Abstract
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 power conversion in PV systems. However, it is difficult for nontechnical solar energy consumers to define different parameters of the controller and deal with distinct sources of data related to the planning. Semantic Web technologies enable us to improve knowledge representation, sharing, and reusing of relevant information generated by various sources. In this work, we propose a knowledge-based model representing key concepts associated with an MPPT-based controller. The model is featured with Semantic Web Rule Language (SWRL), allowing the system planner to extract information about power reductions caused by snow and several airborne particles. The proposed ontology, named MPPT-On, is validated through a case study designed by the System Advisor Model (SAM). It acts as a decision support system and facilitate the process of planning PV projects for non-technical practitioners. Moreover, the presented rule-based system can be reused and shared among the solar energy community to adjust the power estimations reported by PV planning tools especially for snowy months and polluted environments.
Highlights
Since 25 years ago, solar energy has become one of the main contributors among other forms of renewable energy resources [1]
We demonstrated the application of Semantic Web technologies in solar
The model consists of essential parameters and factors which are required for designing Maximum power point tracking (MPPT) controllers
Summary
Since 25 years ago, solar energy has become one of the main contributors among other forms of renewable energy resources [1]. Using current-voltage (I-V) tracing approaches, performances of a PV module or even solar panels of a utility-size PV system, a power plant can be measured by system operators [2]. These online diagnosis and cost-efficient techniques provide accurate data needed for effectively operating a PV system power plant [3]. The convenience of installing a PV system has motivated residential and commercial users to consider it as an important source of energy for their needs It means that consumers with minimum or basic knowledge about a solar panel must deal with the process of the PV system planning.
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