(760f) Optimal Integration of Renewable Based Processes for Fuels and Power Production: Case Study in Spain

Authors: 
Martin, M., University of Salamanca
Grossmann, I. E., Carnegie Mellon University
Although renewable resources are plentiful, their sources are scattered. Therefore, to meet a certain demand of power and fuels using renewable sources, and mitigate the variability in their availability, process integration at local or greater scale has become an interesting engineering and technical challenge. Weekman (2010) and Yaun and Chen (2012) presented overviews regarding the integration possibilities as a perspective for the future combination of different sources of energy. In order to help with those decisions, process system engineering has the tools to compare sources and allocations in search for the optimal options at local and wider scales. Most of the studies either focus on fuels supply (Cucek et al 2014, Elia et al 2012) or power supply based on the unit commitment problem (Saravanan, et al 2013). However, power is most of the times produced by using a fuel, which is a chemical that can also be synthesized. Therefore, both supply networks are linked and must be addressed simultaneously. Over the last years plant size integration of renewable resources has been considered (Vidal and Martín, 2015, Martín and Davis, 2016, Martín and Grossmann, 2016). However, the integration at a larger scale, beyond the plant level, has not been attempted.

In this work we have developed a framework for the optimal integration of renewable sources of energy to produce fuels and power. A network is developed using surrogate models for various technologies that use solar energy, PV solar, CSP or algae to produce oil, wind technology, biomass based syngas to ethanol, methanol, FT-liquids and thermal energy, hydroelectric power and waste based power plant via biogas production. Hydrogen can be produced if there is a surplus of energy. It can be stored, by producing methanol or methane. Methane can be further used to produce power at need, while methanol is employed for oil transesterification to produced biodiesel. In both cases, the carbon source is CO2, that has been captured during the gasification based processes or it imported from outside the network. The corresponding processes are modeled using an input- output approach based on the results of detailed optimization studies previously developed by the authors. However, we do not model an entire process from biomass to fuels as a black box, but we break it into sections that produce intermediates that can be used for a different purpose, i.e. syngas can be used to produced ethanol FT-liquids, etc, or because various technologies are available for that; i.e. dry or wet cooling for power plants. The model is formulated as an MILP that allows determining the optimal selection of technologies to meet certain demand. Both cost and environmental objective functions are considered.

We apply the network to evaluate process integration at different scales, from region level, where we also evaluate the effect of uncertainty in renewable resources, up to the level of an entire country (Spain). Solutions under uncertainty are more robust and expensive, about 25% higher requiring the use of further technologies to meet the demand. For Spain, and using 1% of the area, it is possible to substitute 20% of fossil fuels for transportation and 100% of the power demand. The solution suggests the use of Hydropower, and oil production in all regions, while bioethanol biodiesel plants are allocated close to demand points such as large population areas. Up to 44% of fuels and total power can be substituted with the current technology development status. However, we can only reach 90% substitution by using 20% area with the availability and efficiency of current processes. The investment required for this option is more than twice that to reach 20% fossil fuels substitution.

References

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