{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,14]],"date-time":"2026-02-14T00:06:40Z","timestamp":1771027600579,"version":"3.50.1"},"reference-count":56,"publisher":"MDPI AG","issue":"11","license":[{"start":{"date-parts":[[2021,5,26]],"date-time":"2021-05-26T00:00:00Z","timestamp":1621987200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Electronics"],"abstract":"<jats:p>This paper presents the AiD-EM Ontology, which provides a semantic representation of the concepts required to enable the interoperability between multi-agent-based decision support systems, namely AiD-EM, and the market agents that participate in electricity market simulations. Electricity markets\u2019 constant changes, brought about by the increasing necessity for adequate integration of renewable energy sources, make them complex and dynamic environments with very particular characteristics. Several modeling tools directed at the study and decision support in the scope of the restructured wholesale electricity markets have emerged. However, a common limitation is identified: the lack of interoperability between the various systems. This gap makes it impossible to exchange information and knowledge between them, test different market models, enable players from heterogeneous systems to interact in common market environments, and take full advantage of decision support tools. To overcome this gap, this paper presents the AiD-EM Ontology, which includes the necessary concepts related to the AiD-EM multi-agent decision support system, to enable interoperability with easier cooperation and adequate communication between AiD-EM and simulated market agents wishing to take advantage of this decision support tool.<\/jats:p>","DOI":"10.3390\/electronics10111270","type":"journal-article","created":{"date-parts":[[2021,5,26]],"date-time":"2021-05-26T21:56:44Z","timestamp":1622066204000},"page":"1270","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":10,"title":["Ontologies to Enable Interoperability of Multi-Agent Electricity Markets Simulation and Decision Support"],"prefix":"10.3390","volume":"10","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-8839-8807","authenticated-orcid":false,"given":"Gabriel","family":"Santos","sequence":"first","affiliation":[{"name":"GECAD Research Group, 4249-015 Porto, Portugal"},{"name":"Institute of Engineering, Polytechnic of Porto, 4249-015 Porto, Portugal"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8248-080X","authenticated-orcid":false,"given":"Tiago","family":"Pinto","sequence":"additional","affiliation":[{"name":"GECAD Research Group, 4249-015 Porto, Portugal"},{"name":"Institute of Engineering, Polytechnic of Porto, 4249-015 Porto, Portugal"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4560-9544","authenticated-orcid":false,"given":"Zita","family":"Vale","sequence":"additional","affiliation":[{"name":"Institute of Engineering, Polytechnic of Porto, 4249-015 Porto, Portugal"}]}],"member":"1968","published-online":{"date-parts":[[2021,5,26]]},"reference":[{"key":"ref_1","unstructured":"Santos, G. (2015). Ontologies for the Interoperability of Multiagent Electricity Markets Simulation Platforms. [Master\u2019s Thesis, Instituto Superior de Engenharia do Porto]. Available online: http:\/\/hdl.handle.net\/10400.22\/8200."},{"key":"ref_2","unstructured":"Sioshansi, F. (2013). Evolution of Global Electricity Markets: New Paradigms, New Challenges, New Approaches, Elsevier Science."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"25","DOI":"10.1016\/j.tej.2005.06.008","article-title":"Development of the Internal Electricity Market in Europe","volume":"18","author":"Meeus","year":"2005","journal-title":"Electr. J."},{"key":"ref_4","doi-asserted-by":"crossref","unstructured":"Shahidehpour, M., Yamin, H., and Li, Z. (2003). Market Operations in Electric Power Systems: Forecasting, Scheduling, and Risk Management, Wiley.","DOI":"10.1002\/047122412X"},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"399","DOI":"10.3233\/ICA-140477","article-title":"Adaptive Learning in Agents Behaviour: A Framework for Electricity Markets Simulation","volume":"21","author":"Pinto","year":"2014","journal-title":"Integr. Comput. Aided Eng."