Exploring the techno-economic feasibility of new bioeconomy concepts: Solar-assisted thermochemical biorefineries

Applied Energy 322 (2022) 119535 Available online 29 June 2022 0306-2619/© 2022 The Author(s). Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/bync-nd/4.0/). Exploring the techno-economic feasibility of new bioeconomy concepts: Solar-assisted thermochemical biorefineries R.E. Guti´ errez a , b , K. Guerra a , P. Haro a , * a Chemical and Environmental Engineering Department. Escuela T´ ecnica Superior de Ingeniería, Universidad de Sevilla, Camino de los Descubrimientos s/n., 41092 Seville, Spain b Postgraduate Faculty, Universidad de las Am´ ericas Quito, Avenida de los Granados, E12-41 y Colimes Quito, Ecuador HIGHLIGHTS GRAPHICAL ABSTRACT •Three designs for dimethyl ether (DME) production using biomass and solar energy. •Utility supply approach is used favoring a two-way synergy between solar and biomass. •Solar power allows positive electricity balances and a fuel upgrading of up to 4%. •Solar-assisted scenarios show higher product conversion but lower overall efficiency. •DME minimum selling prices are only moderately increased compared to base scenarios. ARTICLE INFO Keywords: Biorefinery Processes Solar Fuels Dimethyl Ether Concentrated Solar Power Techno-economic Assessment ABSTRACT Integrating thermochemical biomass conversion and solar thermal energy is an emerging concept for the sustainable production of electricity, biofuels, and other renewable products. This study uses a utility supply approach to assess the techno-economic feasibility of thermochemical biorefineries (TBRF) assisted by concentrated solar power (CSP) systems. Three TBRF scenarios were modelled to produce dimethyl ether (DME) from gasified biomass (500 MW th ), considering different alternatives for syngas upgrading. A CSP plant of 50 MW e and 15 h of thermal energy storage (TES) was incorporated to increase the system power generation. The assessment of the six scenarios (3 stand-alone and 3 CSP-assisted) was based on a specific location to show its potential: the solar resource of Seville (Spain) and the electricity prices in the Iberian market, both at hourly resolution. The CSP-assisted scenarios show fuel upgrading in the range of 2–4%, up to 85% of electricity demand coverage and power surpluses of up to 52% of its annual demand. However, the inclusion of a CSP block leads to an increase in investment costs of up to 74% and a decrease in the internal rate of return (IRR) of 9.2 points compared to a stand-alone TRBF. The DME minimum selling price ranged from 14 to 18.1 USD/GJ for the stand-alone scenarios and between 18.3 and 21.2 USD/GJ for the CSP-assisted scenarios. Furthermore, these results suggest that modular integration based on commercially available technologies may constitute a first step towards the feasibility of future biorefineries. * Corresponding author. E-mail address: [email protected] (P. Haro). Contents lists available at ScienceDirect Applied Energy journal homepage: www.elsevier.com/locate/apenergy https://doi.org/10.1016/j.apenergy.2022.119535 Received 28 February 2022; Received in revised form 5 June 2022; Accepted 19 June 2022 Applied Energy 322 (2022) 119535 2 1. Introduction The path towards economic decarbonization calls for the substitution of hydrocarbons used in power generation and as precursors for transport fuels, chemicals and other industrial supplies [1]. Nowadays, biomass as a carbon source is of great interest due to its contribution to reducing greenhouse gas emissions. The conversion of biomass can occur through biochemical (e.g., enzymatic hydrolysis and fermentation) or thermochemical processes (e.g., torrefaction, pyrolysis, gasification and hydrothermal treatments) in complex structures called biorefineries [2]. Thermochemical biorefinery (TBRF) is a promising option due to the possibility to take advantage of some of the know-how and technology developed by the petrochemical industry. However, TBRFs are investment-intensive facilities, require a large scale of installation to be profitable and rely on currently not fully commercial technologies [3]. One of the most attractive TBRF is based on the syngas platform, where syngas is generated through the thermal gasification of biomass and waste. A great deal of research has been conducted to assess the techno-economic feasibility of these schemes [4]. Syngas-platform biorefineries have been proposed either for a single product (i.e., biomass- to-liquids processes (BTL)) [5] or for polygeneration using other platform chemicals as intermediates [6]. A fraction of the feedstock is usually combusted to meet some or all of the energy needs of these processes [7]. Although this may favor the system energy integration, it also limits its bioproduct generation performance by using carbonaceous resources in lower value-added applications. This limitation has increased interest in integrating other renewable sources such as geothermal, solar and wind to supply the heat and electricity needs of the biorefinery [8]. Among these, solar energy is projected to be one of the most promising options due to the abundance and availability of the resource (depending on location) and the maturity of solar power generation technologies (i.e., photovoltaic (PV) and thermal). Unlike PV systems, concentrating solar thermal energy (CSTE) can provide power as well as medium and high-temperature process heat. In addition, the availability of thermal energy storage systems (TES) and the possibility of hybridization with other thermal systems make CSTE a highly suitable and dispatchable option [9]. The continuous operation of TBRFs highlights the role of CSP as a flexible utility provider. CSTE can be integrated into TBRFs mainly following two different approaches: i) the direct supply of the heat required to drive chemical reactions in highly endothermic processes through so-called solar reactors and ii) the supply of utilities such as steam or electricity consumed in different sections of the plant. Several studies have analyzed the application of solar heat to run thermochemical reactors commonly used in TBRF concepts. For example, the solar-assisted biomass gasification in a directly irradiated packed bed reactor was addressed in [10], while an indirectly irradiated fluidized bed reactor was analyzed in [11]. Besides, the possibility of using the bed material (solid particles) as heat transfer fluid in a solar-driven dual fluidized bed reactor is assessed in [12]. Other studies have also addressed the integration of CSTE in steam reforming processes, units commonly selected for syngas upgrading in TBRFs. For example, a directly irradiated methane reforming reactor for low-carbon hydrogen production is investigated in [13] and a membrane reactor using molten salts as heat carrier is experimentally investigated at a pilot scale in [14]. Solar-assisted gasification of biomass has been thoroughly reviewed in [7], while progress on solarassisted reforming systems is discussed in [15]. In the literature, studies of solar-assisted TBRFs are commonly based on structures in which the central unit is a solar thermochemical reactor. For instance, a solar-assisted gasification-based biorefinery for methanol and electricity generation is evaluated in [16]. Similarly, a multipurpose system for H 2 , electricity and heat generation from a solar tower gasification system is assessed in [17]. These studies have considered strategies to deal with the intermittency of the solar resource, such as oversizing the solar field and storing excess syngas to be released at Nomenclature DCC direct capital costs (MUSD) FOC fixed operation costs (MUSD/y) ICC indirect capital costs (MUSD) Ƞ th total energy efficiency (% HHV) Ƞ th product product efficiency (% HHV) PEC purchase cost of equipment (MUSD) S stoichiometric ratio (-) TOC total operation costs (MUSD/y) TPI total plant investment (MUSD) VOC variable operation costs (MUSD/y) Abbreviations BTL biomass-to-liquids CEPCI chemical engineering plant cost index CSP concentrated solar power CSTE concentrating solar thermal energy DCFBG dual circulant fluidized bed gasifier DME dimethyl ether DMSP DME minimum selling price DNI direct normal irradiation GHI global horizontal irradiation GHSV gas hourly space velocity HEN heat exchanger network HHV high heating value HPS high pressure steam HRSG heat recovery steam generation HTF heat transfer fluid IRR internal rate of return LCOE levelized cost of electricity LPS low pressure steam MIBEL Iberian electricity market (Spanish acronym) MEA monoethanolamine MSP minimum selling price NPV net present value NREL National Renewable Energy Laboratory NRTL-RK non-random two liquid with the Redlich-Kwong equation of state PPA power purchase agreement PSA pressure swing absorption PV photovoltaic RESH residual heat RKS-BM Redlich–Kwong–Soave with Boston–Mathias alpha function SAM system advisor model SC(i) scenarios, i ranges from 1 to 3 SR steam reformer ST solar tower TBRF thermochemical biorefinery TES thermal energy storage TMY typical meteorological year TR tar cracker/reformer TRL technological readiness level WGS water gas shift reaction WHSV weight hourly space velocity R.E. Guti´ errez et al. Applied Energy 322 (2022) 119535 3 times of low or no solar irradiation. The gasification block is followed by conventional syngas cleaning and conditioning sections and a product synthesis loop in both studies. The results show the theoretical potential for solar reactor-based biorefineries to achieve higher energy efficiencies and reasonable economic competitiveness. However, further research is still needed on significant issues, such as reactor design, operation, and scalability, limiting the application and deployment of these technologies. The previous studies focused on a reactor-level integration of solar energy to maximize the solar share in final products (i.e., fuels) and increase the energy efficiency of the entire process [12]. However, substantial technological, operational, and economic challenges still need to be overcome before solar reactors can be considered feasible solutions. The high complexity, variety of technological options, and the early stages of technological development of such systems also need to be considered [7]. Process issues such as high operating temperature and constant syngas supply (flowrate and composition) require further development of heat-transfer materials and thermal storage or hybridization options. Designing and scaling up solar reactors to economically attractive sizes for coupling to a TBRF is an issue that is yet to be solved [18]. Consequently, these issues highlight the importance of addressing further possibilities for integration that would favor the commercial development of solar-assisted biorefineries in the near future. In contrast to the concept of solar reactor-based biorefineries, the CSTE integration approach relies on well-established technologies such as commercial concentrated solar power plants (CSP), aiming for utility supply and co-product. This approach enables decoupling between resources and represents a less technologically complex and more scalable alternative. However, only a few studies have analyzed this approach, although only for biochemical biorefineries and other renewable systems, but not in the case of a thermochemical biorefinery. For instance, the integration of PV and CSP systems in a biochemical biorefinery based on corn stover hydrolysis was analyzed in [19]. Similarly, a few conceptual alternatives for supplying electricity and heat from solar thermal and/or PV systems to an ethanol biorefinery were discussed in [8]. To the best of our knowledge, the integration of state-of-the-art CSP units into TBRFs (according to the second approach mentioned earlier) has not been addressed. This study contributes to filling this gap by assessing the techno-economic feasibility of a biomass-derived dimethyl ether (DME) biorefinery assisted by a molten salts solar tower (ST) plant. The aim is to provide insights into the performance of solar-assisted TBRFs by assessing their operation on an annualized scale with hourly resolution. This time resolution allows integrating the effect of solar intermittency and thermal storage system in the supply of utilities for both self-consumption and export. Considering two routes for DME synthesis (i.e., 1 and 2 steps) allows addressing multiple combinations between the gasification and syngas conditioning units [6]. Therefore, DME has been chosen as the reference product to evaluate the system performance through different technological options for syngas upgrading and compare them based on the same final product (which makes the comparison fairer). DME is a product of great interest due to its potential as a transport fuel, suitable for use in conventional diesel ignition engines, as well as a commodity for the petrochemical industry [3,20]. In addition, DME can be used as a platform chemical to synthesize other products in polygeneration biorefineries. A specific location has been selected to provide an in-depth assessment with a twofold objective. Firstly, to assess the combined impact of real solar resource and the electricity market prices on the biorefinery. Secondly, to address the economic implications of assuming different trading mechanisms for buying and selling electricity as a coproduct (e.g., by Power Purchase Agreements (PPAs) or by day-ahead market-imposed prices). Modular integration based on commercially available systems