Comparison of micro inverters based on practical analysis

Sadati, A.M.; Krauter, Stefan; Bendfeld, Jörg

doi:10.1109/iyce.2015.7180817

Cited by 5 publications

(3 citation statements)

References 3 publications

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“…While the results of other years do not show any significant difference. Actually, it seems that the monthly energy efficiency of micro-inverter PV system is dependent on the shading, resulting in a lower ambient temperature and slow MPPT adaption as mentioned in [13] and [40], comparing to the non-shading one. However, we did not observe this difference in our monthly yield analysis.…”

Section: B Monthly Yield Analysismentioning

confidence: 99%

“…Therefore, the shading appears in a PV module does not affect to other modules in a micro-inverter PV system. Authors in [13]- [16] investigated the conversion efficiency and energy yield of micro-inverters in non-shading condition in both laboratory environment and outdoor test field. The study in [17] simulated the operation of micro-inverter based on Matlab and Simulink modeling.…”

Section: Introductionmentioning

confidence: 99%

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Comparative Electrical Energy Yield Performance of Micro-Inverter PV Systems Using a Machine Learning Approach Based on a Mixed-Effect Model of Real Datasets

Benjapolakul

2019

IEEE Access

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Long-term energy evaluation of PV systems that use micro-inverter configuration (microinverter PV systems) is currently unclear due to the lacking of sufficient longitudinal measurement data and appropriate analysis method. The poor knowledge about impact and aging of micro-inverter PV system affects the comprehension and accuracy of PV design and simulation tools. In this paper, we propose a machine learning approach based on the mixed-effect model to compare and evaluate the electrical energy yield of micro-inverter PV systems. The analyzed results using a 5-year period data of PV stations located at Concord, Massachusetts, USA showed that there is no significant difference in yearly electrical energy yield of micro-inverter PV systems under shading and non-shading condition. This finding has confirmed the advantage of micro-inverter PV system over the other PV types. In addition, our work is the first study that identified the average degradation rate of micro-inverter PV of 3% per year (95% confidence intervals: 2% − 4.3%). Our findings in this study have extended substantially the comprehensive understanding of micro-inverter PV system.INDEX TERMS Mixed-effect model, micro-inverter PV system, micro-inverter configuration, longitudinal measurement, fixed effects, random effects.

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Section: B Monthly Yield Analysismentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Comparative Electrical Energy Yield Performance of Micro-Inverter PV Systems Using a Machine Learning Approach Based on a Mixed-Effect Model of Real Datasets

Benjapolakul

2019

IEEE Access

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“…Moreover, the use of several micro-inverters implies the duplication of protections and AC filters to offer the same quality and safety than a central inverter, which leads to a more expensive solution. Different micro-inverters efficiencies are analyzed in [25], in which a test circuit that can be used as efficiency measure to analyze and compare different features of micro inverters is designed.…”

Section: Theoretical Reviewmentioning

confidence: 99%

Analysis of the influence of DC optimizers on photovoltaic production

Hernández-Callejo

Gallardo-Saavedra

Diez-Cercadillo

et al. 2019

Rev.Fac.Ing.Univ.Antioquia

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Energy efficiency is a key element in the Smart Cities (SC), in which integration of renewable sources is a reality. Small-scale integration is usually implemented with photovoltaic (PV) and solar thermal energy. The shadows on the PV modules are a reality as they are originated by unavoidable buildings and obstacles existing in the cities. These shadows will cause the decrease in PV efficiency. Therefore, the increase in PV efficiency is essential. This increase in efficiency can be achieved by associating the DC-DC converters (DC-DC optimizers) with PV modules. This work presents and compares simulations and real results of the influence of DC-DC optimizers in the efficiency of PV modules. In addition, the work includes an economic study of the installation of DC optimizers considering three different electricity price scenarios.

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