{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,24]],"date-time":"2026-01-24T15:05:15Z","timestamp":1769267115222,"version":"3.49.0"},"reference-count":93,"publisher":"MDPI AG","issue":"5","license":[{"start":{"date-parts":[[2020,3,6]],"date-time":"2020-03-06T00:00:00Z","timestamp":1583452800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>The transition of the energy system into a more efficient state requires innovative ideas to finance new schemes and engage people into adjusting their behavioural patterns concerning consumption. Effective energy management combined with Information and Communication Technologies (ICTs) open new opportunities for local and regional authorities, but also for energy suppliers, utilities and other obligated parties, or even energy cooperatives, to implement mechanisms that allow people to become more efficient either by producing and trading energy or by reducing their energy consumption. In this paper, a novel framework is proposed connecting energy savings with a digital energy currency. This framework builds reward schemes where the energy end-users could benefit financially from saving energy, by receiving coins according to their real consumption compared to the predicted consumption if no actions were to take place. A pilot appraisal of such a scheme is presented for the case of Bahrain, so as to simulate the behaviour of the proposed framework in order for it to become a viable choice for intelligent energy management in future action plans.<\/jats:p>","DOI":"10.3390\/s20051456","type":"journal-article","created":{"date-parts":[[2020,3,6]],"date-time":"2020-03-06T09:26:41Z","timestamp":1583486801000},"page":"1456","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":20,"title":["From Intelligent Energy Management to Value Economy through a Digital Energy Currency: Bahrain City Case Study"],"prefix":"10.3390","volume":"20","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-5488-4006","authenticated-orcid":false,"given":"Vangelis","family":"Marinakis","sequence":"first","affiliation":[{"name":"Decision Support Systems Laboratory, School of Electrical and Computer Engineering, National Technical University of Athens, 15780 Athens, Greece"}]},{"given":"Haris","family":"Doukas","sequence":"additional","affiliation":[{"name":"Decision Support Systems Laboratory, School of Electrical and Computer Engineering, National Technical University of Athens, 15780 Athens, Greece"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3656-4874","authenticated-orcid":false,"given":"Konstantinos","family":"Koasidis","sequence":"additional","affiliation":[{"name":"Decision Support Systems Laboratory, School of Electrical and Computer Engineering, National Technical University of Athens, 15780 Athens, Greece"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2141-1944","authenticated-orcid":false,"given":"Hanan","family":"Albuflasa","sequence":"additional","affiliation":[{"name":"Department of Physics, College of Science, University of Bahrain, Zallaq 32038, Bahrain"}]}],"member":"1968","published-online":{"date-parts":[[2020,3,6]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"394","DOI":"10.1016\/j.enbuild.2007.03.007","article-title":"A review on buildings energy consumption information","volume":"40","author":"Ortiz","year":"2008","journal-title":"Energy Build."},{"key":"ref_2","unstructured":"Covenant of Mayors for Climate and Energy (2020, January 08). The Covenant of Mayors for Climate and Energy Reporting Guidelines. Available online: https:\/\/www.covenantofmayors.eu\/IMG\/pdf\/Covenant_ReportingGuidelines.pdf."},{"key":"ref_3","unstructured":"EPRS-European Parliamentary Research Service (2020, January 08). Revised Energy Efficiency Directive. Briefing EU Legislation in Progress. Available online: http:\/\/www.europarl.europa.eu\/RegData\/etudes\/BRIE\/2017\/595923\/EPRS_BRI(2017)595923_EN.pdf."