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"387","DOI":"10.1016\/j.enconman.2015.04.042","article-title":"Multi-agent simulation of competitive electricity markets: Autonomous systems cooperation for European market modeling","volume":"99","author":"Santos","year":"2015","journal-title":"Energy Convers. Manag."},{"key":"ref_7","doi-asserted-by":"crossref","unstructured":"Li, H., and Tesfatsion, L. (2009). Development of Open Source Software for Power Market Research: The AMES Test Bed, Department of Economics, Iowa State University. Staff General Research Papers Archive.","DOI":"10.21314\/JEM.2009.020"},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"39","DOI":"10.1109\/MPAE.2004.1310872","article-title":"Real-world market representation with agents","volume":"2","author":"Koritarov","year":"2004","journal-title":"IEEE Power Energy Mag."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"54","DOI":"10.1109\/MIS.2003.1249170","article-title":"MASCEM: A multiagent system that simulates competitive electricity markets","volume":"18","author":"Ramos","year":"2003","journal-title":"IEEE Intell. Syst."},{"key":"ref_10","doi-asserted-by":"crossref","unstructured":"Oliveira, P., Pinto, T., Morais, H., and Vale, Z. (2012, January 22\u201326). MASGriP\u2014A Multi-Agent Smart Grid Simulation Platform. Proceedings of the 2012 IEEE Power and Energy Society General Meeting, San Diego, CA, USA.","DOI":"10.1109\/PESGM.2012.6345649"},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"56","DOI":"10.1109\/MIS.2013.2","article-title":"Distributed, Agent-Based Intelligent System for Demand Response Program Simulation in Smart Grids","volume":"29","author":"Gomes","year":"2014","journal-title":"IEEE Intell. Syst."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"1720","DOI":"10.1109\/TNNLS.2015.2461491","article-title":"Adaptive Portfolio Optimization for Multiple Electricity Markets Participation","volume":"27","author":"Pinto","year":"2016","journal-title":"IEEE Trans. Neural Netw. Learn. Syst."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"513","DOI":"10.1016\/j.energy.2016.05.127","article-title":"MASCEM: Optimizing the performance of a multi-agent system","volume":"111","author":"Santos","year":"2016","journal-title":"Energy"},{"key":"ref_14","unstructured":"Foundation for Intelligent Physical Agents (FIPA) (2021, March 16). Homepage. Available online: http:\/\/www.fipa.org\/."},{"key":"ref_15","unstructured":"(2021, March 16). Foundation for Intelligent Physical Agents (FIPA), FIPA Ontology Service Specification. Available online: http:\/\/www.fipa.org\/specs\/fipa00086\/XC00086D.html."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"2124","DOI":"10.1109\/TII.2012.2235450","article-title":"Automatically Generated Layered Ontological Models for Semantic Analysis of Component-Based Control Systems","volume":"9","author":"Dai","year":"2013","journal-title":"IEEE Trans. Ind. Informatics"},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"1753","DOI":"10.1109\/TPWRS.2007.908472","article-title":"Multi-Agent Systems for Power Engineering Applications\u2014Part II: Technologies, Standards, and Tools for Building Multi-agent Systems","volume":"22","author":"McArthur","year":"2007","journal-title":"IEEE Trans. Power Syst."