies’, Energy Policy, Vol. 57, pp.462–468.
[14] McHenry, M.P. (2013) ‘Technical and governance considerations for advanced metering infrastructure/smart meters: technology, security, uncertainty, costs, benefits, and risks’, Energy Policy, Vol. 59, pp.834–842.
[15] Hossein Shahinzadeh, Ayla Hasanalizadeh-Khosroshahi, “Implementation of Smart Metering Systems: Challenges and Solutions”, Indonesian Journal of Electrical Engineering, Vol.12, No.7, pp. 5104 ~ 5109, July 2014.
[16] Sören, F. and Ingmar, B. (2015) ‘Privacy-aware smart metering: a survey’, IEEE, pp.1088–1101.
[17] Augustus Ehiremen Ibhaze. (2020) ‘A Review on Smart Metering Infrastructure’, International Journal of Energy Technology and Policy, Vol. 16, No. 3.
[18] Labs, S. (n.d.) Smart Metering Brings Intelligence and Connectivity to Utilities, Green Energy and Natural Resource Management [online] http://www.silabs.com/Support%20Documents/TechnicalDocs/Designing-Low-Power-Metering-Applications.pdf (accessed 4 April 2017).
[19] Mohassel, R.R., Fung, A.S., Mohammadi, F. and Raahemifar, K. (2014) ‘A survey on advanced metering infrastructure and its application in smart grids’, CCECE, pp.1–8.
[20] Lipošak, Z. and Boškovi, M. (2013) ‘Survey of smart metering communication technologies’, EUROCON, 2013 IEEE, pp.1391–1400.
[21] Ajoy Kumar Chakraborty and Navonita Sharma. (2016) ‘Advance Metering Infrastructure: Technology and Challenges’, IEEE, 978-1-5090-2157.
[22] K.S.K Waranga, Sisil Kumarawadu, D.P Chandima, “Smart Metering Design and Applications”, SpringerBriefs in Applied Sciences and Technology, DOI 10.1007/978-981-4451-82-6, 2014.
[23] Espinoza, M., Joye, C., Belmans, R. and DeMoor, B. (2005) ‘Short-term load forecasting, profile identification, and customer segmentation: a methodology based on periodic time series’, IEEE Transactions on Power Systems, Vol. 20, No. 3, pp.1622–1630.
[24] Liu, H., Yao, Z., Eclund, T. and Back, B. (2012) ‘From Smart Meter Data to Pricing Intelligence: Real time BI for pricing intelligence.
[25] Sorrell, S., Dimitropoulos, J. and Sommerville, M. (2009) ‘Empirical estimates of the direct rebound effect: a review’, Energy Policy, Vol. 37, pp.1356–1371.
[26] Taouil, K., Jellad, T. and Chtourou, Z. (2014) ‘Community-coupled microgrids for the implementation of a smart grid in Tunisia’, International Journal of Energy Technology and Policy, Vol. 10, Nos. 3–4, pp.183–199.
[27] Kim, K.H., Youn, H.S. and Kang, Y.C. (2000) ‘Short-term load forecasting for special days in anomalous load conditions using neural networks and fuzzy inference method’, IEEE Transactions on Power Systems, Vol. 15, No. 2, pp.559–565.
[28] Verdu, S.V. et al. (2006) ‘Classification, filtering, and identification of electrical customer load patterns through the use of self-organizing maps’, IEEE Transactions on Power Systems, Vol. 21, No. 4, pp.1672–1682.
[29] Pao, H. (2007) ‘Forecasting electricity market pricing using artificial neural networks’, Energy Conversion and Management, Vol. 48, No. 3, pp.907–912.
[30] Liao, H. and Niebur, D. (2003) ‘Load profile estimation in electric transmission networks using independent component analysis’, IEEE Transactions on Power Systems, Vol. 18, No. 2, pp.707–715.
