Proposing an Ontology Model for Planning Photovoltaic Systems

The performance of a photovoltaic (PV) system is negatively affected when operating under shading conditions. Maximum power point tracking (MPPT) systems are used to overcome this hurdle. Designing an efficient MPPT-based controller requires knowledge about conversion in PV systems. However, it difficult for nontechnical solar energy consumers define different parameters the and deal with distinct sources data related planning. Semantic Web technologies enable us improve representation, sharing, reusing relevant information generated by various sources. In work, we propose knowledge-based model representing key concepts associated controller. featured Rule Language (SWRL), allowing planner extract reductions caused snow several airborne particles. proposed ontology, named MPPT-On, validated through case study designed System Advisor Model (SAM). It acts as decision support facilitate process planning projects non-technical practitioners. Moreover, presented rule-based can be reused shared among community adjust estimations reported tools especially snowy months polluted environments.