Paraskeva Vasiliki, Norton Matthew, Livera Andreas, Kyprianou Andreas, Hadjipanayi Maria, Peraticos Elias, Aguirre Aranzazu, Ramesh Santhosh, Merckx Tamara, Ebner Rita, Aernouts Tom, Krishna Anurag, Georghiou George E
PV Technology Laboratory, Department of Electrical and Computer Engineering,, University of Cyprus, Nicosia 1678, Cyprus.
PV Technology Laboratory, Department of Mechanical and Manufacturing Engineering, University of Cyprus, Nicosia 1678, Cyprus.
ACS Energy Lett. 2024 Sep 26;9(10):5081-5091. doi: 10.1021/acsenergylett.4c01943. eCollection 2024 Oct 11.
Long-term stability is the primary challenge for the commercialization of perovskite photovoltaics, exacerbated by limited outdoor data and unclear correlations between indoor and outdoor tests. In this study, we report on the outdoor stability testing of perovskite mini-modules conducted over a two-year period. We conducted a detailed analysis of the changes in performance across the day, quantifying both the diurnal degradation and the overnight recovery. Additionally, we employed the XGBoost regression model to forecast the power output. Our statistical analysis of extensive aging data showed that all perovskite configurations tested exhibited diurnal degradation and recovery, maintaining a linear relationship between these phases across all environmental conditions. Our predictive model, focusing on essential environmental parameters, accurately forecasted the power output of mini-modules with a 6.76% nRMSE, indicating its potential to predict the lifetime of perovskite-based devices.
长期稳定性是钙钛矿光伏商业化面临的主要挑战，有限的户外数据以及室内和室外测试之间不明确的相关性使这一挑战更加严峻。在本研究中，我们报告了对钙钛矿微型模块进行的为期两年的户外稳定性测试。我们对一天内性能的变化进行了详细分析，量化了日间降解和夜间恢复情况。此外，我们采用XGBoost回归模型来预测功率输出。我们对大量老化数据的统计分析表明，所有测试的钙钛矿配置都表现出日间降解和恢复，在所有环境条件下这些阶段之间保持线性关系。我们的预测模型聚焦于关键环境参数，以6.76%的归一化均方根误差（nRMSE）准确预测了微型模块的功率输出，表明其具有预测钙钛矿基器件寿命的潜力。