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.omega.2016.07.005","article-title":"Multicriteria decision support in local energy planning: An evaluation of alternative scenarios for the sustainable energy action plan","volume":"69","author":"Marinakis","year":"2017","journal-title":"Omega"},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"46","DOI":"10.1016\/j.enbuild.2016.02.025","article-title":"Managing demand uncertainty with cost-for-deviation retail pricing","volume":"118","author":"Zhu","year":"2016","journal-title":"Energy Build."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"85","DOI":"10.1016\/j.rser.2014.08.039","article-title":"Heating and cooling energy trends and drivers in buildings","volume":"41","author":"Cabeza","year":"2015","journal-title":"Renew. Sustain. Energy Rev."},{"key":"ref_7","unstructured":"EEA-European Environment Agency (2019, December 17). Final Energy Consumption by Sector and Fuel. Available online: https:\/\/www.eea.europa.eu\/data-and-maps\/indicators\/final-energy-consumption-by-sector-9\/assessment-4?fbclid=IwAR3BUOwd1MLEiWpnd6NSCTWgviQEOM_HMBqAgSaAyMgN_DndkWvCaJUyhEI."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"194","DOI":"10.1016\/j.apenergy.2015.01.145","article-title":"Intelligent energy and thermal comfort management in grid-connected microgrids with heterogeneous occupancy schedule","volume":"149","author":"Korkas","year":"2015","journal-title":"Appl. Energy"},{"key":"ref_9","unstructured":"Sharpe, T.R., Foster, J.A., and Poston, A. (2015, January 15\u201317). Monitored environmental conditions in new energy efficient housing in Scotland\u2013Effects by and on occupants. Proceedings of the International Seminar on Renewable Energy and Sustainable Development, Rinchending, Phuentsholing, Bhutan."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"70","DOI":"10.1109\/TCE.2013.6490243","article-title":"Intelligent household LED lighting system considering energy efficiency and user satisfaction","volume":"59","author":"Byun","year":"2013","journal-title":"IEEE Trans. Consum. Electron."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"556","DOI":"10.1016\/j.enpol.2005.11.010","article-title":"Polices for Increasing Energy Efficiency: Thirty Years of Experience in OECD Countries","volume":"34","author":"Geller","year":"2006","journal-title":"Energy Policy"},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"600","DOI":"10.1109\/TASE.2014.2356337","article-title":"A hybrid physics-based and data driven approach to optimal control of building cooling\/heating systems","volume":"13","author":"Vaghefi","year":"2016","journal-title":"IEEE Trans. Autom. Sci. Eng."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"87","DOI":"10.1016\/j.apenergy.2012.10.037","article-title":"Achieving better energy-efficient air conditioning\u2013A review of technologies and strategies","volume":"104","author":"Chua","year":"2013","journal-title":"Appl. Energy"},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"4095","DOI":"10.1016\/j.rser.2012.03.034","article-title":"Energy behaviours as promoters of energy efficiency: A 21st century review","volume":"16","author":"Lopes","year":"2012","journal-title":"Renew. Sustain. Energy Rev."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"84","DOI":"10.1016\/j.erss.2015.03.004","article-title":"Towards more effective behavioural energy policy: An integrative modelling approach to residential energy consumption in Europe","volume":"7","author":"Lopes","year":"2015","journal-title":"Energy Res. Soc. Sci."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"2807","DOI":"10.1016\/j.enpol.2009.03.043","article-title":"Influencing households\u2019 energy behaviour\u2014how is this done and on what premises?","volume":"37","author":"Gyberg","year":"2009","journal-title":"Energy Policy"},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"436","DOI":"10.1109\/TCE.2011.5955177","article-title":"A smart energy distribution and management system for renewable energy distribution and context-aware services based on user patterns and load forecasting","volume":"57","author":"Byun","year":"2011","journal-title":"IEEE Trans. Consum. Electron."