| Phase | 6-Grad |
| Prog. | PhD STI |
| Adm. – Grad. | 2014 – 2021 |
| Dir.; Codir. | Stéphane Gagnon; Raul Valverde |
| https://www.linkedin.com/in/farhad-k-6b444413/ |
An ontology-based decision-making framework modeling power efficiency for photovoltaic systems
Khosrojerdi, Farhad
Context: Planning an efficient photovoltaic (PV) system requires defining technical parameters that represent different knowledge areas, especially variables associated with the controller in the power conversion system. PV systems generate less energy under shading conditions or in changing climates. In a PV control system, the application of a maximum power point tracking (MPPT) method is the key factor that enables the PV arrays to operate efficiently in various ambient conditions. It is the system design requirement to define an appropriate MPPT method and the related technical parameters. As a result, dealing with characteristics of an MPPT method is a complex task when planning a PV system.
Problem: In this work, we propose a knowledge base ontology model that represents key concepts associated with designing MPPT-based controllers. The model embodies factors that affect power outputs in various ambient conditions. The proposed ontology aids to determine technical constraints and requirements of the control system and to select an appropriate MPPT method. Furthermore, the ontology model provides system design recommendations, suggestions, and power output corrections that most PV planning tools fail to report. The designed ontology, named MPPT-On, is developed using SWRL rules and queries to deal with shading conditions originated based on snowfalls.
Methodology: Evaluation of the proposed ontology is performed using a case study. We consider two scenarios for PV shading conditions expecting longer and shorter durations for snow coverings. Analysis of three types of datasets: I) output powers reported by SAM model, II) output powers corrected by MPPT-On, and III) onsite measured output powers demonstrates significant improvements by applying the proposed ontology.
Contribution: We propose an MPPT database featured with SWRL queries providing technical design data required for the MPPT-based control system of a PV project. We claim that such a MPPT database need to be added to PV planning tools to including MPPT-based control system. Furthermore, defined rules and queries for MPPT-On provide valuable technical recommendations, design considerations, and output corrections that help system designers and project managers in different phases of a PV project.
Outcome: Using the proposed ontology model helps non-technical end-user to define design-related parameters correctly and plan an efficient PV system.