Forecast modeling and performance assessment of solar PV systems

• Published in: Journal of cleaner production 2020-09, Vol.267, p.122167, Article 122167
• Main Authors: Ameur, Arechkik, Berrada, Asmae, Loudiyi, Khalid, Aggour, Mohamed
• Format: Article
• Language: English
• Subjects: Comparison; LCOE; Prediction; Solar radiation
• ISSN: 0959-6526; 1879-1786
• DOI: 10.1016/j.jclepro.2020.122167

Electricity is converted directly from incident solar energy through photovoltaic systems. This latter is considered an elegant mean of exploiting renewable energy. It contributes significantly to the energy transition by reducing fossil fuel usage. Several studies about photovoltaic (PV) technology have focused on the design of photovoltaic systems or the theory behind them. On the contrary, this paper presents an evaluation of PV systems performance; it investigates the impact of diverse factors on the performance of these PV technologies. The aim of this work is to assess and compare the performance of different PV types including monocrystalline, polycrystalline, and amorphous silicon (Si) systems. Various indices are utilized in this evaluation such as system efficiency, performance ratio, energy output, and capacity factor. The performance analysis was evaluated using real measured data for a period of 5 years. It has shown that polycrystalline-Si technologies have higher performance compared to both monocrystalline-Si and amorphous-Si. This latter has lower conversion efficiency and capacity factor as compared to its counterparts. The performed economic analysis indicates that the most cost-effective system in the investigated Case study is polycrystalline -Si as it has the lowest levelized cost of energy (LCOE) of 0.10 USD/kWh. In addition, a dynamic simulator based on physical resources has been developed using Python to predict the power production of PV systems over one week. The forecast model is based on cloud cover predictions obtained from Dark Sky API. The simulation results are compared to the measured ones. The obtained results demonstrate that the proposed prediction model has high accuracy. The root mean square errors of polycrystalline-Si, monocrystalline-Si, and amorphous-Si are 17.9%, 17%, and 20.4%, respectively. In addition, the mean absolute percentage errors of the aforementioned systems are 5.05%, 4.57%, and 4.35%, respectively. Finally, a detailed analysis comparing the performance of PV systems installed in various regions of Morocco is presented in this paper. The compared systems have the same brand and power capacity. •Performance assessment of different PV types under similar weather conditions was performed.•Dynamic model is proposed to forecast the PV power output over one-week period.•Validation of the model by a Case study.•Accuracy of the proposed prediction model is quantified and compared to other models.•Results sh