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"90","DOI":"10.1109\/TCE.2011.5735486","article-title":"Development of a self-adapting intelligent system for building energy saving and context-aware smart services","volume":"57","author":"Byun","year":"2011","journal-title":"IEEE Trans. Consum. Electron."},{"key":"ref_19","doi-asserted-by":"crossref","unstructured":"Marinakis, V., Nikolopoulou, C., and Doukas, H. (2018, January 19\u201323). Digitizing Energy Savings in Sustainable Smart Cities: Introducing a Virtual Energy-Currency Approach. Proceedings of the IEEE International Conference on Pervasive Computing and Communications Workshops (PerCom Workshops), Athens, Greece.","DOI":"10.1109\/PERCOMW.2018.8480235"},{"key":"ref_20","doi-asserted-by":"crossref","unstructured":"Park, S., Lee, S., Park, S., and Park, S. (2019). AI-based physical and virtual platform with 5-layered architecture for sustainable smart energy city development. Sustainability, 11.","DOI":"10.3390\/su11164479"},{"key":"ref_21","first-page":"32","article-title":"Switzerland and the 2,000-Watt society","volume":"1","author":"Morrow","year":"2008","journal-title":"Sustain. J. Rec."},{"key":"ref_22","unstructured":"New Economics Foundation (2019, November 17). Energising Money: An Introduction to Energy Currencies and Accounting. Available online: http:\/\/www.i-r-e.org\/bdf\/docs\/nef.pdf."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"1749","DOI":"10.1016\/j.enpol.2009.11.049","article-title":"Tangible and fungible energy: Hybrid energy market and currency system for total energy management. A Masdar City Case Study","volume":"38","author":"Sgouridis","year":"2010","journal-title":"Energy Policy"},{"key":"ref_24","doi-asserted-by":"crossref","unstructured":"Samad, W., and Azar, E. (2019). Intelligent energy management within the smart cities: An eu-gcc cooperation opportunity. Smart Cities in the Gulf, Palgrave Macmillan.","DOI":"10.1007\/978-981-13-2011-8"},{"key":"ref_25","unstructured":"Origami Energy (2020, February 22). Enabling Cleaner Power Systems through Technology. Available online: https:\/\/www.origamienergy.com\/."},{"key":"ref_26","unstructured":"SMARKIA (2020, February 22). Energy Efficiency Solution for Major Energy Consumers. Available online: https:\/\/www.smarkia.com\/en."},{"key":"ref_27","unstructured":"PLOTWATT (2020, February 22). Measure, Model, and Simulate the Impact of Energy Initiatives Before You Invest. Available online: https:\/\/www.plotwatt.com\/."},{"key":"ref_28","unstructured":"NUUKA (2020, February 22). Real-Time Data Platform for Real Estate that Drives Value, Sustainability and Comfort. Available online: https:\/\/www.nuukasolutions.com\/home."},{"key":"ref_29","unstructured":"Plugwise (2020, February 22). Zone Control for the Ideal Temperature per Room. Available online: https:\/\/www.plugwise.com\/en_US\/."},{"key":"ref_30","unstructured":"OptiWatti (2020, February 22). Smart Energy Management. Available online: https:\/\/www.optiwatti.com\/."},{"key":"ref_31","unstructured":"Loop (2020, February 22). Meet Loop the Energy-Saving Assistant for Your Home. Available online: https:\/\/loop.homes\/."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"12","DOI":"10.1016\/j.ausmj.2016.12.001","article-title":"Understanding how gamification influences behaviour in social marketing","volume":"25","author":"Mitchell","year":"2017","journal-title":"Australas. Mark. J."},{"key":"ref_33","first-page":"13","article-title":"Towards building energy efficiency for developing countries","volume":"3","year":"2013","journal-title":"Bonfring Int. J. Ind. Eng. Manag. Sci."