A photovoltaics emulator for electrochemistry using Python and SCPI
Coupling photovoltaics to electrochemical devices is one of the major routes to overcome intermittent power generation and facilitate further PV deployment. However, for practical tests researchers are often at the whims of the environmental conditions at their testing sites. Experimental devices may be constrained to laboratory environments, which makes coupling to physical photovoltaics impractical. To avoid these limitations, photovoltaic devices can be emulated using highly specialized custom hardware. Adding to this development, we show emulation in software using only common functions available in many off the shelf laboratory power supplies. This approach offers maximum flexibility in choosing a photovoltaic model and operating conditions, both of which may be measured, predicted or entirely artificial. It is geared towards electrochemistry updating the output 2 times per second typically and reproducing the current–voltage characteristics of the photovoltaic device with high accuracy (0.3 % error). It also provides fast convergence for electrochemical loads and protects them from excessive ripple currents. • Photovoltaics emulators provide weather independence and output scalability. • Our software focused emulator offers high accuracy and reproducibility. • We improved convergence and reduced ripple for electrochemical devices. • We show reliability and 1 s response time in two 24 h validation runs. • The emulator consists of off the shelf hardware and free and open source software.
Authors
- Tsvetelina Merdzhanova (ORCID: https://orcid.org/0000-0003-0902-6330)
- Martin Florian Seidler (ORCID: https://orcid.org/0000-0002-8001-3746)
- Stefan Haas (ORCID: https://orcid.org/0000-0003-1579-2875)
- Bart E. Pieters (ORCID: https://orcid.org/0000-0001-6533-2098)
- Oleksandr Astakhov (ORCID: https://orcid.org/0000-0001-8499-058X)
- Walter Zwaygardt (ORCID: https://orcid.org/0000-0003-0262-053X)
Institutions
- Forschungszentrum Jülich (DE)
Publication Details
- Journal
- Journal of Power Sources
- Published
- 2025-03-20
- DOI
- https://doi.org/10.1016/j.jpowsour.2025.236723
- Citations
- 3
- Primary Topic
- CO2 Reduction Techniques and Catalysts
- Type
- article
- Field-Weighted Citation Impact
- 1.09
Funders
- Deutsche Forschungsgemeinschaft
- Horizon 2020 Framework Programme
- Horizon 2020