b7851d5c-f283-4989-b66f-182b70f1c3c520210316074459760wseamdt@crossref.orgMDT DepositWSEAS TRANSACTIONS ON COMPUTERS2224-28721109-275010.37394/23205http://wseas.org/wseas/cms.action?id=40262720202720201910.37394/23205.2020.19http://wseas.org/wseas/cms.action?id=23186Proposing a Knowledge-based Model for Photovoltaic Modules Operating under Shading ConditionsFarhadKhosrojerdiDépartement d'informatique et d'ingénierie, Université du Québec en Outaouais (UQO), CanadaStephaneGagnonDépartement d'informatique et d'ingénierie, Université du Québec en Outaouais (UQO), CanadaRaulValverdeJohn Molson School of Business, Concordia University, Montréal, CANADAIn a photovoltaic (PV) control system, the application of a maximum power point tracking (MPPT) method is the key factor that enables PV modules to operate efficiently under shading conditions. However, dealing with technical parameters of the MPPT-based controller requires expertise’s knowledge about MPPT methods. PV planning tools overlook to provide system design parameters needed for the control system. Ontologies, as knowledge-based models, provide improved representation, sharing and re-use of the relevant information that facilitate the process of decision-making. In this work, we propose a knowledge-based model representing key concepts associated with an MPPT-based control device. The ontology model is featured with Semantic Web Rule Language (SWRL) allowing the system planner to extract information about MPPT classifications and select an appropriate MPPT method. Moreover, technical recommendations and design information needed for the control system is delivered as well. 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