},{"key":"ref_34","doi-asserted-by":"crossref","unstructured":"Yao, R. (2013). Occupant behavior and building performance. Design and Management of Sustainable Built Environments, Springer.","DOI":"10.1007\/978-1-4471-4781-7"},{"key":"ref_35","doi-asserted-by":"crossref","unstructured":"Li, S., Deng, K., and Zhou, M. (2014, January 18\u201322). Social incentive policies to engage commercial building occupants in demand response. Proceedings of the IEEE International Conference on Automation Science and Engineering (CASE), Taipei, Taiwan.","DOI":"10.1109\/CoASE.2014.6899357"},{"key":"ref_36","unstructured":"IEA-International Energy Agency, Paris (2020, January 08). Transition to Sustainable Buildings: Strategies and Opportunities to 2050. Available online: https:\/\/www.oecd-ilibrary.org\/energy\/transition-to-sustainable-buildings_9789264202955-en."},{"key":"ref_37","unstructured":"Hassan, M. (2020, January 08). Peak-Load Pricing, Working Paper. Available online: https:\/\/www.researchgate.net\/publication\/313185818_Peak-Load_Pricing."},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"169","DOI":"10.1016\/S0301-4215(00)00004-5","article-title":"Energy efficiency in buildings through information\u2013Swedish perspective","volume":"28","author":"Henryson","year":"2000","journal-title":"Energy Policy"},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"229","DOI":"10.1007\/s11149-013-9215-x","article-title":"Motivating energy suppliers to promote energy conservation","volume":"43","author":"Chu","year":"2013","journal-title":"J. Regul. Econ."},{"key":"ref_40","unstructured":"Eicherm\u00fcller, J., Furlan, M., Habersbrunner, K., and Kordi\u0107, Z. (2019, December 16). Energy Cooperatives: Comparative Analysis in Eastern Partnership Countries and Western Balkans. Study Made by Women Engage for a Common Future (WECF) and Zelena Energetska Zadruga (ZEZ). Available online: http:\/\/www.wecf.eu\/german\/publikationen\/EnergyCoops_LongOnline.pdf."},{"key":"ref_41","unstructured":"Debor, S. (2014). The socio-economic power of renewable energy production cooperatives in Germany: Results of an empirical assessment. Wuppertal Papers, Wuppertal Institut f\u00fcr Klima, Umwelt, Energie, Wuppertal. No. 187."},{"key":"ref_42","doi-asserted-by":"crossref","unstructured":"Luan, H., and Leng, J. (2016, January 28\u201330). Design of energy monitoring system based on IoT. Proceedings of the 2016 Chinese Control and Decision Conference (CCDC), Yinchuan, China.","DOI":"10.1109\/CCDC.2016.7532219"},{"key":"ref_43","doi-asserted-by":"crossref","unstructured":"Chen, Y.Y., and Lin, Y.H. (2019). A smart autonomous time-and frequency-domain analysis current sensor-based power meter prototype developed over fog-cloud analytics for demand-side management. Sensors, 19.","DOI":"10.3390\/s19204443"},{"key":"ref_44","doi-asserted-by":"crossref","unstructured":"Marinakis, V., and Doukas, H. (2018). An advanced IoT-based system for intelligent energy management in buildings. Sensors, 18.","DOI":"10.3390\/s18020610"},{"key":"ref_45","doi-asserted-by":"crossref","unstructured":"Marinakis, V., Doukas, H., Tsapelas, J., Mouzakitis, S., Sicilia, \u00c1., Madrazo, L., and Sgouridis, S. (2019). From big data to smart energy services: An application for intelligent energy management. Future Gener. Comput. Syst., in press.","DOI":"10.1016\/j.future.2018.04.062"},{"key":"ref_46","doi-asserted-by":"crossref","first-page":"297","DOI":"10.1016\/j.rser.2018.02.002","article-title":"Forecasting methods in energy planning models","volume":"88","author":"Debnath","year":"2018","journal-title":"Renew. Sustain. Energy Rev."},{"key":"ref_47","doi-asserted-by":"crossref","first-page":"3165","DOI":"10.1016\/j.enpol.2005.02.010","article-title":"Use of artificial neural networks for transport energy demand modeling","volume":"34","author":"Murat","year":"2006","journal-title":"Energy Policy"},{"key":"ref_48","doi-asserted-by":"crossref","first-page":"284","DOI":"10.1016\/j.enbuild.2015.12.050","article-title":"Forecasting diurnal cooling energy load for institutional buildings using Artificial Neural Networks","volume":"121","author":"Deb","year":"2016","journal-title":"Energy Build."