The effect of switching renewable energy support systems on grid parity for photovoltaics: Analysis using a learning curve model
Soonpa Hong,
Taeyong Yang,
Hyun Joon Chang and
Sungjun Hong
Energy Policy, 2020, vol. 138, issue C
Abstract:
Renewable energy electricity, such as photovoltaic (PV) power generation, has the benefits of strengthening energy security, addressing climate change, reducing air pollution, etc., but there are some impediments to deployment of renewable energy electricity: higher costs than fossil fuels, intermittent energy production, site constraints, etc. Korea changed its renewable energy electricity support systems from feed-in tariff (FIT) to a renewable portfolio standard (RPS) in 2012. This study evaluates FIT versus RPS in terms of the time to reach grid parity for PVs. Using a learning curve model, we calculate the learning rate of PV power generation during the FIT and RPS periods. We find that the PV learning rate during the RPS period was 18.44%, much higher than that during the FIT period, −0.28%, and R2 is 0.9861 and 0.7346 in the RPS and FIT periods, respectively. Using the calculated learning rate in the RPS period, we also predict that grid parity for PVs is expected in 2025 in Korea.
Keywords: Renewable energy; Feed in tariff; Renewable portfolio standard; Grid parity; Photovoltaics; Learning curve (search for similar items in EconPapers)
Date: 2020
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Citations: View citations in EconPapers (12)
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Persistent link: https://EconPapers.repec.org/RePEc:eee:enepol:v:138:y:2020:i:c:s0301421519308146
DOI: 10.1016/j.enpol.2019.111233
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