Electricity storage with liquid fuels in a zone powered by 100% variable renewables

In this work, an electricity zone with 100% renewables is simulated to determine the optimal sizing of generation and storage capacities in such a zone. Using actual wind output data, the model evaluates the economic viability of a power-to-fuel storage technology that combines water electrolysis, CO2 capture and methanol synthesis. The main advantage of using methanol as an energy carrier is that liquid fuels are suitable for (long-term) energy storage thanks to their high energy density. The levelized electricity cost projection by 2050 equals 83.4 €/MWh in the base case configuration. The effects of storage round-trip efficiency and the storage unit lifetime are quantified and their impacts on the electricity cost discussed. Additional benefits of using methanol as a fuel substitute may be taken into account in further work.

[1]  K. Lackner,et al.  Options to dissociate CO2 and H2O for sustainable sunlight-to-fuel pathways: Comparative assessment of current R&D hurdles and future potential , 2014 .

[2]  Damien Ernst,et al.  Using approximate dynamic programming for estimating the revenues of a hydrogen-based high-capacity storage device , 2014, 2014 IEEE Symposium on Adaptive Dynamic Programming and Reinforcement Learning (ADPRL).

[3]  R. Von Burg,et al.  Methanol , 1925, Journal of applied toxicology : JAT.

[4]  Damien Ernst,et al.  Global Power Grids for Harnessing World Renewable Energy , 2014 .

[5]  C. Breyer,et al.  Global energy storage demand for a 100% renewable electricity supply , 2014 .

[6]  P. Denholm,et al.  Value of Energy Storage for Grid Applications , 2013 .

[7]  K. Lackner,et al.  Sustainable hydrocarbon fuels by recycling CO2 and H2O with renewable or nuclear energy , 2011 .

[8]  George A. Olah,et al.  Beyond Oil and Gas: The Methanol Economy , 2005 .

[9]  Claus Krog Ekman,et al.  Prospects for large scale electricity storage in Denmark , 2010 .

[10]  Damien Ernst,et al.  Chapter 14 – Global Power Grids for Harnessing World Renewable Energy , 2014 .

[11]  K. Lackner,et al.  Smart households: Dispatch strategies and economic analysis of distributed energy storage for residential peak shaving , 2015 .

[12]  Peter Meibom,et al.  Wind power impacts and electricity storage – A time scale perspective , 2012 .

[13]  Matthias A. Bucher,et al.  Integrating large shares of wind energy in macro-economical cost-effective way , 2012 .

[14]  S. Jensen,et al.  Technology data for high temperature solid oxide electrolyser cells, alkali and PEM electrolysers , 2013 .

[15]  Jaeger-Waldau Arnulf,et al.  ETRI 2014 - Energy Technology Reference Indicator projections for 2010-2050 , 2014 .

[16]  Mark O'Malley,et al.  The viability of balancing wind generation with large scale energy storage , 2010 .

[17]  K. Lackner,et al.  Agent-based model for electricity consumption and storage to evaluate economic viability of tariff arbitrage for residential sector demand response , 2014 .