},{"key":"ref_49","doi-asserted-by":"crossref","first-page":"71","DOI":"10.1016\/S0925-2312(98)00072-1","article-title":"Artificial neural networks for short-term energy forecasting: Accuracy and economic value","volume":"23","author":"Hobbs","year":"1998","journal-title":"Neurocomputing"},{"key":"ref_50","doi-asserted-by":"crossref","first-page":"43","DOI":"10.5547\/ISSN0195-6574-EJ-Vol19-No4-2","article-title":"Short term energy forecasting with neural networks","volume":"19","author":"McMenamin","year":"1998","journal-title":"Energy J."},{"key":"ref_51","doi-asserted-by":"crossref","first-page":"385","DOI":"10.1109\/TPWRS.2005.860926","article-title":"An optimized adaptive neural network for annual midterm energy forecasting","volume":"21","author":"Tsekouras","year":"2006","journal-title":"IEEE Trans. Power Syst."},{"key":"ref_52","unstructured":"Bonetto, R., and Rossi, M. (2020, January 16). Machine Learning Approaches to Energy Consumption Forecasting in Households. Neural and Evolutionary Computing. Available online: https:\/\/arxiv.org\/abs\/1706.09648."},{"key":"ref_53","doi-asserted-by":"crossref","first-page":"168","DOI":"10.1016\/j.apenergy.2014.02.057","article-title":"Forecasting energy consumption of multi-family residential buildings using support vector regression: Investigating the impact of temporal and spatial monitoring granularity on performance accuracy","volume":"123","author":"Jain","year":"2014","journal-title":"Appl. Energy"},{"key":"ref_54","doi-asserted-by":"crossref","first-page":"1766","DOI":"10.3390\/s7091766","article-title":"Time series forecasting energy-efficient organization of wireless sensor networks","volume":"7","author":"Wang","year":"2007","journal-title":"Sensors"},{"key":"ref_55","doi-asserted-by":"crossref","unstructured":"Oprea, S.V., P\u00eerjan, A., C\u0103ru\u021ba\u0219u, G., Petro\u0219anu, D.M., B\u00e2ra, A., St\u0103nic\u0103, J.L., and Coculescu, C. (2018). Developing a mixed neural network approach to forecast the residential electricity consumption based on sensor recorded data. Sensors, 18.","DOI":"10.3390\/s18051443"},{"key":"ref_56","doi-asserted-by":"crossref","first-page":"598","DOI":"10.1016\/j.apenergy.2019.01.145","article-title":"Optimal energy management strategies for energy internet via deep reinforcement learning approach","volume":"239","author":"Hua","year":"2019","journal-title":"Appl. Energy"},{"key":"ref_57","doi-asserted-by":"crossref","unstructured":"Lee, S., and Choi, D.H. (2019). Reinforcement learning-based energy management of smart home with rooftop solar photovoltaic system, energy storage system, and home appliances. Sensors, 19.","DOI":"10.3390\/s19183937"},{"key":"ref_58","first-page":"01016","article-title":"Deep reinforcement learning solutions for energy microgrids management","volume":"217","author":"Taralla","year":"2016","journal-title":"Eur. Workshop Reinf. Learn."},{"key":"ref_59","doi-asserted-by":"crossref","first-page":"3698","DOI":"10.1109\/TSG.2018.2834219","article-title":"On-line building energy optimization using deep reinforcement learning","volume":"10","author":"Mocanu","year":"2018","journal-title":"IEEE Trans. Smart Grid"},{"key":"ref_60","doi-asserted-by":"crossref","first-page":"646","DOI":"10.1016\/j.enbuild.2016.01.030","article-title":"Unsupervised energy prediction in a smart grid context using reinforcement cross-building transfer learning","volume":"116","author":"Mocanu","year":"2016","journal-title":"Energy Build."},{"key":"ref_61","doi-asserted-by":"crossref","first-page":"39","DOI":"10.1016\/j.ijrefrig.2019.07.018","article-title":"A novel deep reinforcement learning based methodology for short-term HVAC system energy consumption prediction","volume":"107","author":"Liu","year":"2019","journal-title":"Int. J. Refrig."