[31] Nagi, J., Yap, K.S., Tiong, S.K. and Ahmed, S.K. (2008) ‘Electrical power load forecasting using hybrid self-organizing maps and support vector machines’, The 2nd International Power Engineering and Optimization Conference (PEOCO 2008), Shah Alam, Selangor, Malaysia, June.
[32] Kanakasabapathy, P. and Shanti Swarup, K. (2009) ‘Market operations in future Indian restructured power system scenario’, International Journal of Energy Technology and Policy, Vol. 7, No. 1, pp.78–94.
[33] Farouqui, A. (2010) ‘Ethics of dynamic pricing’, The Electricity Journal, Vol. 23, No. 6, pp.13–27.
[34] Moutinho, V.M.F. (2015) ‘Evaluating the strategic supply per power plant: evidence from the Spanish wholesale electricity market’, International Journal of Energy Technology and Policy, Vol. 11, No. 2, pp.97–126.
[35] John Chan, Ricky Ip, K. W. Cheng and Ken S.P. Chan. (2019) ‘Advance Metering Infrastructure Deployment and Challenges’, IEEE. 978-1-5386-7434-5.
[36] Kagiannas, G.A., Flamos, A., Askounis, D.T. and Psarras, J. (2004) ‘Energy policy indicators for the assessment of the Euro-Mediterranean energy cooperation’, International Journal of Energy Technology and Policy, Vol. 2, No. 4, pp.301–322.
[37] Abotah, R. and Daim, T.U. (2007) ‘Towards building a multi perspective policy development framework for transition into renewable energy’, Sustainable Energy Technologies and Assessments, Vol. 21, pp.66–88.
[38] Amer, M. and Daim, T.U. (2010) ‘Application of technology roadmaps for renewable energy sector’, Technological Forecasting and Social Change, Vol. 77, No. 8, pp.1355–1370.
[39] Amer, M. and Daim, T.U. (2011) ‘Selection of renewable energy technologies for a developing county: a case of Pakistan’, Energy for Sustainable Development, Vol. 15, No. 4, pp.420–435.
[40] Visessonchok, T. (2016) ‘Detection and introduction of emerging technologies for green buildings in Thailand’, International Journal of Energy Technology and Policy, Vol. 12, No. 1, pp.2–19.
[41] Misra, S., Maheswaran, M. and Hashmi, S. (2017) Security Challenges and Approaches in Internet of Things, in: SpringerBriefs in Electrical and Computer Engineering, Springer International Publishing AG, Switzerland
[2] Sanni, T.F., Ayo, O.O., Adoghe, A.U. and Ibhaze, A.E. (2017) ‘A hybrid thermo-electric solar based system for energy efficiency in microgrids’, IEEE PES PowerAfrica, pp.518–522.
[3] Hart, G. (1989) ‘Residential energy monitoring and computerized surveillance via utility power flows’, IEEE Technol. Soc. Mag., Vol. 8, No. 2, pp.12–19.
[4] Chan, M., Campo, E., Estève, D. and Fourniols, J-Y. (2009) ‘Smart homes – current features and future perspectives’, Maturitas, Vol. 64, No. 2, pp.90–97.
[5] AlAbdulkarim, L. and Lukszo, Z. (2011) ‘Impact of privacy concerns on consumers’ acceptance of smart metering in the Netherlands’, IEEE International Conference on Networking, Sensing and Control, pp.287–292.
[6] McKenna, E., Richardson, I. and Thomson, M. (2012) ‘Smart meterdata: balancing consumer privacy concerns with legitimate applications’, Energy Policy, Vol. 41, pp.807–814.
[7] Wilson, C., Hargreaves, T. and Hauxwell-Baldwin, R. (2017) ‘Benefits and risks of smart home technologies’, Energy Policy, Vol. 103, pp.72–83.
[8] Bhati, A., Hansen, M. and Chan, C.M. (2017) ‘Energy conservation through smart homes in a smart city: a lesson for Singapore households’, Energy Policy, Vol. 104, pp.230–239.
