3.8 Proceedings Paper

Opportunities of Integrating CO2 Utilization with RES-E: a Power-to-Methanol Business Model with Wind Power Generation

Publisher

ELSEVIER SCIENCE BV
DOI: 10.1016/j.egypro.2017.03.1833

Keywords

RES-E; Wind power generation; Carbon dioxide utilization (CDU); Methanol synthesis; Business model; Optimization

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Under the need to reduce CO2 emissions, renewable energy sources for electricity (RES-E) and more efficient processes are needed to decrease GHG emission rates. Carbon dioxide utilization (CDU) for the production of fuels, chemicals and materials is becoming complementary to captured CO2 and a promising source of competitive advantage for the European industry. CDU processes are at conceptual design, up to small demonstration readiness level. Since the CDU process has to compete with wellestablished conventional synthesis processes, they may not be profitable at current market conditions. Moreover, to have lower carbon footprint than the benchmark process, it has been demonstrated that they need electricity from renewable sources when CO2 is combined with H-2 as raw material [1]. This work aims at evaluating the connection of a methanol CDU plant with a wind power portfolio, to elucidate under which conditions this relationship is advantageous for both: (i) the CDU plant as a source of low-cost and zero emission energy, and (ii) the wind producer for the maximization of its profit. The business model proposed here lies in the methodology developed by [2], aiming at reducing the wind power forecasting uncertainty, between the closure of the day-ahead market and the first intraday bidding session in the Spanish power market. We have implemented an ad-hoc linear programming optimization based in GAMS that maximizes the revenue from the wind producer's perspective. The model considers the options of a wind producer of selling its RES-E to the day-ahead power market or of using its RES-E to synthesize and sell methanol. The intraday market is used as balancing market for the deviations of the wind power forecasting. (C) 2017 The Authors. Published by Elsevier Ltd.

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