seems to be the first real step towards the feasibility of solar-aided biorefineries. The support of CSP systems to the biorefinery allows extending the energy integration, prioritizing the use of the highest quality heat sources for the highest value applications. This concept could lead to a lower import of utilities and a higher yield of bioproducts without affecting the TBRF plant size to the design particularities of a solar reactor. In addition, the selected approach favors a two-way synergy between solar energy and biomass. For example, the residual heat from the TBRF can be used to increase the electrical generation of the CSP system, which at the same time is used to meet the electrical demand of the entire structure. The paper is structured as follows: the concept used for integrating the CSP system in the biorefinery and the differences between the TBRF configurations are presented in section 2. In section 3, the technoeconomic design parameters included in the modelling of all biorefinery blocks and the related simulation process are described in detail. In section 4, the main findings of the study are presented and discussed. Finally, the conclusions are included in section 5. Fig. 1. Overview of selected scenarios for biomass-based DME biorefineries to be assessed in this study. R.E. Guti´ errez et al. Applied Energy 322 (2022) 119535 4 2. System description 2.1. Conceptual processes for thermochemical biorefineries This study models and assesses three concepts of syngas platform biorefineries for biomass-derived DME production. DME is the target product, which is also used to compare the performance of different routes for syngas cleaning and conditioning. Moreover, electricity generation for own consumption or sale (if surplus) is also considered in all concepts. In one of the scenarios, H 2 is included as a high-value coproduct. However, the expected yield of these co-products will be determined by the energy integration of each concept, always targeting maximum DME generation. The two main DME synthesis processes are used in the proposed schemes; the direct conversion from syngas in a single reactor (1 step) and the indirect route through the synthesis and dehydration of methanol in two reactors (2 steps) [21]. Nevertheless, depending on the chosen synthesis loop, the syngas must meet the specific requirements of their catalytic reactors. These requirements impact the selection and coupling of the different technological options for the cleaning and conditioning sections of the syngas. Fig. 1 shows the basic scheme of the process alternatives considered in this study. The process starts with biomass drying and milling operations for subsequent gasification in a dual circulating fluidized bed reactor (DCFBG). Two options were analyzed for the syngas purification section. The first uses an oil scrubber (OLGA) for tar removal, and the second uses a tar cracker/reformer (TR) reactor. These processes are Fig. 2. Concept schemes illustration for the proposed systems. (a) Stand-alone thermochemical biorefinery, (b) Thermochemical biorefinery including concentrated solar power (CSP) assistance. R.E. Guti´ errez et al. Applied Energy 322 (2022) 119535 5 intended to keep the gas stream free of impurities such as tars, NH 3 , H 2 S, among others, which can poison catalysts and downstream damage equipment. In addition, clean syngas can be directly used to generate heat and electricity or synthesize several bio-products. However, its conditioning is necessary to meet the specific requirements of each synthesis loop, such as the limit content of light hydrocarbons and CO 2 , among others (further details in section 3.1.3). Three conditioning routes that define the base scenarios were selected (without CSP support). Scenario 1 (SC1), linked to OLGA, is based on a steam reformer (SR), in which the aim is to reduce the light hydrocarbon content. Scenarios 2 (SC2) and 3 (SC3) are linked to the TR option, that in addition to tar cracking, also includes steam reforming. SC2 includes a water gas shift (WGS) unit, and SC3 a pressure swing absorption (PSA) unit. A monoethanolamine (MEA) based absorption system is used for CO 2 recovery in all scenarios. Finally, the direct DME synthesis (1 step) is applied for SC3, and the 2 steps DME synthesis loop is applied for SC1 and SC2. 2.2. Solar integration approach The concept used to integrate solar energy into the TBRF scenarios is based on a conventional CSP plant for power generation. This scheme will contribute to meeting the plant’s electricity needs and exporting the power surplus to the grid. Solar tower (ST) technology was selected due to its maturity and greater suitability for operation with large-capacity TES systems. Fig. 2b shows how the inclusion of the ST plant modifies the operation of the TBRF by redirecting the off-gases (i.e., unreacted syngas from the synthesis loop and distillate lights from the separation train) from the power block to the reforming reactor furnaces (SR or TR depending on the scenario). This modification aims to increase DME production by replacing a fraction of the fresh syngas burned to supply process heat with off-gas. However, this also implies an increase in electricity consumption and a reduction in generation capacity by removing the off-gas fueled combined cycle from the power block (included in the stand-alone scenarios). In stand-alone scenarios, the high-temperature heat required in endothermic reactors (e.g., DCFBG, SR, TR) is satisfied by burning a portion of the biomass or processing syngas. Similarly, other medium and low-temperature heat needs and process steam are covered by the energy integration of the plant through a heat exchangers network (HEN). In terms of power production, the base scenarios include a combined cycle driven by the off-gas from the synthesis loop. In addition, the amount of residual heat (RESH) available after the plant energy integration will boost the power production (as shown in Fig. 2a). Further details on RESH calculations are provided in section 3.1.4. The plants were designed under the assumption of maximum DME generation. Therefore, no net power generation is expected, and a portion of the electricity will have to be imported from the grid to supply the unmet demand. Large TES capacities imply significant increases in the operating hours of CSP plants, allowing, for example, an ST plant to reach capacity factors of up to 66% [22]. However, to reach firm supply, such large storage systems are required that are neither technical nor economically feasible [23]. Therefore, in CSP-assisted scenarios, it will still be necessary to import electricity from the grid at certain hours. On the other hand, it is assumed that electricity from RESH maintains the same mode of operation as in the stand-alone scenarios. Thus, CSP variable generation will be added to the stable generation of RESH to supply the entire structure consumption and, when possible, export the surplus. The latter would occur in the hours when the solar resource or the TES allows the CSP block to operate at a capacity greater than the TBRF demand, discounting the RESH generation. Otherwise, consumption coverage will be completed by importing electricity from the grid. Table 1 shows the design basis and summarizes the process options for the six scenarios analyzed in this study: three TBRF stand-alone scenarios and three scenarios, including CSP assistance. 