Journal
APPLIED ENERGY
Volume 283, Issue -, Pages -Publisher
ELSEVIER SCI LTD
DOI: 10.1016/j.apenergy.2020.116302
Keywords
Climate change adaption; Deep learning forecasting; Nationwide renewable energy deployment strategy; Power-to-X; Renewable energy penetration; Reliability assessment
Categories
Funding
- National Research Foundation of Korea (NRF) - Korean government (MSIP) [2017R1E1A1A03070713]
- Korea Research Fellowship Program through the National Research Foundation of Korea (NRF) - Ministry of Science and ICT [2019H1D3A1A02071051]
- Korea Ministry of the Environment (MOE)
- National Research Foundation of Korea [2019H1D3A1A02071051] Funding Source: Korea Institute of Science & Technology Information (KISTI), National Science & Technology Information Service (NTIS)
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The study focuses on the motivation of the South Korean government to increase renewable energy penetration and proposes a deployment strategy of a hybrid renewable energy system and Power-to-X. Results show that a 35% renewable energy penetration will lead to reduced total costs and emissions benefits, although the average electricity prices and hydrogen costs across regions are still facing competitive challenges compared to market prices.
The urge to increase renewable energy penetration into the power supply mix has been frequently highlighted in response to climate change. South Korea was analyzed as a case study for which the government has shown motivation to increase renewable energy penetration. Herein, a hybrid renewable energy system (HRES) including solar and wind energies were selected due to their relatively stable and mature technology. In addition, Power-to-X has been incorporated to cover other renewable energy options such as hydrogen and synthetic natural gas (SNG). Therefore, an approach of forecasting the weather characteristics and demand loading over a relatively long timeframe was implemented via deep learning techniques (LSTM and GRU) and statistical approaches (Fbprophet and SARIMA), respectively. A deployment strategy incorporating HRES and Power-to-X is then proposed in correspondence to the forecasted results of the 15 regions considered in this study. An extension of this, the reliability of the designed system is further assessed based on the probability of the demand losses with the aid of Monte-Carlo simulation. With the proposed deployment strategy, a total annual cost of 9.88 x 10(11) $/year and a greenhouse gas reduction of 1.24 x 10(6) tons/year are expected for a 35% renewable energy penetration. However, only SNG shows relatively competitive cost (at 23.20 $/m(3) SNG), whereas the average costs of electricity (0.133 $/kWh) and hydrogen (7.784 $/kg H-2) across the regions are yet to be competitive compared to the current market prices. Nonetheless, the priority of deployment across regions has been identified via TOPSIS.
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