{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,12]],"date-time":"2025-10-12T03:51:32Z","timestamp":1760241092128,"version":"build-2065373602"},"reference-count":45,"publisher":"MDPI AG","issue":"22","license":[{"start":{"date-parts":[[2019,11,16]],"date-time":"2019-11-16T00:00:00Z","timestamp":1573862400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100002878","name":"Consejer\u00eda de Econom\u00eda, Innovaci\u00f3n, Ciencia y Empleo, Junta de Andaluc\u00eda","doi-asserted-by":"publisher","award":["P08-TIC-03862"],"award-info":[{"award-number":["P08-TIC-03862"]}],"id":[{"id":"10.13039\/501100002878","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>A common problem in solar farms is to predict when accumulators stop working optimally and start losing efficiency. This paper proposes and describes how to use Bayesian networks together with expert systems to predict this moment by using a telecontrol multiagent system for monitoring solar farms with distributed sensors, which was developed in a previous work. To this end, a Bayesian network model and its implementation are proposed. The resulting system meets the requirements of telecontrol systems (reliability, flexibility, and response time), yields a solution for the prediction of lifespan batteries, and provides the multiagent system with autonomous intelligent capabilities and integrated learning.<\/jats:p>","DOI":"10.3390\/s19224998","type":"journal-article","created":{"date-parts":[[2019,11,18]],"date-time":"2019-11-18T04:31:10Z","timestamp":1574051470000},"page":"4998","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["A Distributed Approach for Estimating Battery State-Of-Charge in Solar Farms"],"prefix":"10.3390","volume":"19","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-6965-9485","authenticated-orcid":false,"given":"MCarmen","family":"Romero-Ternero","sequence":"first","affiliation":[{"name":"Departamento de Tecnolog\u00eda Electr\u00f3nica, Universidad de Sevilla, Calle San Fernando, 4, 41004 Sevilla, Spain"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"David","family":"Oviedo-Olmedo","sequence":"additional","affiliation":[{"name":"Departamento de Tecnolog\u00eda Electr\u00f3nica, Universidad de Sevilla, Calle San Fernando, 4, 41004 Sevilla, Spain"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9474-3929","authenticated-orcid":false,"given":"Alejandro","family":"Carrasco","sequence":"additional","affiliation":[{"name":"Departamento de Tecnolog\u00eda Electr\u00f3nica, Universidad de Sevilla, Calle San Fernando, 4, 41004 Sevilla, Spain"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9041-0035","authenticated-orcid":false,"given":"Joaqu\u00edn","family":"Luque","sequence":"additional","affiliation":[{"name":"Departamento de Tecnolog\u00eda Electr\u00f3nica, Universidad de Sevilla, Calle San Fernando, 4, 41004 Sevilla, Spain"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2019,11,16]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"587","DOI":"10.1016\/j.enconman.2012.05.027","article-title":"Dynamic model to follow the state of charge of a lead-acid battery connected to photovoltaic panel","volume":"64","author":"Fendri","year":"2012","journal-title":"Energy Convers. Manag."},{"key":"ref_2","doi-asserted-by":"crossref","unstructured":"Leao, J.A., Hartmann, L.V., Correa, M.B., and Lima, A.M. (2010, January 21\u201325). Lead-acid battery modeling and state of charge monitoring. Proceedings of the 2010 Twenty-Fifth Annual IEEE Applied Power Electronics Conference and Exposition (APEC), Palm Springs, CA, USA.","DOI":"10.1109\/APEC.2010.5433666"},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"1586","DOI":"10.3390\/en3091586","article-title":"Estimation of State of Charge of a Lithium-Ion Battery Pack for Electric Vehicles Using an Adaptive Luenberger Observer","volume":"3","author":"Hu","year":"2010","journal-title":"Energies"},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.simpat.2013.01.001","article-title":"Comparison between two model-based algorithms for Li-ion battery SOC estimation in electric vehicles","volume":"34","author":"Hu","year":"2013","journal-title":"Simul. Model. Pract. Theory"},{"key":"ref_5","first-page":"7306","article-title":"A comparative study of lumped equivalent circuit models of a lithium battery for state of charge prediction","volume":"43","author":"Ren","year":"2019","journal-title":"Int. J. Energy Res."