3. Methodology 3.1. Detailed process modelling 3.1.1. Biomass pretreatment and gasification A 500 MW th capacity was selected as the design basis, implying a daily consumption of 2140 tonnes of dry biomass. This nominal capacity is widely used in similar studies of biomass-to-liquids (BTL) processes [24,25]. The feed biomass in all scenarios is poplar chips with a high heating value (HHV) of 20.18 MJ/kg on a dry basis. The biomass moisture is reduced from 30% to 12% in a rotary dryer using flue gas from char combustion in the gasifier as an energy source. This gas is precooled in a heat exchanger to 450 ◦C while generating low-pressure steam (LPS) (2 bar, 140 ◦C) used in the gasifier. After drying, the biomass undergoes a grinding process to reduce its particle size. The biomass conversion to syngas is carried out in a dual circulating fluidized bed gasifier (DCFBG) using steam as the gasifying agent. DCFBG was chosen because of its ability to produce syngas with low nitrogen content and because, unlike other gasifiers, it does not require an expensive air separation unit (ASU). The reactor operates at 900 ◦C and atmospheric pressure (1.5 bar), consuming 0.4 kg of steam per kg of biomass. Besides, the cold gas efficiency is assumed to be 77.07% (HHV basis). DCFBG was modelled according to experimental data from the Battelle Columbus laboratory gasifier [26]. The ultimate analysis of the feedstock biomass and the raw syngas composition is shown in Table 2. Table 1 Design basis and process concepts for the scenarios assessed in this study. SC1 SC2 SC3 SC1- CSP SC2- CSP SC3- CSP Basis of design Plant size (MW th , HHV basis) 500 500 500 500 500 500 Energy self-sufficient criterion a Maximum product yield criterion b Power neutral criterion c – – – CSP support – – – ST plant net capacity (MW e ) – – – 49.5 49.5 49.5 TES capacity (hours) – – – 15 15 15 Expected products H 2 – – – – DME Electricity for export – – – Process options Oil scrubber (OLGA) – – – – Tar cracker/steam reformer – – H 2 S removal unit Steam reformer (SR) – – – – Water-gas shift reactor (WGS) – – – – CO 2 recovery system Pressure swing absorption (PSA) – – – – Combined cycle power – – – a The only input for process heat generation is biomass. b Unreacted syngas is recirculated as much as possible in the synthesis loop. c Electricity generated in the plant is greater than its consumption on an annualized scale. Notes: SC1-3: Scenarios 1 to 3, CSP: Concentrated solar power, DCFBG: Dual circulant fluidized bed gasifier, ST: Solar tower, TES: Thermal energy storage. R.E. Guti´ errez et al. Applied Energy 322 (2022) 119535 6 3.1.2. Syngas cleaning and conditioning Although the syngas at the gasifier outlet is mainly composed of CO and H 2 , it also contains components such as tars, H 2 S, NH 3 , alkali compounds, among others that must be removed to prevent damage to the downstream process units. In this study, two options for removing tars are considered, tar washing in an oil scrubber (OLGA) or tar cracking and reforming in TR. The use of an oil scrubber is a conservative alternative since it is a reliable technology already tested in pilot and demo plants [27]. TR is an innovative alternative that, despite its moderate technological readiness level (TRL), has been included in several feasibility studies [28–30]. TR is based on a catalytic process that allows adjusting the H 2 /CO molar ratio by reforming TAR and light hydrocarbons. However, it requires burning a portion of the syngas that provides additional heat to reach an operating temperature of 930 ◦C (higher than the gasification temperature). It is assumed that the water content in the syngas is sufficient to run the reaction so that no steam addition is necessary. The pre-cooled gas passes through a water scrubber to remove NH 3 and HCl in both purification routes. The syngas is then compressed to 20 bar in a 3-stage compression set with intermediate cooling. The compressor’s isentropic efficiency is set at 78%, with a maximum compression ratio of 3.5. Sulphur removal (in the form of H 2 S) is carried out by LO-CAT® technology, enhanced by a bed filtration unit (i.e., ZnO bed) to ensure a sulphur concentration of less than 0.1 ppm [31,32]. Three process alternatives for gas conditioning are included in this study. These alternatives combine different technological options to meet the downstream requirements according to the synthesis loop of each scenario. Nonetheless, in all cases, the conditioning is based on a unit for adjusting the molar composition of the syngas accompanied by a Table 2 Biomass feedstock and syngas composition. Biomass feedstock Raw Syngas Component % wt., dry basis Component Molar (%) C 50.9 H 2 14.55 H 2 6.05 CO 23.64 O 2 41.92 CO 2 6.92 N 2 0.17 H 2 O 43.43 S 0.04 CH 4 8.43 Ash 0.92 NH 3 0.18 Moisture 30% wt. TARS 0.15 HHV 20.18 MJ/kg C 2 +2.7 – – H 2 S 184 ppm – – Ratio H 2 /CO 0.61 Fig. 3. Flow diagram for SC1 process concept. The dotted blue line includes the variation in the use of off-gas only for the case with CSP assistance (SC1-CSP). (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.) R.E. Guti´ errez et al. Applied Energy 322 (2022) 119535 7 CO 2 removal system. SR is used in SC1 to convert methane and other light hydrocarbons into syngas. The molar composition is adjusted by varying the steam addition. However, the process requires additional heat input to sustain the operating temperature (900 ◦C). This extra heat is obtained from burning a portion of the syngas, reducing process efficiency. In SC2 and SC3, the reforming has been previously carried out in the purification section through the TR unit. For SC2, a portion of the desulphurized syngas passes through a WGS reactor to adjust the stoichiometric ratio by generating additional H 2 and converting CO to CO 2 [33]. In SC3, a PSA unit is included to recover H 2 and adjust the H 2 /CO molar ratio. The recovered H 2 is compressed to 200 bar for further commercialization as a co-product [34]. CO 2 removal is carried out in all scenarios through a scrubber with a MEA solution [35]. 