Microinverter Thermal Performance in the Real-World: Measurements and Modeling

Abstract

Real-world performance, durability and reliability of microinverters are critical concerns for microinverter-equipped photovoltaic systems. We conducted a data-driven study of the thermal performance of 24 new microinverters (Enphase M215) connected to 8 different brands of PV modules on dual-axis trackers at the Solar Durability and Lifetime Extension (SDLE) SunFarm at Case Western Reserve University, based on minute by minute power and thermal data from the microinverters and PV modules along with insolation and environmental data from July through October 2013. The analysis shows the strengths of the associations of microinverter temperature with ambient temperature, PV module temperature, irradiance and AC power of the PV systems. The importance of the covariates are rank ordered. A multiple regression model was developed and tested based on stable solar noon-time data, which gives both an overall function that predicts the temperature of microinverters under typical local conditions, and coefficients adjustments reecting refined prediction of the microinverter temperature connected to the 8 brands of PV modules in the study. The model allows for prediction of internal temperature for the Enphase M215 given similar climatic condition and can be expanded to predict microinverter temperature in fixed-rack and roof-top PV systems. This study is foundational in that similar models built on later stage data in the life of a device could reveal potential influencing factors in performance degradation.

An improved synchronous reference frame current control strategy for a photovoltaic grid-connected inverter under unbalanced and nonlinear load conditions

“…In the grid-connected power control mode, essentially all the available power that can be achieved from the microturbine (MT) [ 27 ], fuel cell (FC) [ 28 ] and PV is delivered to the grid [ 29 ]. Furthermore, compensation of the reactive power is possible.…”

Predictive models of poly(ethylene-terephthalate) film degradation under multi-factor accelerated weathering exposures

“…These span from least squares analysis that produces empirical relationships for dielectric, mechanical, and chemical properties [ 29 , 30 ], to multiple regression modeling of thermo-oxidative and outdoor weathering of polymers with diagnostic confirmation [ 31 ]. Hossain et al [ 32 ] developed a multiple regression predictive model for the operating temperature of PV module microinverters with rank-ordered dependencies on ambient temperature and PV module temperature which is strongly affected by the solar irradiance. The time-temperature superposition principle was applied to degradation rates of PET and EVA (ethylene-vinyl acetate) polymers under accelerated weathering exposures [ 33 ], but accurate determination of activation energies is a challenge.…”