Kazuya Tada

Equivalent circuit models that reproduce the current–voltage characteristics of solar cells are useful not only to gain physical insight into the power loss mechanisms that take place in solar cells but also for designing systems that use renewable solar energy as a power source. As mentioned in a previous paper, Bayesian estimation of equivalent circuit parameters avoids the drawbacks of nonlinear least-squares methods, such as the possibility of evaluating estimation errors. However, it requires a long computation time because the estimated values are obtained by sampling using a Markov chain Monte Carlo method. In this paper, a trial to accelerate the calculation by upgrading the Bayesian statistical package PyMC is presented. PyMC ver. 4, the next version of PyMC3 used in the previous paper, started to support the latest sampling libraries using a machine learning framework JAX, in addition to PyMC-specific methods. The acceleration effect of JAX is remarkable, achieving a calculation time of less than 1/20 times that of the case without JAX. Recommended calculation conditions were disclosed based on the results of a number of trials, and a demonstration with testable Python code on Google Colaboratory using the recommended conditions is published on GitHub.

The dye-sensitized solar cell (DSSC) has been on the market as a permanent power source for indoor IoT edge devices. In recent years, indoor illumination technology has been experiencing a drastic transition from incandescent and fluorescent lamps toward solid-state lighting devices with light-emitting diodes (LEDs). In addition to the high power efficiency, a virtue of LEDs is their prompt response, which enables precise change of the illumination level using pulse-width modulation (PWM) of the current source, and thus PWM illumination is commonly installed in society. The light intensity change from off to on states of an LED under PWM driving is literally infinity, which causes the lighting to flicker. The lighting flicker induces not only an optical illusion but also biological effects, including serious health problems, which can be mitigated by raising the modulation frequency. Because the peak intensity of a PWM illumination can be 100 times that of the average intensity, the indoor solar cell, which has a relatively high series resistance, is expected to underperform. In this paper, the characteristics of a commercial indoor DSSC under PWM illumination are studied. It is found that while PWM illumination at low frequency seriously deteriorates the performance of the DSSC, it recovers at high frequency. The latter feature is not found in indoor amorphous-Si solar cells, and the electrochemical impedance spectroscopy revealed that it stems from the electrochemical nature of some components of the series impedance in the DSSC, offering a key piece of evidence of the superiority for use in the modern indoor application of the DSSC over traditional amorphous-Si solar cells.