3.1.3. DME synthesis and product separation The two main routes for DME synthesis were considered in this study. CO and H 2 are converted into DME in a single catalytic reactor for the 1-step route [36]. While in the 2-steps route, methanol is first synthesized and subsequently dehydrated to obtain DME. For the 1-step route, the inlet syngas must maintain an H 2 /CO molar ratio in the range of 0.5–2.0 and a molar concentration of light hydrocarbons and CO 2 below 10% and 25%, respectively. For the 2-steps route, the stoichiometric ratio (S =(H 2 -CO 2 )/(CO +CO 2 )) must be equal to 2.0, the hydrocarbon content less than 10% and the CO 2 content can vary in the range of 4–8% (molar basis). In the 1-step process, the syngas is compressed up to 50 bar and heated up to 230 ◦C before entering the synthesis reactor. The DME stream leaving the reactor requires cryogenic cooling to achieve a temperature as low as −20 ◦C to facilitate gas–liquid separation in a degasser. The resulting condensate undergoes a two-step distillation process to separate the hydrocarbons and CO 2 (lights) initially and finally the remaining water. In the 2-step process, the methanol synthesis reactor operates at 80 bar and 260 ◦C. The stream leaving the reactor passes first through a gas–liquid separator and then through a methanol distillate column. Then, pure methanol is dehydrated to DME in a fixed bed reactor and subsequently sent to a DME distillation column. The unreacted syngas is further compressed and recirculated to increase DME production in both processes. Maximum recirculation is assumed if the requirements at the inlet of the synthesis loop are met, being hydrocarbon concentration the active constraint. Product separation in all scenarios has been adjusted to produce DME with a purity between 99.0% and 99.5%. Further details are given in the supporting information. 3.1.4. Energy integration and power island Once the TBRF process units are modelled, an exhaustive inventory of all heat sources and heat sinks is performed, including, among other parameters, thermal power and temperature ranges. Based on the information collected, the energy integration of the plant is carried out using the pinch method with a minimum temperature difference (ΔT min ) of 20 ◦C. Then, the grand composite curve is constructed, and the heat exchanger network (HEN) is modelled accordingly. The residual (surplus) heat (RESH) is only quantified when all the thermal needs of the plant have been satisfied. Then, the amount of RESH available at medium and high temperatures (>250 ◦C) is used to produce high-pressure steam (HPS: 100 bar, 550 ◦C), which is then expanded in a turbine for power generation. The energy efficiency of this process is assumed to be 37%. According to each scenario, the fixed electricity derived from RESH is either added to the combined cycle generation or the CSP block. In the stand-alone scenarios, the process off-gas (consisting of unreacted and non-recirculated syngas from the synthesis loop and distillate lights from the separation train) is used for electricity production through a combined cycle unit. Meanwhile, electricity generation comes mainly from the CSP system (including TES) in solar-assisted scenarios. In these cases, the combined cycle is suppressed, and the offgases are redirected from the power block to the reforming reactors (SR and TR) aiming to reduce the combustion of fresh syngas. The thermal energy supplied by the off-gas to the reforming processes varies in the range of 7.8 to 21.6 MW th depending on the scenario analyzed (this represents between 20 and 46% of the heat duty consumed in the SR or TR units, more details are provided in section 4 of the supporting information). Moreover, available RESH for power generation may vary compared to the stand-alone scenarios due to the increased syngas in the downstream process units (as described in section 4.1). Briefly, CSP- assisted scenarios have a fixed electricity generation from the RESH steam turbine plus a variable generation from the CSP block. Fig. 3 shows the process flow diagram for scenario SC1 and the variations included for SC1-CSP, while the power block alternatives are shown in Fig. 4. The process diagrams for all scenarios assessed in this study are included in the supporting information. Table A1, included in Appendix A shows the parameters and reactions used to model the main TBRF process units. 3.1.5. Solar tower block and plant location The CSP block is based on a 50 MW e (net capacity) ST plant with 15- hour of TES, following the typical size of current operational CSP plants in Spain [37]. In addition, this plant size ensures coverage of TBRFs electricity demand and allows selling surplus (if available) as a coproduct. Several technical design parameters are based on the Fig. 4. Power block related to stand-alone (a) and solar-assisted cases (b). R.E. Guti´ errez et al. Applied Energy 322 (2022) 119535 8 Gemasolar plant currently operating in the province of Seville (southwest Spain) [38]. Seville was selected as a case study because of its high direct normal irradiance (DNI) (i.e., 5.68 kWh/m 2 /day) [39] and due to its location in an area with significant biomass and organic waste resources available for the bioeconomy [40]. From our previous studies, a plant located in Seville would have different biomass sources. However, considering a realistic approach, agricultural wastes would be prioritized to avoid competition with other uses (domestic heating, firstgeneration biofuels, among others). Agricultural wastes are highly affected by transportation (low density) and represent a local resource with no current or planned use. In addition, this type of biomass is often found in moderate DNI locations, which is the aim of this study. Considering the selected location of Seville, a plant size of 500 MW th would imply consuming about twothirds of the available biomass within a radius of 100 km [40]. Therefore, the price used in this study for the reference biomass (66 USD/t) is close to those accepted for agricultural wastes in Spain (approx. 