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"193","DOI":"10.1109\/TSG.2011.2173508","article-title":"High Level Event Ontology for Multiarea Power System","volume":"3","author":"Pradeep","year":"2012","journal-title":"IEEE Trans. Smart Grid"},{"key":"ref_19","doi-asserted-by":"crossref","unstructured":"Do\u011fdu, E., \u00d6zbayo\u011flu, A.M., Benli, O., Ak\u0131n\u00e7, H.E., Erol, E., Atasoy, T., G\u00fcre\u00e7, O., and Er\u00e7in, O. (2014, January 2\u20136). Ontology-centric data modelling and decision support in smart grid applications a distribution service operator perspective. Proceedings of the 2014 IEEE International Conference on Intelligent Energy and Power Systems (IEPS), Kyiv, UKraine.","DOI":"10.1109\/IEPS.2014.6874179"},{"key":"ref_20","doi-asserted-by":"crossref","unstructured":"Espinoza, A., Ortega, M., Fernandez, C., Garbajosa, J., and Alvarez, A. (2011, January 26\u201329). Software-intensive systems interoperability in Smart Grids: A semantic approach. Proceedings of the 2011 9th IEEE International Conference on Industrial Informatics, Lisbon, Portugal.","DOI":"10.1109\/INDIN.2011.6034984"},{"key":"ref_21","doi-asserted-by":"crossref","unstructured":"den Hartog, F., Daniele, L., and Roes, J. (2015, January 9\u201312). Toward semantic interoperability of energy using and producing appliances in residential environments. Proceedings of the 2015 12th Annual IEEE Consumer Communications and Networking Conference (CCNC), Las Vegas, NV, USA.","DOI":"10.1109\/CCNC.2015.7157972"},{"key":"ref_22","unstructured":"(2021, April 13). SAREF Ontology. Available online: https:\/\/w3id.org\/saref."},{"key":"ref_23","unstructured":"IBM (2021, March 30). The Insights Foundation for Energy Data Model. Available online: https:\/\/www.ibm.com\/support\/knowledgecenter\/SSZMQW_1.6.0\/com.ibm.swg.ba.cognos.ife_ug.1.6.0.doc\/com_inf_mod.html."},{"key":"ref_24","unstructured":"Alexopoulos, P., Kafentzis, K., and Zoumas, C. (2009, January 7\u201310). ELMO: An interoperability ontology for the electricity market. Proceedings of the International Conference on e-Business\u2014Volume 1: ICE-B, (ICETE 2009), Milan, Italy."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"410","DOI":"10.1016\/j.ijepes.2014.03.052","article-title":"An integrated simulation model for analysing electricity and gas systems","volume":"61","author":"Erdener","year":"2014","journal-title":"Int. J. Electr. Power Energy Syst."},{"key":"ref_26","doi-asserted-by":"crossref","unstructured":"van Dam, K.H., and Keirstead, J. (2010, January 11\u201313). Re-use of an ontology for modelling urban energy systems. Proceedings of the Next Generation Infrastructure Systems for Eco-Cities, Shenzhen, China.","DOI":"10.1109\/INFRA.2010.5679232"},{"key":"ref_27","unstructured":"Catterson, V.M., Baker, P.C., Davidson, E.M., and McArthur, S.D.J. (2021, March 16). An Upper Ontology for Power Engineering Applications. Available online: http:\/\/sites.ieee.org\/pes-mas\/."},{"key":"ref_28","unstructured":"Catterson, V.M. (2006). Engineering Robustness, Flexibility, and Accuracy into a Multi-Agent System for Transformer Condition Monitoring. [Ph.D. Thesis, University of Strathclyde]."},{"key":"ref_29","unstructured":"Masolo, C., Borgo, S., Gangemi, A., Guarino, N., Oltramari, A., and WonderWeb Report (2021, May 25). Deliverable D18: Ontology Library. \u201cWonderWeb: Ontology Infrastructure for the Semantic Web\u201d Project, IST Project 2001-33052. Technical Report. Available online: http:\/\/wonderweb.man.ac.uk\/deliverables\/D18.shtml."},{"key":"ref_30","unstructured":"Smith, B. (2008). Ontology. The Blackwell Guide to the Philosophy of Computing and Information, Blackwell Publishing Ltd."},{"key":"ref_31","doi-asserted-by":"crossref","unstructured":"Omatu, S., Neves, J., Rodriguez, C.J.M., Paz Santana, F.J., and Gonzalez, R.S. (2013). Upper Ontology for Multi-Agent Energy Systems\u2019 Applications. Distributed Computing and Artificial Intelligence: 10th International Conference, DCAI 2013, Salamanca, Spain, 22\u201324 May 2013, Springer International Publishing.","DOI":"10.1007\/978-3-319-00551-5"},{"key":"ref_32","doi-asserted-by":"crossref","unstructured":"Bajo, J., Escalona, J.M., Giroux, S., Hoffa-D\u0105browska, P., Juli\u00e1n, V., Novais, P., S\u00e1nchez-Pi, N., Unland, R., and Azambuja-Silveira, R. (2016). Electricity Markets Ontology to Support MASCEM\u2019s Simulations. Highlights of Practical Applications of Scalable Multi-Agent Systems, Proceedings of the PAAMS Collection: International Workshops of PAAMS 2016, Sevilla, Spain, 1\u20133 June 2016, Springer International Publishing.","DOI":"10.1007\/978-3-319-39387-2"},{"key":"ref_33","first-page":"15","article-title":"Enabling Communications in Heterogeneous Multi-Agent Systems: Electricity Markets Ontology","volume":"5","author":"Santos","year":"2016","journal-title":"Adv. Distrib. Comput. Artif. Intell. J."