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"479","DOI":"10.1016\/j.engappai.2005.12.005","article-title":"Fuzzy logic-based learning system and estimation of state-of-charge of lead-acid battery","volume":"19","author":"Malkhandi","year":"2006","journal-title":"Eng. Appl. Artif. Intell."},{"key":"ref_7","doi-asserted-by":"crossref","unstructured":"Anand, I., and Mathur, B.L. (2013, January 20\u201321). State of charge estimation of lead acid batteries using neural networks. Proceedings of the 2013 IEEE International Conference on Circuits, Power and Computing Technologies (ICCPCT), Nagercoil, India.","DOI":"10.1109\/ICCPCT.2013.6528901"},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"249","DOI":"10.1016\/j.engappai.2009.11.001","article-title":"Energy dispatch controllers for a photovoltaic system","volume":"23","author":"Venayagamoorthy","year":"2010","journal-title":"Eng. Appl. Artif. Intell."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"1484","DOI":"10.1016\/j.jpowsour.2008.06.059","article-title":"Lead acid batteries simulation including experimental validation","volume":"185","author":"Achaibou","year":"2008","journal-title":"J. Power Sources"},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"359","DOI":"10.1016\/j.jpowsour.2011.10.013","article-title":"A comparative study of equivalent circuit models for Li-ion batteries","volume":"198","author":"Hu","year":"2012","journal-title":"J. Power Sources"},{"key":"ref_11","unstructured":"Spath, V., Jossen, A., Doring, H., and Garche, J. (1997, January 23). The detection of the state of health of lead-acid batteries. Proceedings of the INTELEC 97: 19th IEEE International Telecommunications Energy Conference, Melbourne, Australia."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"3905","DOI":"10.1109\/TVT.2009.2028348","article-title":"New battery model and state-of-health determination through subspace parameter estimation and state-observer techniques","volume":"58","author":"Gould","year":"2009","journal-title":"IEEE Trans. Veh. Technol."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"3691","DOI":"10.1016\/j.apenergy.2010.04.013","article-title":"Auxiliary health diagnosis method for lead-acid battery","volume":"87","author":"Sun","year":"2010","journal-title":"Appl. Energy"},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"236","DOI":"10.1016\/j.simpat.2014.06.010","article-title":"An innovative method based on satellite image analysis to check fault in a PV system lead\u2013acid battery","volume":"47","author":"Tadj","year":"2014","journal-title":"Simul. Model. Pract. Theory"},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"953","DOI":"10.1016\/j.energy.2013.11.061","article-title":"Enhanced sample entropy-based health management of Li-ion battery for electrified vehicles","volume":"64","author":"Hu","year":"2014","journal-title":"Energy"},{"key":"ref_16","first-page":"2645","article-title":"Battery Health Prognosis for Electric Vehicles Using Sample Entropy and Sparse Bayesian Predictive Modeling","volume":"63","author":"Hu","year":"2016","journal-title":"IEEE Trans. Ind. Electron."},{"key":"ref_17","doi-asserted-by":"crossref","unstructured":"Conte, G., Scaradozzi, D., Perdon, A., Cesaretti, M., and Morganti, G. (2007, January 27\u201329). A simulation environment for the analysis of home automation systems. Proceedings of the 2007 IEEE Mediterranean Conference on Control & Automation, Athens, Greece.","DOI":"10.1109\/MED.2007.4433913"},{"key":"ref_18","doi-asserted-by":"crossref","unstructured":"Morganti, G., Perdon, A.M., Conte, G., and Scaradozzi, D. (2009, January 10\u201312). Multi-agent system theory for modelling a home automation system. Proceedings of the International Work-Conference on Artificial Neural Networks, Salamanca, Spain.","DOI":"10.1007\/978-3-642-02478-8_74"},{"key":"ref_19","doi-asserted-by":"crossref","unstructured":"Conte, G., Perdon, A.M., Scaradozzi, D., Morganti, G., and