64.5 USD/t) [41]. In addition, considering the need for decentralized collection and in-situ pretreatment of agricultural wastes, their price is not distance-sensitive within the assumed range. Furthermore, a typical meteorological year (TMY) with high-precision ground-based measurements was used as the solar dataset. The data includes measures of DNI, global horizontal irradiance (GHI), ambient temperature, relative humidity and other meteorological variables with hourly resolution [39]. The DNI design point was set at 850 W/m 2 , a typical value used for CSP plants operating in Spain [42]. The solar field consists of 5522 heliostats with an area of 144 m 2 each that reflect the irradiation and concentrate it on a single focal point. Heliostats are arranged around a tower that supports a cylindrical receiver in which molten salts circulate, used as HTF and storage fluid. Molten salts are heated in the receiver from 295 ◦C (cold tank temperature) to 565 ◦C and sent to the hot tank. Then salts are conducted to the power block or stored according to the generation schedule. The power block is based on a conventional Rankine cycle operating with superheated steam at 100 bar. A gross-to-net efficiency of 90% and a cycle efficiency of 41.2% were set assuming a wet cooling system [43,44]. Parameters such as total reflection area, tower height and receiver diameter are obtained from the SolarPilot optimization algorithm of the National Renewable Energy Laboratory (NREL) [45]. In addition, the solar multiple (MS) was set based on the selected TES capacity according to a correlation developed by the authors [22]. Table 3 summarizes the main parameters used in the ST modelling. 3.1.6. Methodological steps and simulation process The TBRF process alternatives were modelled in detail (as further described in Table A1) using the Aspen Plus® process simulator (version 10). The Redlich-Kwong-Soave with Boston-Mathias alpha function (RKS-BM) thermodynamic model has been applied to the biomass gasification, gas cleaning and conditioning sections and the DME (1- step) and methanol (2-steps) synthesis. In contrast, the Non-Random Two Liquids model with the Redlich-Kwong equation of state (NTRLRK) was used for modelling the product separation trains and methanol dehydration in the 2-steps DME synthesis [6,24]. Moreover, the hourly electricity generation of the ST plant was simulated using System Advisor Model (SAM) version 2018.11.11, NREL’s proprietary software widely used in CSP-related studies [47,48]. The results of Aspen plus and SAM are linked by accounting for the hourly electricity generation of the related systems (please see section 3.1.4). The methodological steps used to assess the proposed scenarios are described as follows. The performance of the biorefinery is simulated using Aspen plus to obtain the material and energy balances of the process units. An inventory of heat sources and sinks is developed and used to perform the plant’s energy integration through the pinch method. Then, the RESH available for power generation is quantified, and the linked power cycle (case-specific) is designed accordingly. In the stand-alone scenarios, the RESH-derived steam is added to the combined cycle of the plant to complete the electricity balance. Whereas, in the solar-assisted scenarios, the RESH generates electricity decoupled from the steam turbine of the CSP block. The CSP block is simulated through SAM, obtaining the dataset corresponding to the net power output, among other results (e.g., incident and absorbed power in the solar field). Then, the hourly power derived from CSP is added to the RESH electricity to complete the power generation. Dedicated spreadsheets are used to quantify the electricity needs and surpluses of the entire system according to the generation status for each hour. These spreadsheets also include the electricity price dataset from the Iberian day-ahead market (described in section 3.2.2) to calculate the costs and revenues for purchasing and selling electricity (hourly resolution). Finally, technical evaluation parameters are calculated (as described in section 3.3), and the economic study of each scenario is conducted. 3.2. Economic design The economic analysis is based on the results of the process simulations. The feasibility assessment is carried out using the discounted cash flow analysis (DFCA) methodology. For the CSP-assisted scenarios, parameters such as total plant investment (TPI) and total operation costs (TOC) are obtained from the sum of the values associated with the systems involved (i.e., TBRF and ST blocks). Equations (1) and (2) are used to calculate TPI and TOC, respectively. TPI =DCCTBRF +DCCST +ICCTBRF +DCCST (1) TOC =FOCTBRF +FOCST +VOCTBRF +VOCST (2) 3.2.1. Total plant investment Both direct (DCC) and indirect capital costs (ICC) associated with the biorefinery are calculated from input parameters and ratios used in similar studies. The purchase cost for equipment (PEC) is calculated and scaled according to the mass and energy flows obtained in the simulations for each process unit. The effect of inflation is corrected using the Chemical Engineering Plant Cost Index (CEPCI) and the installation cost by multiplying the PEC of each unit by a specific installation factor (if unknown, it is assumed to be 2.47). Thus, DCC corresponds to the sum of the installation costs of all equipment. Meanwhile, ICC is estimated as a percentage of DCC as carried out in [6]. The reference parameters for calculating the installation costs of the main equipment are shown in Table 4. Table 3 Main parameters used in ST modelling. Parameter Value DNI design point (W/m 2 ) 850 Solar multiple (-) 2.7 a Heliostat reflective area (m 2 ) 144.4 Total reflective area (m 2 ) 797 382 TES capacity (hours) 15 Heat transfer fluid (HTF) Molten salt (60% NaNO 3 , 40% KNO 3 ) HTF cold/hot temperature (◦C) 290–565 Tower height (m) 148 b Receiver diameter (m) 13.9 b Design gross output (MW e ) 55 Net output at design (MW e ) 49.5 Gross to net conversion efficiency (-) 90% Cycle conversion efficiency (-) 41.20% Power absorbed in the solar field (MW th ) 360.4 TES thermal capacity (MW th ) 2003 Working fluid Superheated steam Boiler operating pressure (bar) 100 a Optimal value for the selected TES capacity (using the correlation developed by the authors in [22]). b Obtained from solar field optimization algorithm [46]. R.E. Guti´ errez et al. Applied Energy 322 (2022) 119535 9 The input parameters for calculating the capital costs associated with ST have been taken from widely accepted practices in CSP systems [49,50]. However, conservative values have been prioritized (i.e., not fully considering the significant cost reductions expected for this technology in the coming years) [51]. Where necessary, the 2018 exchange rate of the European Central Bank is used [52]. Land costs for the entire structure are estimated as 6% of the sum of the DCCs of both blocks. Finally, the summary of the main economic parameters of ST is shown in Table 5. Further details regarding the economic parameters are provided in the supporting information. 