Net-metering compared to battery-based electricity storage in a single-case PV application study considering the Lithuanian context
| Author | Affiliation | |
|---|---|---|
Aleksiejuk-Gawron, Joanna | Warsaw University of Life Sciences, Poland | PL |
LT | ||
LT | ||
Doheijo, Enrique | Deloitte, Madrid, Spain | ES |
Garzon, Diego | Deloitte, Madrid, Spain | ES |
Lietuvos energetikos institutas, | LT | |
Lietuvos energetikos institutas | LT |
| Date |
|---|
2020 |
Further increases in the number of photovoltaic installations in industry and residential buildings will require technologically and economically flexible energy storage solutions. Some countries utilize net-metering strategies, which use national networks as “virtual batteries.” Despite the financial attractiveness, net-metering faces many technological and economical challenges. It could also lead to the negative tendencies in prosumer behavior, such as a decrease in motivation for the self-consumption of photovoltaic (PV)-generated electricity. Batteries, which are installed on the prosumer’s premises, could be a solution in a particular case. However, the price for battery-based storage solutions is currently sufficiently unattractive for the average prosumer. This paper aimed to present a comparison of the economic and energy related aspects between net-metering and batteries for a single case study by considering the Lithuanian context. The net present value, degree of self-sufficiency, internal rate of return, payback time, and quantified reduction of carbon emission were calculated using a specially developed Prosumer solution simulation tool (Version 1.1, Delloite, Madrid, Spain) for both the PV and net-metering and PV and batteries cases. The received results highlight that the battery-based energy storage systems are currently not an attractive alternative in terms of price where net-metering is available; a rather radical decrease in the installation price for batteries is required.
art. no. 2286
| Journal | IF | AIF | AIF (min) | AIF (max) | Cat | AV | Year | Quartile |
|---|---|---|---|---|---|---|---|---|
Energies | 3.004 | 7.341 | 7.341 | 7.341 | 1 | 0.409 | 2020 | Q3 |
| Journal | IF | AIF | AIF (min) | AIF (max) | Cat | AV | Year | Quartile |
|---|---|---|---|---|---|---|---|---|
Energies | 3.004 | 7.341 | 7.341 | 7.341 | 1 | 0.409 | 2020 | Q3 |
| Journal | Cite Score | SNIP | SJR | Year | Quartile |
|---|---|---|---|---|---|
Energies | 4.7 | 1.161 | 0.598 | 2020 | Q1 |