Rosettani, M. (2010, January 23\u201325). Resource management in home automation systems. Proceedings of the 2010 18th IEEE Mediterranean Conference on Control & Automation (MED), Marrakech, Morocco.","DOI":"10.1109\/MED.2010.5547602"},{"key":"ref_20","doi-asserted-by":"crossref","unstructured":"Pan, Z., Shieh, S.Y., and Li, B. (2018, January 27\u201330). Battery State-of-Charge Pulse-and-Glide Strategy Development of Hybrid Electric Vehicles for VTS Motor Vehicle Challenge. Proceedings of the 2018 IEEE Vehicle Power and Propulsion Conference (VPPC), Chicago, IL, USA.","DOI":"10.1109\/VPPC.2018.8605043"},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"2480","DOI":"10.1109\/TAC.2008.2006925","article-title":"Multi-Agent Coordination by Decentralized Estimation and Control","volume":"53","author":"Yang","year":"2008","journal-title":"IEEE Trans. Autom. Control"},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"410","DOI":"10.1109\/TAC.2008.2009583","article-title":"Consensus Based Overlapping Decentralized Estimator","volume":"54","author":"Stankovic","year":"2009","journal-title":"IEEE Trans. Autom. Control"},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"531","DOI":"10.1109\/TAC.2010.2076530","article-title":"Decentralized Parameter Estimation by Consensus Based Stochastic Approximation","volume":"56","author":"Stankovic","year":"2011","journal-title":"IEEE Trans. Autom. Control"},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"2043","DOI":"10.1109\/TAC.2010.2042982","article-title":"Consensus Conditions of Multi-Agent Systems with Time-Varying Topologies and Stochastic Communication Noises","volume":"55","author":"Li","year":"2010","journal-title":"IEEE Trans. Autom. Control"},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"477","DOI":"10.1109\/TAC.2013.2274689","article-title":"Robust Fault Estimation Using Relative Information in Linear Multi-Agent Networks","volume":"59","author":"Menon","year":"2014","journal-title":"IEEE Trans. Autom. Control"},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"1040","DOI":"10.1109\/TAC.2015.2454373","article-title":"Information Centrality and Ordering of Nodes for Accuracy in Noisy Decision-Making Networks","volume":"61","author":"Poulakakis","year":"2016","journal-title":"IEEE Trans. Autom. Control"},{"key":"ref_27","doi-asserted-by":"crossref","unstructured":"Khalid, A., Sundararajan, A., and Sarwat, A.I. (2019, January 11\u201314). A multi-step predictive model to estimate li-ion state of charge for higher c-rates. Proceedings of the 2019 IEEE International Conference on Environment and Electrical Engineering and 2019 IEEE Industrial and Commercial Power Systems Europe (EEEIC\/I&CPS Europe), Genova, Italy.","DOI":"10.1109\/EEEIC.2019.8783692"},{"key":"ref_28","doi-asserted-by":"crossref","unstructured":"Saleem, A., Nordstr\u00f6m, L., and Lind, M. (2011, January 17\u201319). Knowledge based support for real time application of multiagent control and automation in electric power systems. Proceedings of the 2011 16th International Conference on Intelligent System Applications to Power Systems, Anaheim, CA, USA.","DOI":"10.1109\/ISAP.2011.6082181"},{"key":"ref_29","doi-asserted-by":"crossref","unstructured":"Gonz\u00e1lez-Briones, A., De La Prieta, F., Mohamad, M., Omatu, S., and Corchado, J. (2018). Multi-agent systems applications in energy optimization problems: A state-of-the-art review. Energies, 11.","DOI":"10.3390\/en11081928"},{"key":"ref_30","doi-asserted-by":"crossref","unstructured":"Gonz\u00e1lez-Briones, A., Prieto, J., De La Prieta, F., Herrera-Viedma, E., and Corchado, J.M. (2018). Energy Optimization Using a Case-Based Reasoning Strategy. Sensors, 18.","DOI":"10.3390\/s18030865"},{"key":"ref_31","doi-asserted-by":"crossref","unstructured":"Sivianes, F., Romero, M., Hern\u00e1ndez, M.D., Carrasco, A., and Escudero, J.I. (July, January 30). Automatic surveillance in power system telecontrol applying embedded and multi-agent system technologies. Proceedings of the 2008 IEEE International Symposium on Industrial