3.2.2. Operating costs and other economic assumptions The fixed operating costs (FOC) of the TBRF are calculated as a percentage of its CCD. The variable operating costs (VOC) are calculated as a function of the system’s consumable purchase costs. Expenses and revenues from buying and selling electricity are calculated by multiplying the amount traded by the day-ahead prices set by the Iberian electricity market (MIBEL) for each hour of the year. The 2017 electricity price dataset was obtained from [59,60] and processed and integrated into the economic analysis, as conducted in [61]. It should be noted that the system is assumed to be a price taker due to the priority dispatch in the power system since it is a renewable technology (merit order) [61,62]. The uncertainty on electricity prices variation is included assuming an annual escalation rate of 4%. Table 6 summarizes the parameters used to calculate the operating costs. The FOC related to the CSP block is calculated as a function of its installed capacity. VOC is calculated as a function of the electricity generated. For FOC, a value of 65 USD/kW-year was set, which is widely accepted and used in economic studies of ST plants [66]. Regarding VOC, 3.5 USD/MWh is common value for CSP plants [66,67]. However, this value does not consider insurance or the complexity added by TES capacity and the integration of the system in a TBRF installation [68]. Therefore, in line with the conservative approach of the study, a value of 5 USD/MWh was set [22]. Furthermore, the internal rate of return (IRR) is calculated by setting the assumed market price for DME in all scenarios and for H 2 in SC3 and SC3-CSP. The DME minimum selling price (DMSP) is calculated as the value that makes the net present value (NPV) zero for a discount rate of 10%. Finally, a capacity factor of 100% has been assumed for TBFR to match its performance with the generation from the CSP block and the hourly electricity prices. The economic assumptions and market prices of the products used for the DFCA are shown in Table 7. 3.3. Analysis of efficiency In this study, the material and energy flows of the TBRF block have been calculated on an annualized basis, assuming a capacity factor of 100%. This approach includes the effect of variable CSP operation on the electricity balance (generation and consumption). In addition, it also provides a more realistic estimate of energy efficiency and analysis of the effect of solar assistance on the performance of the different scenarios analyzed. Equations 3–5 are used to calculate the overall energy efficiency (Ƞ th total), product generation efficiency (Ƞ th product) and solar share [3]. Where CSP Products and SA Products represent the sum of the energy contained in the products of each CSP-assisted scenario and its related stand-alone scenario (e.g., SC1 and SC1-CSP). The proposed evaluation parameters enable a fair comparison of all the scenarios considering the different kinds of energy quality of the flows involved (biomass feedstock, solar isolation, utilities, and products). The energy contained in the products (i.e., DME and H 2 ) and the input biomass is calculated based on their HHV (GWh th ). Output electricity accounts for the overall amounts exported from the system to the grid. Whereas, to match the electricity imported from the grid with the energy from other system inputs (i.e., feedstock and DNI) a transformation factor from GWh th to GWh e of 0.35 has been assumed. The DNI collected annually by the solar field is calculated according to equation (6). Where SF represents the solar field, the incident power is obtained from the sum of the DNI values of the dataset and the reflection surface by multiplying the area of each heliostat by the total number of heliostats (as described in section 3.1.5). η th,total =∑ N=8760 n=1 [Productsn(GWhth)+Electricity outputn(GWhe)] [Biomassn(GWhth)+Electricity inputn(GWhe) 0.35 +Collected DNIn(GWhth)] (3) η th,product =∑ N=8760 n=1 Productsn(GWhth) Biomassn(GWhth)(4) Table 4 Input parameters for calculating the DCC of the biorefinery main equipment. Equipment Reference costs (MUSD) Reference year Base scale Unit Scaling factor a Installation factor Reference Dryer 0.39 2008 110 dry t/day 0.7 2.47 [6] Grinding 0.13 2003 2140 dry t/day 1 2.47 [6] DCFB gasifier 10.7 2010 100 MW th input (HHV) 0.72 2.47 [53] Filtering (cyclone) 2.7 2008 500 MW th input (HHV) 0.7 2.47 [6] Oil scrubber (OLGA) 2.3 2008 6131 Nm 3 /h (398 ◦C,1 atm) 0.65 1 Supplier TR (including combustor) 4.64 2002 34.22 t (input gas)/h 0.65 2.47 [54] Water scrubber 0.165 1995 23.15 m 3 (input gas)/s 0.7 1 b [6] Gas compressor 5.85 2009 5.44 MW e 0.7 1.32 [6] Air compressor 5.44 2009 5.85 MW e 0.7 1.32 Supplier LO-CAT system 15.4 2001 27.83 lb (H 2 S)/s 0.65 2.47 [6] ZnO guard bed 0.02 2002 8 m 3 (feed gas)/s 1 3 [6] SR (including combustor) 41 2002 1277 kmol (output gas)/h 0.6 1 [55] WGS unit 0.32 2002 98.45 lb/s 0.56 1 [31] PSA unit 5.46 2002 0.29 kmol (purge)/s 0.74 1.2 [28] CO 2 recovery system (MEA) 15.4 2001 45.45 t (CO 2 )/h 0.65 2.47 [6] Methanol synthesis reactor 32 2010 30.54 t (MeOH)/h 0.67 1.3 [56] Methanol dehydration reactor 2.8 2011 2386 kmol (MeOH)/h 0.65 2.47 [29] DME synthesis section 36.79 2009 2910 mol (feed gas)/s 0.65 2.1 [57] DME distillation column 0.48 1998 63,478 lb/h 1.32 2.1 [6] Gas turbine +HRSG 19.09 2003 50 MW e 0.7 1 [58] Steam turbine 23.25 2007 50 MW e 0.7 1 [58] Heat exchangers c – – – – – – – a Scaling equation: Cost/Costbase = (Scale/Scalebase)n. b The installation factor is 1 if the base cost already includes the indirect costs. c The purchase cost is calculated as described in [5]. R.E. Guti´ errez et al. Applied Energy 322 (2022) 119535 16 m 2 /day). Electricity price datasets are also site-specific, which could affect the economic performance of the system when analyzed for markets beyond the Iberian market. Nonetheless, the Iberian market is part of the integrated EU energy market, and therefore, the results of this study are applicable to the whole EU. It is noteworthy that the economics of all the assessed scenarios may improve if environmental incentives such as emission neutrality credits or even subsidies for CO 2 sequestration are incorporated. In addition, the solar-assisted scenarios could also benefit from other types of subsidies associated with electricity from CSP. Dispatchable renewable energy systems such as CSP are expected to provide stability and ancillary services to power grids; thus, exported electricity could benefit for around 30% tariff increases over the average spot market prices [82]. This study has not considered the potential benefits associated with these mechanisms, which are also under high uncertain because of the future regulatory changes. However, a discussion on these and other financial mechanisms, as well as their role in the deployment of integrated renewable concepts should be addressed in future studies. 