},{"key":"ref_62","doi-asserted-by":"crossref","unstructured":"Lee, S.H., Lee, T., Kim, S., and Park, S. (2019, January 10\u201313). Energy consumption prediction system based on deep learning with edge computing. Proceedings of the 2nd International Conference on Electronics Technology, Chengdu, China.","DOI":"10.1109\/ELTECH.2019.8839589"},{"key":"ref_63","doi-asserted-by":"crossref","first-page":"937","DOI":"10.1016\/j.apenergy.2018.12.061","article-title":"Incentive-based demand response for smart grid with reinforcement learning and deep neural network","volume":"236","author":"Lu","year":"2019","journal-title":"Appl. Energy"},{"key":"ref_64","unstructured":"Power Legder (2019, December 15). Power Legder Whitepaper. Available online: https:\/\/cdn2.hubspot.net\/hubfs\/4519667\/Documents%20\/Power%20Ledger%20Whitepaper.pdf."},{"key":"ref_65","unstructured":"Electrify (2019, December 15). Electrify Whitepaper. Available online: https:\/\/electrify.asia\/technical_whitepaper\/."},{"key":"ref_66","unstructured":"SunContract (2019, December 15). SunContract Whitepaper -An Energy Trading Platform that Utilises Blockchain Technology to Create a New Disruptive Model for Buying and Selling Electricity. Available online: https:\/\/suncontract.org\/res\/whitepaper.pdf."},{"key":"ref_67","unstructured":"Robotina (2019, December 15). Robotina Whitepaper -Internet of Things, Artificial Intelligence and Blockchain Empowering Energy Consumers. Available online: https:\/\/robotinarox.io\/wp-content\/uploads\/2018\/07\/Robotina_WP.pdf."},{"key":"ref_68","unstructured":"WePower (2019, December 15). WePower Whitepaper. Available online: https:\/\/wepower.network\/media\/WhitePaper-WePower_v_2.pdf."},{"key":"ref_69","unstructured":"Bittwatt (2019, December 15). Bittwatt Whitepaper. Available online: https:\/\/ico.bittwatt.com\/static\/files\/Bittwatt-Whitepaper-EN.pdf."},{"key":"ref_70","unstructured":"Solarcoin (2019, December 15). Solarcoin: A Blockchain-Based Solar Energy Incentive. Available online: https:\/\/solarcoin.org\/wp-content\/uploads\/SolarCoin_Policy_Paper_EN-1.pdf."},{"key":"ref_71","unstructured":"Fleming, D. (2005). Energy and the Common Purpose: Descending the Energy Staircase with Tradable Energy Quotas (TEQs), The Lean Economy Connection."},{"key":"ref_72","doi-asserted-by":"crossref","unstructured":"Mihaylov, M., Jurado, S., Narcis, A., Van Moffaert, K., Magrans, I., and Nowe, A. (2014, January 28\u201330). NRGcoin: Virtual currency for trading of renewable energy in smart grids. Proceedings of the International Conference on the European Energy Market, EEM. 1\u20136, Krakow, Poland.","DOI":"10.1109\/EEM.2014.6861213"},{"key":"ref_73","doi-asserted-by":"crossref","first-page":"390","DOI":"10.1016\/j.apenergy.2019.04.132","article-title":"Design and management of a distributed hybrid energy system through smart contract and blockchain","volume":"248","author":"Li","year":"2019","journal-title":"Appl. Energy"},{"key":"ref_74","doi-asserted-by":"crossref","first-page":"12","DOI":"10.2478\/acss-2018-0002","article-title":"Blockchain use cases and their feasibility","volume":"23","year":"2018","journal-title":"Appl. Comput. Syst."},{"key":"ref_75","doi-asserted-by":"crossref","first-page":"234","DOI":"10.1016\/j.apenergy.2017.03.039","article-title":"Blockchain technology in the chemical industry: Machine-to-machine electricity market","volume":"195","author":"Sikorski","year":"2017","journal-title":"Appl. Energy"},{"key":"ref_76","doi-asserted-by":"crossref","first-page":"143","DOI":"10.1016\/j.rser.2018.10.014","article-title":"Blockchain technology in the energy sector: A systematic review of challenges and opportunities","volume":"100","author":"Andoni","year":"2019","journal-title":"Renew. Sustain. Energy Rev."},{"key":"ref_77","doi-asserted-by":"crossref","first-page":"1385","DOI":"10.1016\/j.apenergy.2018.07.012","article-title":"Energy demand side management within micro-grid networks enhanced by blockchain","volume":"228","author":"Noor","year":"2018","journal-title":"Appl. Energy"},{"key":"ref_78","unstructured":"Brooklyn (2019, December 18). Brooklyn Microgrid. Available online: http:\/\/brooklynmicrogrid.com\/."