Application of the mixed effects model for analysing photovoltaic datasets and interpreting into meaningful insights

Abstract

Energy power studies commonly apply the analysis of variance (ANOVA) method in data analysis context to find the significant difference among many compared groups or to evaluate the impact of an influential factor. However, most of the datasets in these studies are time series data or longitudinal data, which are collected from the same object over some periods. Therefore, violating the independent assumption of ANOVA is the error commonly made. This leads to the misinterpretation of the comparison tests. In this article, this problem is solved by providing the application of mixed effects model (MEM) as a viable alternative to the ANOVA. In detail, two models based on MEM are proposed to analyse the time series data of micro‐inverter PV stations located in Concord city, Massachusetts, USA. In the first scenario, the average models are implemented to compare the seasonal variation of monthly yield taking into account the effects of shading conditions and different orientations. In the second scenario, the linear regression model based on MEM is implemented to estimate and compare the decline rate in a 6‐year period of PV stations. The analysis results have shown that the models based on MEM performs better than ANOVA in interpreting raw time‐series dataset into meaningful insights.

Energy Production Analysis of Rooftop PV Systems Equipped with Module-Level Power Electronics under Partial Shading Conditions Based on Mixed-Effects Model

“…The mixed-effects model (MEM) is increasingly recognized as an effective method in power engineering instead of the test-of-variation (ANOVA) method in power engineering [21,22,27,28] to compare many grouped objects whose datasets are time series and grouped [29]. In our study, we proposed two models based on an MEM: an average model to find the effect of PSC on the energy utilization ratio and a linear decline model to evaluate the effect of PSC on the annual degradation rate.…”

“…By determining the fixed-effects terms for grouped objects, any differences among groups could be determined easily. The mixed-effects model's further theories and computational methods are referenced in [28,29].…”

Annual Degradation Rate Analysis of Mono-Si Photovoltaics Systems in Thailand Using the Mixed Effects Method

“…In addition, the mixed effects model (MEM) is applied for estimating monthly decline rate and then interpreting the annual degradation rate of Mono-Si PV system based on linear mixed effects method instead of simple linear regression as in [19]. The mixed effects model, proposed by author [27] in statistical literature, has received attention in biological, clinical, and also in power engineering recently [28]- [31]. By utilizing this model, the decline rate is achieved by decomposing the trend of monthly energy yield of a particular PV system as the fixed term, which represents the generalized value for the whole observed systems, and the random terms, which represent the variations in trend of that PV system and between many PV systems to the fixed term.…”