5. Conclusions This study assesses the techno-economic feasibility of thermochemical biorefineries (TBRF) assisted by concentrated solar power systems (CSP). The integration effect on the performance of 3 process alternatives (Table 1) for DME production from gasified biomass (6 scenarios in total) is analyzed. Furthermore, a modular approach was used based on Fig. 10. Internal rate of return (IRR) as a function of various design scales for TBRF (MW th of input biomass) and CSP (MW e of power output) blocks. (a) SC1-CSP, (b) SC2-CSP, (c) SC3-CSP. The white boxes on the axes represent the size combinations for the cases simulated in this analysis. Fig. 11. DME minimum selling price (DMSP) sensitivity to the simultaneous variation of biomass feedstock cost and market electricity price. (a) SC1, (b) SC2, (c) SC3, (d) SC1-CSP, (e) SC2-CSP, (f) SC3-CSP. R.E. Guti´ errez et al. Applied Energy 322 (2022) 119535 17 commercially available solar technologies and focused on electricity generation for self-consumption and sale of surplus to the grid. The main findings are summarized below: •The stand-alone scenarios presented a negative electricity balance (i. e., they consume more than is generated), covering up to 42% of their demand with electricity imported from the grid. The CSP electricity support changes this trend, favoring positive electricity balances in all scenarios. Although a certain amount of electricity is still imported from the grid (due to the intermittency of solar energy), there is a significant annual surplus of exported electricity. •In the stand-alone scenarios, the total energy and product efficiencies range from 54% to 61% and 58% to 64%, respectively. Solar assistance moderately increases product energy efficiency (up to 4 points), with a solar share of up to 6.5%. This increase is due to the utilization of off-gases to produce process heat instead of electricity. However, it also reduces the overall efficiency of the plant (up to 11 points) due to the limited electrical efficiency of the CSP block (approx. 16%). •The inclusion of the CSP block had a significant effect on the investment of the plants but had a minor impact on the operating costs. The internal rate of return (IRR) was reduced by up to 9 points compared to that achieved by the stand-alone biorefineries. Nevertheless, all solar-assisted scenarios achieved an IRR above 10% (reference rate). •The dispatchability provided by the thermal energy storage system favors the generation of the CSP plants in the hours with the highest daily price in the electricity market. On average, the assisted biorefineries imported electricity from the grid at 0.066 USD/kWh and sold it at 0.069 USD/kWh. This trend could be intensified as the share of variable renewables in the grid increases. •The sensitivity analysis shows that the impact of uncertainties in TPI and product price amounts to a maximum variation of +18/-16 points in the base scenarios IRR. Solar assistance reduces the sensitivity to the variation of all parameters. In addition, the effect of the biomass price increase is partly offset by a higher market price for electricity sales. CSP plants are based on commercially mature technologies that can support the operation of TBRF at an economically viable installed capacity. Although direct integration of solar heat in thermochemical reactors is of great interest to the scientific community, it must first overcome challenges related to the complexity and scalability of the systems involved. The proposed integration of solar energy into thermochemical biorefineries could be a first realistic step towards future polygeneration systems with high synergy between BTL processes and concentrated solar power. The findings of this study are of special relevance for policy makers to promote the integration of CSP systems into “innovative” renewable solutions. CRediT authorship contribution statement R.E. Guti´ errez: Conceptualization, Methodology, Data curation, Formal analysis, Software, Writing – original draft. K. Guerra: Investigation, Writing – review & editing. P. Haro: Conceptualization, Methodology, Validation, Supervision, Writing – review & editing. Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. Data availability Data will be made available on request. Acknowledgements This work was supported by grant PID2020-114725RA-I00 of the project GH2T funded by MCIN/AEI/ 10.13039/501100011033 and by the “European Union”. This work was also supported by the Junta de Andalucía through the grant P18-RT-4512 (Co-funded by European Regional Development Fund/European Social Fund “A way to make Europe”). The Ph.D. grant of K. Guerra from Universidad de Sevilla (Spain) under VI PPIT-US is acknowledged. The authors acknowledge A. G´ omez-Barea for valuable comments and administrative support during the realization of this work. Appendix A See Table A1. Table A1 Main parameters and reactions used in TBRF modelling. Parameter Value General equipment Pumps Mechanical efficiency 90% Compressors Isentropic efficiency 78% Max. pressure ratio 3.5 Process turbines Isentropic efficiency 72% Gas turbine Isentropic efficiency 90% RESH power cycle Conversion efficiency 37% Heat exchangers Pressure drop 3 psi Syngas cleaning and conditioning equipment Oil scrubber (OLGA) Tar recovery 99.9% Water Scrubber Water/syngas ratio 0.001 m 3 LO-CAT® (Sep and RStoic)* Reaction 1) H 2 S +0.5O 2 → H 2 O +S H 2 S recovery 99.9% Air/H 2 S molar ratio 2.5 Steam reformer (RGibbs)* Pressure 17 bar Temperature 900 ◦C Reactions Chemical equilibrium (ΔT = 20 ◦F) Tar cracker/steam reformer (RStoic and REquil)* Pressure 1.4 bar Temperature 930 ◦C Reactions 1) CH 4 +H 2 O ↔ CO +3H 2 2) C 2 H 2 +2H 2 O → 2CO +3H 2 3) C 2 H 4 +2H 2 O → 2CO +4H 2 4) C 2 H 6 +2H 2 O → 2CO +5H 2 5) Tar +2H 2 O → 10CO + 14H 2 6) 2NH 3 ↔ N 2 +3H 2 7) CO +H 2 O ↔ CO 2 +H 2 Gas boiler (RGibbs)* Pressure 1.4 bar Flue gas temperature 150 ◦C WGS unit (REquil)* Reaction 1) CO +H 2 O ↔ H 2 +CO 2 Steam/CO molar ratio 3 MEA bed Max. CO 2 recovery 90% Steam consumption 4.5 MJ per kg of CO 2 PSA unit Max. H 2 recovery 85% Synthesis loop equipment Methanol synthesis reactor (REquil)* Temperature 260 ◦C Pressure 80 bar Reactions 1) CO +2H 2 ↔ CH 3 OH 2) CO +H 2 O ↔ H 2 +CO 2 Methanol dehydration reactor (RStoic)* Temperature 330 ◦C Pressure 21 bar Reaction 1) 2CH 3 OH ↔ CH 3 OCH 3 + H 2 O DME synthesis reactor (REquil)* Temperature 280 ◦C Pressure 50 bar Reactions 1) 3CO +3H 2 ↔ CH 3 OCH 3 + CO 2 2) CO +H 2 O ↔ H 2 +CO 2 * Blocks used for modelling in Aspen Plus. Notes: WGS: Water-gas shift, MEA: Monoethanolamine, PSA: Pressure swing adsorption. R.E. Guti´ errez et al. Applied Energy 322 (2022) 119535 18 Appendix B. Supplementary data Supplementary data to this article can be found online at https://doi. org/10.1016/j.apenergy.2022.119535. References [1] Creutzig F, Ravindranath NH, Berndes G, Bolwig S, Bright R, Cherubini F, et al. Bioenergy and climate change mitigation: an assessment. 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