GB2496115A - Method and plant for producing hydrocarbon compounds - Google Patents

Abstract

A plant for producing hydrocarbon compounds has a renewable energy generator (e.g. using solar power), an algal biomass cultivator, an algal biomass harvester, an algal biomass dryer and a means for generating hydrocarbon compounds from the algal biomass. The algal biomass cultivator, the algal biomass harvester, the algal biomass dryer and/or the means for generating hydrocarbon compounds are arranged to utilise power generated by the renewable energy generator.

Description

CHEMICAL PROCESSING SYSTEM

This invention is directed to a chemical processing system. In particular, it relates to a method fol chemical processing and a chemical process plant for producing fuels and raw materials for the chemical industry, using algae biomass, and for producing electricity.

BACKGROUND OF THE INVENTION

Conventional energy sources like oil and coal have been successfully providing energy to our earth over the last century. However, worries over the depletion of these non-renewable energy sources, global warming and increasing energy demand in both developed and developing countries have spearheaded the search for an alternative carbon neutral and negative renewable and sustainable source of energy.

The constant search for alternative renewable energy sources to replace unsustainable conventional energy sources like oil and coal have led to the discovery of solutions like first generation biofuels. However, these crop derived first generation biofuels have major drawbacks like increasing food prices, biodiversity problems and enormous land area requirements.

Algae-derived biodiesel is a renewable and sustainable alternative to growing fuel on land. The main advantage algae have over other crops is its greater efficiency in using sunlight and consuming CO2 for photosynthesis, which results in much greater productivity per km2.

However, despite possessing the technology to produce algae-derived fuels, there remain challenges as to how such fuels may be produced in the necessary volumes with a neutral or even negative carbon footprint.

SUMMARY OF INVENTION

The invention relates to a method and a plant as defined in the independent claims to which reference should now be made. Advantageous or preferred features are set forth in the dependent claims.

Problems addressed by the proposed system include the high carbon footprint associated with the production of liquid hydrocarbon fuels, the high carbon footprint associated with production of raw materials for the chemical industry and the low efficiency of first and second generation of biofuels.

The invention may thus provide a method comprising: a) generating power/electricity by a renewable energy generator; b) cultivating, harvesting and drying algal biomass; and c) generating hydrocarbon compounds from the algal biomass, in which steps b) and/or c) utilise the power generated by the renewable energy generator.

Preferably, the method is for generating biofuels. Most preferably, the method is for generating biodiesel, kerosene or naptha. However, the method may be used to produce raw materials and commodity chemicals for the chemical industry, such as waxes and other straight chain alkanes..

In a preferred example, the renewable energy generatol is a solar power system.

However, wind energy, for example, could be exploited, using, a wind farm as a renewable energy generator. Examples of suitable solar power systems are photovoltaic (PV) systems and concentrating solar power (CSP) systems. Most preferably, a CSP system is employed. It is also conceivable that electricity from a conventional electricity grid could provide a source of power.

Step c) of the method may comprise subjecting the algal biomass to gasification and Fischer-Tropsch (FT) synthesis. Biomass may thus be gasified to produce syngas, which acts as a feed for the FT process. The FT process may then be used to produce syncrude. Step c) may also comprise subjecting a product of gasification to gas conditioning and acid gas removal. Step c) preferably comprises subjecting a product of FT synthesis to hydrocracking. Thus syncrude may undergo hydrocracking, and possibly also a refining step, to produce hydrocarbon liquid fuels such as, for example, biodiesel and naptha.

Alternatively, step c) of the method may comprise extracting algal oil from the algal biomass and subjecting the algal oil to transesterification, which is the reaction between algal oil and alcohol to produce biodiesel.

Preferably, drying of the algal biomass is achieved using a solar dryer.

The method may also comprise supplying electricity produced in step a)to an electricity grid. Optionally, the method may comprise producing desalinated water using the power generated by the renewable energy source. For example, desalinated water may be produced by multi-effect desalination or reverse osmosis.

The invention may thus provide a plant comprising a renewable energy/electricity source; an algal biomass cultivator; an algal biomass harvester; an algal biomass dryer and a means for generating hydrocarbon compounds from the algal biomass, in which the algal biomass cultivator, the algal biomass harvester, the algal biomass dryer and/or the means for generating hydrocarbon compounds are arranged to utilise power generated by the renewable energy source.

Preferabty, the renewable energy source is a solar power system, such as a csP.

In a preferred example, the algal biomass cultivator is an algae photobioreactor (P BR).

The means for generating hydrocarbon compounds may comprise a gasifier for gasifying the algal biomass and a FT reactor for generating hydrocarbon products from the gasified cultivated algae.

The algae dryer is preferably a solar dryer.

The plant may also be arranged to supply electricity to an electricity grid. The renewable energy source may also be used to produce desalinated water preferably by multi-effect desalination or reverse osmosis.

Other implementations, may include carrying out part of the process as a pre-combustion carbon capture process; in which hydrogen produced from biomass gasification is used in a fuel cell or gas turbine application to produce electricity.

The invention may be of particular benefit to places with an arid climate, such as places possessing desert landscapes. Suitable places may include, for example, the United States, Saudi Arabia, Spain and North Africa. As a specific non-limiting example, Saudi Arabia is the largest oil producer and exporter of petroleum liquids in the world. However, it is also the largest consumer of petroleum for transportation fuels and power generation in the Middle East. Furthermore, the increasing demand for water in Saudi Arabia creates the need for a sustainable water source to meet this demand. Fortunately, Saudi Arabia possesses an abundance of natural resources like sunlight, seawater and desert land to be utilised.