},{"key":"ref_79","doi-asserted-by":"crossref","first-page":"870","DOI":"10.1016\/j.apenergy.2017.06.054","article-title":"Designing microgrid energy markets: A case study: The Brooklyn microgrid","volume":"210","author":"Mengelkamp","year":"2018","journal-title":"Appl. Energy"},{"key":"ref_80","unstructured":"Mishra, S. (2017). Energy Consumption\u2013Bitcoin\u2019s Achilles heel. SSRN Electron. J."},{"key":"ref_81","doi-asserted-by":"crossref","first-page":"36","DOI":"10.1109\/MSPEC.2017.8048837","article-title":"Blockchain world-feeding the Blockchain beast if Bitcoin ever does go mainstream, the electricity needed to sustain it will be enormous","volume":"54","author":"Fairley","year":"2017","journal-title":"IEEE Spectr."},{"key":"ref_82","unstructured":"Nakamoto, S. (2008). Bitcoin: A peer-to-peer electronic cash system. White Paper, Bitcoin Foundation."},{"key":"ref_83","doi-asserted-by":"crossref","unstructured":"Garcia, D., Tessone, C.J., Mavrodiev, P., and Perony, N. (2014). The digital traces of bubbles: Feedback cycles between socio-economic signals in the Bitcoin economy. J. R. Soc. Interface, 11.","DOI":"10.1098\/rsif.2014.0623"},{"key":"ref_84","first-page":"1","article-title":"Stock market volatility: An evaluation","volume":"3","author":"Bhowmik","year":"2013","journal-title":"Int. J. Sci. Res. Publ."},{"key":"ref_85","first-page":"555","article-title":"The present-value relation: Tests based on implied variance bounds","volume":"49","author":"LeRoy","year":"1981","journal-title":"Econom. J. Econom. Soc."},{"key":"ref_86","unstructured":"Sunstein, C.R. (1999). Free Markets and Social Justice, Oxford University Press."},{"key":"ref_87","first-page":"419","article-title":"Bitcoin money laundering: Mixed results? An explorative study on money laundering of cybercrime proceeds using Bitcoin","volume":"25","author":"Oerlemans","year":"2018","journal-title":"J. Financ. Crime"},{"key":"ref_88","doi-asserted-by":"crossref","first-page":"135","DOI":"10.18502\/keg.v3i7.3078","article-title":"Smart energy management systems for households in Bahrain","volume":"3","author":"Albuflasa","year":"2018","journal-title":"KnE Eng."},{"key":"ref_89","unstructured":"United Nations (2019, November 21). Household Size and Composition around the World. Available online: http:\/\/www.un.org\/en\/development\/desa\/population\/publications\/databooklet\/index.asp."},{"key":"ref_90","unstructured":"Sustainable Energy Unit (2019, November 21). The Kingdom of Bahrain: National Energy Efficiency (Action Plan), Available online: http:\/\/www.seu.gov.bh\/neeap\/."},{"key":"ref_91","first-page":"705","article-title":"Risk, return and portfolio theory\u2013A contextual note","volume":"5","author":"Senthilnathan","year":"2016","journal-title":"Int. J. Sci. Res."},{"key":"ref_92","unstructured":"IRENA (2020, February 21). Renewable Power Generation Costs in 2017. Available online: www.irena.org\/publications."},{"key":"ref_93","unstructured":"Barbu, A.D., Griffiths, N., and Morton, G. (2013). Achieving Energy Efficiency through Behaviour Change: What does it Take, European Environment Agency (EEA)."}],"container-title":["Sensors"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1424-8220\/20\/5\/1456\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T09:04:50Z","timestamp":1760173490000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1424-8220\/20\/5\/1456"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,3,6]]},"references-count":93,"journal-issue":{"issue":"5","published-online":{"date-parts":[[2020,3]]}},"alternative-id":["s20051456"],"URL":"https:\/\/doi.org\/10.3390\/s20051456","relation":{},"ISSN":["1424-8220"],"issn-type":[{"value":"1424-8220","type":"electronic"}],"subject":[],"published":{"date-parts":[[2020,3,6]]}}}