[9] PBB (2015) Paris Agreement, United Nations.
[10] Buchanan, K., Banks, N., Preston, I. and Russo, R. (2016) ‘The British public’s perception of the UK smart metering initiative: threats and opportunities’, Energy Policy, Vol. 91, pp.87–97.
[11] Guo, P., Li, V.O.K. and Lam, J.C.K. (2017) ‘Smart demand response in China: challenges and drivers’, Energy Policy, Vol. 107, pp.1–10.
[12] Faruqui, A., Harris, D. and Hledik, R. (2010) ‘Unlocking the h53 billion savings from smart meters in the EU: how increasing the adoption of dynamic tariffs could make or break the EU’s smart grid investment’, Energy Policy, Vol. 38, pp.6222–6231.
[13] Jennings, G.M. (2013) ‘A smarter plan? A policy comparison between Great Britain and Ireland’s deployment strategies for rolling out new metering technologies’, Energy Policy, Vol. 57, pp.462–468.
[14] McHenry, M.P. (2013) ‘Technical and governance considerations for advanced metering infrastructure/smart meters: technology, security, uncertainty, costs, benefits, and risks’, Energy Policy, Vol. 59, pp.834–842.
[15] Hossein Shahinzadeh, Ayla Hasanalizadeh-Khosroshahi, “Implementation of Smart Metering Systems: Challenges and Solutions”, Indonesian Journal of Electrical Engineering, Vol.12, No.7, pp. 5104 ~ 5109, July 2014.
[16] Sören, F. and Ingmar, B. (2015) ‘Privacy-aware smart metering: a survey’, IEEE, pp.1088–1101.
[17] Augustus Ehiremen Ibhaze. (2020) ‘A Review on Smart Metering Infrastructure’, International Journal of Energy Technology and Policy, Vol. 16, No. 3.
[18] Labs, S. (n.d.) Smart Metering Brings Intelligence and Connectivity to Utilities, Green Energy and Natural Resource Management [online] http://www.silabs.com/Support%20Documents/TechnicalDocs/Designing-Low-Power-Metering-Applications.pdf (accessed 4 April 2017).
[19] Mohassel, R.R., Fung, A.S., Mohammadi, F. and Raahemifar, K. (2014) ‘A survey on advanced metering infrastructure and its application in smart grids’, CCECE, pp.1–8.
[20] Lipošak, Z. and Boškovi, M. (2013) ‘Survey of smart metering communication technologies’, EUROCON, 2013 IEEE, pp.1391–1400.
[21] Ajoy Kumar Chakraborty and Navonita Sharma. (2016) ‘Advance Metering Infrastructure: Technology and Challenges’, IEEE, 978-1-5090-2157.
[22] K.S.K Waranga, Sisil Kumarawadu, D.P Chandima, “Smart Metering Design and Applications”, SpringerBriefs in Applied Sciences and Technology, DOI 10.1007/978-981-4451-82-6, 2014.
[23] Espinoza, M., Joye, C., Belmans, R. and DeMoor, B. (2005) ‘Short-term load forecasting, profile identification, and customer segmentation: a methodology based on periodic time series’, IEEE Transactions on Power Systems, Vol. 20, No. 3, pp.1622–1630.
[24] Liu, H., Yao, Z., Eclund, T. and Back, B. (2012) ‘From Smart Meter Data to Pricing Intelligence: Real time BI for pricing intelligence.
[25] Sorrell, S., Dimitropoulos, J. and Sommerville, M. (2009) ‘Empirical estimates of the direct rebound effect: a review’, Energy Policy, Vol. 37, pp.1356–1371.
[26] Taouil, K., Jellad, T. and Chtourou, Z. (2014) ‘Community-coupled microgrids for the implementation of a smart grid in Tunisia’, International Journal of Energy Technology and Policy, Vol. 10, Nos. 3–4, pp.183–199.