},{"key":"ref_34","doi-asserted-by":"crossref","unstructured":"Santos, G., Pinto, T., Pra\u00e7a, I., and Vale, Z. (2016). An Interoperable Approach for Energy Systems Simulation: Electricity Market Participation Ontologies. Energies, 9.","DOI":"10.3390\/en9110878"},{"key":"ref_35","doi-asserted-by":"crossref","unstructured":"Santos, G., Pinto, T., Praca, I., and Vale, Z. (2017, January 17\u201320). EPEX ontology: Enhancing agent-based electricity market simulation. Proceedings of the 2017 19th International Conference on Intelligent System Application to Power Systems, ISAP 2017, San Antonio, TX, USA.","DOI":"10.1109\/ISAP.2017.8071411"},{"key":"ref_36","doi-asserted-by":"crossref","unstructured":"Santos, G., Pinto, T., Pra\u00e7a, I., and Vale, Z. (2017). Nord Pool Ontology to Enhance Electricity Markets Simulation in MASCEM, Springer. Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics).","DOI":"10.1007\/978-3-319-65340-2_24"},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"13","DOI":"10.1186\/s42162-018-0018-2","article-title":"Iberian electricity market ontology to enable smart grid market simulation","volume":"1","author":"Santos","year":"2018","journal-title":"Energy Inform."},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"1222","DOI":"10.1007\/s10618-014-0363-0","article-title":"Ontology of core data mining entities","volume":"28","author":"Panov","year":"2014","journal-title":"Data Min. Knowl. Discov."},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"103","DOI":"10.3233\/AO-160164","article-title":"Functions in Basic Formal Ontology","volume":"11","author":"Spear","year":"2016","journal-title":"Appl. Ontol."},{"key":"ref_40","doi-asserted-by":"crossref","unstructured":"Bandrowski, A., Brinkman, R., Brochhausen, M., Brush, M.H., Bug, B., Chibucos, M.C., Clancy, K., Courtot, M., Derom, D., and Dumontier, M. (2016). The Ontology for Biomedical Investigations. PLoS ONE, 11.","DOI":"10.1371\/journal.pone.0154556"},{"key":"ref_41","first-page":"68","article-title":"An information artifact ontology perspective on data collections and associated representational artifacts","volume":"Volume 180","author":"Ceusters","year":"2012","journal-title":"Studies in Health Technology and Informatics"},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"25","DOI":"10.1186\/2041-1480-5-25","article-title":"The Software Ontology (SWO): A resource for reproducibility in biomedical data analysis, curation and digital preservation","volume":"5","author":"Malone","year":"2014","journal-title":"J. Biomed. Semant."},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"900","DOI":"10.1016\/j.ins.2015.08.006","article-title":"Generic ontology of datatypes","volume":"329","author":"Panov","year":"2016","journal-title":"Inf. Sci."},{"key":"ref_44","doi-asserted-by":"crossref","unstructured":"F\u00fcrnkranz, J., H\u00fcllermeier, E., and Higuchi, T. (2013). OntoDM-KDD: Ontology for Representing the Knowledge Discovery Process. Discovery Science, Springer.","DOI":"10.1007\/978-3-642-40897-7"},{"key":"ref_45","unstructured":"Vanschoren, J., and Soldatova, L. (2010, January 20\u201324). Expos\u00e9: An ontology for data mining experiments. Proceedings of the ECML Workshop on Third Generation Data Mining: Towards Service-Oriented Knowledge Discovery (SoKD-2010), Barcelona, Spain."