Meteorological-Data-Based Modeling for PV Performance Optimization
Sustainability
; 15(11):8659, 2023.
Article
Dans Anglais
| ProQuest Central | ID: covidwho-20232100
ABSTRACT
Developing a sustainable and reliable photovoltaic (PV) energy system requires a comprehensive analysis of solar profiles and an accurate prediction of solar energy performance at the study site. Installing the PV modules with optimal tilt and azimuth angles has a significant impact on the total irradiance delivered to the PV modules. This paper proposes a comprehensive optimization model to integrate total irradiance models with the PV temperature model to find the optimal year-round installation parameters of PV modules. A novel integration between installation parameters and the annual average solar energy is presented, to produce the maximum energy output. The results suggest an increase in energy yields of 4% compared to the conventional scheme, where tilt angle is equal to the latitude and the PV modules are facing south. This paper uses a real-time dataset for the NEOM region in Saudi Arabia to validate the superiority of the proposed model compared to the conventional scheme, but it can be implemented as a scheme wherever real-time data are available.
Environmental Studies; energy conversion; power generation meteorological factors; photovoltaic cell radiation effects; photovoltaic cell thermal factors; optimization methods; modeling; algorithms; Emissions; Irradiance; Outdoor air quality; Energy resources; Energy output; Photovoltaic cells; Efficiency; Optimization models; COVID-19; Photovoltaics; Optimization; Wind power; Solar energy; Greenhouse gases; Energy industry; Fossil fuels; Attitude (inclination); Atmospheric models; Renewable resources; Carbon dioxide; Alternative energy sources; Real time; Parameters; Saudi Arabia; China
Texte intégral:
Disponible
Collection:
Bases de données des oragnisations internationales
Base de données:
ProQuest Central
Type d'étude:
Étude pronostique
langue:
Anglais
Revue:
Sustainability
Année:
2023
Type de document:
Article
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