[27] Kim, K.H., Youn, H.S. and Kang, Y.C. (2000) ‘Short-term load forecasting for special days in anomalous load conditions using neural networks and fuzzy inference method’, IEEE Transactions on Power Systems, Vol. 15, No. 2, pp.559–565.
[28] Verdu, S.V. et al. (2006) ‘Classification, filtering, and identification of electrical customer load patterns through the use of self-organizing maps’, IEEE Transactions on Power Systems, Vol. 21, No. 4, pp.1672–1682.
[29] Pao, H. (2007) ‘Forecasting electricity market pricing using artificial neural networks’, Energy Conversion and Management, Vol. 48, No. 3, pp.907–912.
[30] Liao, H. and Niebur, D. (2003) ‘Load profile estimation in electric transmission networks using independent component analysis’, IEEE Transactions on Power Systems, Vol. 18, No. 2, pp.707–715.
[31] Nagi, J., Yap, K.S., Tiong, S.K. and Ahmed, S.K. (2008) ‘Electrical power load forecasting using hybrid self-organizing maps and support vector machines’, The 2nd International Power Engineering and Optimization Conference (PEOCO 2008), Shah Alam, Selangor, Malaysia, June.
[32] Kanakasabapathy, P. and Shanti Swarup, K. (2009) ‘Market operations in future Indian restructured power system scenario’, International Journal of Energy Technology and Policy, Vol. 7, No. 1, pp.78–94.
[33] Farouqui, A. (2010) ‘Ethics of dynamic pricing’, The Electricity Journal, Vol. 23, No. 6, pp.13–27.
[34] Moutinho, V.M.F. (2015) ‘Evaluating the strategic supply per power plant: evidence from the Spanish wholesale electricity market’, International Journal of Energy Technology and Policy, Vol. 11, No. 2, pp.97–126.
[35] John Chan, Ricky Ip, K. W. Cheng and Ken S.P. Chan. (2019) ‘Advance Metering Infrastructure Deployment and Challenges’, IEEE. 978-1-5386-7434-5.
[36] Kagiannas, G.A., Flamos, A., Askounis, D.T. and Psarras, J. (2004) ‘Energy policy indicators for the assessment of the Euro-Mediterranean energy cooperation’, International Journal of Energy Technology and Policy, Vol. 2, No. 4, pp.301–322.
[37] Abotah, R. and Daim, T.U. (2007) ‘Towards building a multi perspective policy development framework for transition into renewable energy’, Sustainable Energy Technologies and Assessments, Vol. 21, pp.66–88.
[38] Amer, M. and Daim, T.U. (2010) ‘Application of technology roadmaps for renewable energy sector’, Technological Forecasting and Social Change, Vol. 77, No. 8, pp.1355–1370.
[39] Amer, M. and Daim, T.U. (2011) ‘Selection of renewable energy technologies for a developing county: a case of Pakistan’, Energy for Sustainable Development, Vol. 15, No. 4, pp.420–435.
[40] Visessonchok, T. (2016) ‘Detection and introduction of emerging technologies for green buildings in Thailand’, International Journal of Energy Technology and Policy, Vol. 12, No. 1, pp.2–19.
[41] Misra, S., Maheswaran, M. and Hashmi, S. (2017) Security Challenges and Approaches in Internet of Things, in: SpringerBriefs in Electrical and Computer Engineering, Springer International Publishing AG, Switzerland
Published
2025-07-29
How to Cite
PUTRA, I Made Agus Artha; MANUABA, Ida Bagus Gede.
Literatur Review Tantangan dan Teknologi dalam Pengembangan Advance Metering Infrastructure (AMI).
Majalah Ilmiah Teknologi Elektro, [S.l.], v. 24, n. 1, p. 1-8, july 2025.
ISSN 2503-2372.
Available at: <http://ojs.unud.ac.id/index.php/mite/article/view/110947>. Date accessed: 29 sep. 2025.
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Articles
This work is licensed under a Creative Commons Attribution 4.0 International License