},{"key":"ref_46","doi-asserted-by":"crossref","first-page":"5004","DOI":"10.1016\/j.energy.2011.05.045","article-title":"A new approach for multi-agent coalition formation and management in the scope of electricity markets","volume":"36","author":"Pinto","year":"2011","journal-title":"Energy"},{"key":"ref_47","unstructured":"Java Agent DEvelopment Framework (2021, April 15). Homepage. Available online: http:\/\/jade.tilab.com."},{"key":"ref_48","doi-asserted-by":"crossref","unstructured":"Fernandes, F., Silva, M., Faria, P., Vale, Z., Ramos, C., and Morais, H. (2013, January 6\u20139). Real-time simulation of energy management in a domestic consumer. Proceedings of the IEEE PES ISGT Europe 2013, Lyngby, Denmark.","DOI":"10.1109\/ISGTEurope.2013.6695319"},{"key":"ref_49","doi-asserted-by":"crossref","first-page":"335","DOI":"10.3233\/ICA-130438","article-title":"Strategic bidding in electricity markets: An agent-based simulator with game theory for scenario analysis","volume":"20","author":"Pinto","year":"2013","journal-title":"Integr. Comput. Aided Eng."},{"key":"ref_50","unstructured":"David, A.K., and Wen, F. (2020, January 16\u201320). Strategic bidding in competitive electricity markets: A literature survey. Proceedings of the 2000 Power Engineering Society Summer Meeting (Cat. No.00CH37134), Seattle, WA, USA."},{"key":"ref_51","doi-asserted-by":"crossref","first-page":"164","DOI":"10.1016\/S0899-8256(05)80020-X","article-title":"Learning in extensive-form games: Experimental data and simple dynamic models in the intermediate term","volume":"8","author":"Roth","year":"1995","journal-title":"Games Econ. Behav."},{"key":"ref_52","doi-asserted-by":"crossref","unstructured":"Sousa, T.M., Pinto, T., Pra\u00e7a, I., Vale, Z., and Morais, H. (2014). Reinforcement Learning Based on the Bayesian Theorem for Electricity Markets Decision Support. Distributed Computing and Artificial Intelligence, 11th International Conference, DCAI 2014, Salamanca, Spain, 4\u20136 June 2014, Springer International Publishing.","DOI":"10.1007\/978-3-319-07593-8_18"},{"key":"ref_53","doi-asserted-by":"crossref","first-page":"9817","DOI":"10.3390\/en8099817","article-title":"Decision Support for Energy Contracts Negotiation with Game Theory and Adaptive Learning","volume":"8","author":"Pinto","year":"2015","journal-title":"Energies"},{"key":"ref_54","doi-asserted-by":"crossref","unstructured":"Teixeira, B., Silva, F., Pinto, T., Pra\u00e7a, I., Santos, G., and Vale, Z. (2014, January 9\u201312). Data mining approach to support the generation of Realistic Scenarios for multi-agent simulation of electricity markets. Proceedings of the 2014 IEEE Symposium on Intelligent Agents (IA), Orlando, FL, USA.","DOI":"10.1109\/IA.2014.7009452"},{"key":"ref_55","doi-asserted-by":"crossref","unstructured":"Omatu, S., Bersini, H., Corchado, J.M., Rodr\u00edguez, S., Pawlewski, P., and Bucciarelli, E. (2014). Data Extraction Tool to Analyse, Transform and Store Real Data from Electricity Markets. Distributed Computing and Artificial Intelligence, 11th International Conference, DCAI 2014, Salamanca, Spain, 4\u20136 June 2014, Springer International Publishing.","DOI":"10.1007\/978-3-319-07593-8"},{"key":"ref_56","unstructured":"OMIE (2021, April 18). Markets and Products, Electricity Market, A bout Our Market. Homepage. Available online: http:\/\/www.omie.es\/en\/home\/markets-and-products\/about-our-market."}],"container-title":["Electronics"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2079-9292\/10\/11\/1270\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T06:08:32Z","timestamp":1760162912000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2079-9292\/10\/11\/1270"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,5,26]]},"references-count":56,"journal-issue":{"issue":"11","published-online":{"date-parts":[[2021,6]]}},"alternative-id":["electronics10111270"],"URL":"https:\/\/doi.org\/10.3390\/electronics10111270","relation":{},"ISSN":["2079-9292"],"issn-type":[{"value":"2079-9292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021,5,26]]}}}