Electronics, Cambridge, UK.","DOI":"10.1109\/ISIE.2008.4676938"},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"534","DOI":"10.1016\/j.jpowsour.2007.08.057","article-title":"Comparison of different approaches for lifetime prediction of electrochemical systems\u2014Using lead-acid batteries as example","volume":"176","author":"Sauer","year":"2008","journal-title":"J. Power Sources"},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"66","DOI":"10.1016\/j.jpowsour.2006.11.092","article-title":"Model prediction for ranking lead-acid batteries according to expected lifetime in renewable energy systems and autonomous power-supply systems","volume":"168","author":"Schiffer","year":"2007","journal-title":"J. Power Sources"},{"key":"ref_34","unstructured":"Nielsen, T., and Jensen, F.V. (2009). Bayesian Networks and Decision Graphs, Springer."},{"key":"ref_35","unstructured":"Linden, D., and Reddy, T.B. (2001). Handbook of Batteries, McGraw-Hill. [3rd ed.]."},{"key":"ref_36","unstructured":"Mantell, C.L. (1982). Batteries and Energy Systems, McGraw-Hill Companies, Inc.. [2nd ed.]."},{"key":"ref_37","unstructured":"Telecom Italia Laboratory (2019, September 27). JADE: JAVA Agent Developement Framework. Available online: http:\/\/jade.tilab.com\/."},{"key":"ref_38","unstructured":"Oviedo, D., Romero-Ternero, M.C., Hern\u00e1ndez, M.D., Carrasco, A., Sivianes, F., and Escudero, J.I. (2010, January 8\u201312). Model of Knowledge Spreading for Multi-Agent Systems. Proceedings of the 12th International Conference on Enterprise Information Systems, Funchal, Madeira, Portugal."},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"180","DOI":"10.1109\/THMS.2014.2302993","article-title":"PeMMAS: A Tool for Studying the Performance of Multi-Agent Systems Developed in JADE","volume":"44","author":"Carrasco","year":"2014","journal-title":"IEEE Trans. Hum. Mach. Syst."},{"key":"ref_40","first-page":"124","article-title":"A Hybrid Intelligent Multiagent System for the Remote Control of Solar Farms","volume":"33","author":"Sivianes","year":"2018","journal-title":"Appl. Artif. Intell."},{"key":"ref_41","unstructured":"Druzdzel, M.J. (1999, January 18\u201322). SMILE: Structural Modeling, Inference, and Learning Engine and GeNIe: A development environment for graphical decision-theoretic models. Proceedings of the 16th National Conference on Artificial Intelligence and the Eleventh Innovative Applications of Artificial Intelligence Conference Innovative Applications of Artificial Intelligence, Orlando, FL, USA."},{"key":"ref_42","unstructured":"Bali, M. (2013). Drools JBoss Rules 5. X Developer\u2019s Guide, Packt Publishing Ltd."},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"6327","DOI":"10.1016\/j.eswa.2014.04.031","article-title":"Behavior monitoring under uncertainty using Bayesian surprise and optimal action selection","volume":"41","author":"Avila","year":"2014","journal-title":"Expert Syst. Appl."},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"70","DOI":"10.1016\/j.apenergy.2014.04.024","article-title":"An integrated framework of agent-based modelling and robust optimization for microgrid energy management","volume":"129","author":"Kuznetsova","year":"2014","journal-title":"Appl. Energy"},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"645","DOI":"10.1016\/j.jpowsour.2015.01.015","article-title":"Balancing autonomy and utilization of solar power and battery storage for demand based microgrids","volume":"279","author":"Lawdera","year":"2015","journal-title":"J. Power Sources"}],"container-title":["Sensors"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1424-8220\/19\/22\/4998\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T13:35:02Z","timestamp":1760189702000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1424-8220\/19\/22\/4998"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019,11,16]]},"references-count":45,"journal-issue":{"issue":"22","published-online":{"date-parts":[[2019,11]]}},"alternative-id":["s19224998"],"URL":"https:\/\/doi.org\/10.3390\/s19224998","relation":{},"ISSN":["1424-8220"],"issn-type":[{"type":"electronic","value":"1424-8220"}],"subject":[],"published":{"date-parts":[[2019,11,16]]}}}