Characterization and optimal site matching of wind turbines: Effects on the economics of synthetic methane production Ver  onica de la Cruz, Mariano Martín * Department of Chemical Engineering, University of Salamanca, Pza. Caídos 1-5, 37008, Salamanca, Spain article info Article history: Received 15 March 2016 Received in revised form 2 June 2016 Accepted 2 June 2016 Available online 13 June 2016 Keywords: Wind energy Power curve Turbine characterization Synthetic methane CO 2 capture abstract In this work we have characterized a number of commercial onshore and offshore wind turbines developing a one-equation generic empirical model for their power curves. This model allows evaluating their efficiency and developing mathematical MINLP formulations for the selection of the turbine type and the appropriate site based on the wind profile over time. Finally, we used these formulations to evaluate the site location and the turbines needed for the production of synthetic methane from carbon dioxide and electrolytic hydrogen as a case study. Selecting the optimal turbine and site location results in competitive prices for synthetic methane, below 2V/MMBTU, and large savings in the facilities in- vestment costs. For a particular site location, the selection of the proper turbine saves up to 30% in in- vestment cost. The selection of turbine and site considering wind variability within a month results in the fact that, although the cost is expected to be higher, since a more robust solution is to be obtained, sometimes lower production prices are found. The more detailed wind distribution fits better with the power curve than just an average velocity. © 2016 Elsevier Ltd. All rights reserved. 1. Introduction Wind energy can easily provide the energy that mankind needs. However, harvesting energy from wind is challenging. First, there are only a few regions where the use of wind energy is economical. Those regions are classified as class 3 or higher, which means that the annual average wind velocity is 6.9 m/s at a height of 80 m (Archer, 2004). Second, the variability of wind velocity makes it difficult to handle as an energy source (Subtil Lacerda and van der Bergh, 2016). So far, battery systems do not have the capacity to store large amounts of energy. Therefore, alternative technologies for energy storage are being evaluated. Gençer et al. (2014) pre- sented the use of phase change in closed cycles. Hybrid systems using batteries, diesel, photovoltaic and wind are being evaluated for their operation in remote areas (Shezan et al., 2016). It is also possible to store wind energy in the form of chemicals, such as methane or ammonia (Davis and Martín, 2014a,b; Tallaksen et al., 2015). Davis and Martín (2014a) used wind and a combination of solar and wind energy (Davis and Martín, 2014b) to produce methane from renewable energy and CO 2 . This system does not only store both sources of energy in a more handy form, but it also reuses CO 2 as a carbon source for fuels. However, if wind and/or solar power are used, the variability in the energy source de- termines the usage capacity of the processing units and a trade-off between investment and the efficiency in harvesting wind energy appears which determines the plant operation. We distinguish between seasonal (monthly) availability and variability (uncer- tainty). Over a year long, records of the availability of wind energy are available, NREL (2014). However, the actual velocity is uncer- tain. Furthermore, the production cost of synthetic methane is out of the current range for natural gas price, $2-4/MMBTU, based on the results by Davis and Martín (2014b). Since the largest contri- bution to the cost corresponds the power production units, an improvement in the selection of the wind farm site location and turbine model is expected to provide an economic advantage. Therefore, when using wind energy, two issues must be handled. On the one hand, seasonal availability of resources. Wind velocity differs over time and regions. Halemane and Grossmann (1983) coined the term flexible design to come up with a mathe- matical formulation for the design of plants that can handle vari- ability in their operation in an efficient way. On the other hand, we have to consider variability in the source, typically addressed as uncertainty within the process community. It represents the probability that wind velocity reaches a certain value. The seminar * Corresponding author. E-mail address: mariano.m3@usal.es (M. Martín). Contents lists available at ScienceDirect Journal of Cleaner Production journal homepage: www.elsevier.com/locate/jclepro http://dx.doi.org/10.1016/j.jclepro.2016.06.019 0959-6526/© 2016 Elsevier Ltd. All rights reserved. Journal of Cleaner Production 133 (2016) 1302e1311