SPECIFIC DESCRIPTION OF THE PREFERRED EMBODIMENTS

Embodiments of the invention will now be described, by way of example, with reference to the accompanying drawings in which: Figure 1 is an overview of a plant according to an embodiment of the invention.

Figure 2 displays the steps involved in an algae production process according to an embodiment of the invention.

Figure 3 displays the steps involved in a fuel production process according to an embodiment of the invention.

Figure 4 displays the product distribution with different chain growth probability in FT synthesis, according to Tijmensen eta! (2002).

Figure 5 is a set of graphs showing plant outputs according to a model.

Figure 6 is a graph showing production scale comparisons according to a model.

Figure 7 is a chart showing a carbon process boundary according to a model.

Figure 8 is a pie-chart showing biofuel revenue contributors according to a model.

Figure 9 is a set of graphs showing NPV comparisons according to a model.

Figure 10 is a graph showing diesel pump price comparisons according to a model.

Figure 11 is an example of a setup used in a UNISIM process simulation.

Figure 12 is a table showing flow, pressure and temperature at various points in the setup of Figure 11.

Example 1 -a C-FAST plant (Carbon negative fuels derived from Algal and Solar Technologies) The plant, as exemplified in Figure 1, consists of three main technology components: 1. A Concentrated solar power (CSP) plant which works on the principle of focussing direct sunlight onto a receiver, heating up a contained heat fluid transfer intern, which is then used to generate superheated steam to power a steam turbine that drives a generator, eventually producing electricity to provide energy for the plant and to be fed into the electricity grid. In addition, it also produces desalinated water via multi-effect desalination or reverse osmosis.

2. An algae photobioreactor (PBS) is a network of transparent tubular plastic reactors that cultivates algae biomass, which is then harvested and dried to produce dry biomass.

3. A fuel production component, in which the biomass is then gasified to produce syngas, which acts as a feed for a Fischer-Tropsch (FT) reactor, to produce syncrude. This syncrude eventually undergoes hydrocracking and refining processes to produce hydrocarbon fuels such as biodiesel and naptha.

Examcjle 2 -Solar Thermal Enerav According to Glennon and Reeves (2010), the two basic solar power systems commercially available nowadays are photovoltaic (PV) cells and concentrating solar power (CSP).

2.1 -Photovoltaic Systems The main idea behind photovoltaic systems according to Abengoa Solar (2011) is the conversion of solar radiation into electrical current by utilising semiconductors. The electrons in the cell become excited and leave the electric field when solar radiation is absorbed. These excited electrons will seek to return to their initial electric field via an external circuit, hence producing electricity via the photovoltaic effect. According to I EA (201 Oa), PV cells are interconnected to form PV modules, which are eventually combined to form PV systems capable of providing power ranging up to tens of megawatts (MW).

Commercial PV modules are generally divided into wafer-based crystalline-Si or thin films that account for 85-90% and 10-15% of the global annual market respectively. Typical incident solar energy conversion efficiencies of crystalline-Si and thin films are about 14-20% and 8-12% respectively.

From Glennon and Reeves (2010), the main advantages associated with PV cells are that minimal water is required for operation, which can be vital for operations in the desert. In addition, they can be built in modular stages and need not be built to utility scales, which can avoid the requirement of large capital investments. However, PV cells do not have the capability to store any excess energy produced, which poses significant power intermittency problems during absence of sunlight or inconsistent weather conditions.

2.2 -Concentrating Solar Power (CSP) According to lEA (2010b), CSP systems generally work on the principle of focusing direct sunlight onto a receiver, heating up the contained heat transfer fluid intern, which is then used to generate superheated steam to power a steam turbine that drives a generator, eventually producing electricity. The solar energy used by CSP is measured via Direct Normal Irradiance (DNI), which is the energy acquired across the surface tracked perpendicularly to the sun. This is a proven utility-scale technology capable of providing large power requirements on a continuous basis. CSP systems mitigates the power intermittency problem with thermal storage of excess energy during the day either via hybridisation with molten salt or natural gas, then releasing the stored heat back into the steam cycle in the absence of sunlight. According to lEA (2010b), the four main CSP technologies are parabolic trough (line focus, mobile receiver), linear Fresnel reflectors (line focus, fixed receiver), solar towers (point focus, fixed receiver) and parabolic dishes (point focus, mobile receiver).

From lEA (201Db), the typical annual solar-to-electric efficiencies for parabolic trough, [FR, solar towers and parabolic dishes are 15%, 8-10%, 20-35% and 25- 30% respectively. Among the main issues associated with CSP plants is the cooling and water requirements. According to Glennon and Reeves (2010), minimal amount of water is consumed in the steam cycle because it is continuously recycled, but a significant amount of water is lost from the cooling process. This requires the CSP plant to be located near a water-source which may prove challenging if located in the desert. The three types of cooling processes typically used are the "open loop" where cooling water is returned to the environment after passing the condenser once, the "closed loop" where the water is recycled after passing the condenser with water losses occurring from evaporation at the cooling towers and process blowdown, and finally "dry cooling" where no water is lost because air is used for the cooling process, which may be unsuitable for desert climates because of high initial air temperatures. lEA (2010b) reported that the estimated water requirement for CSP plants is about 3000L per MWh.

2.3 -Technology selection If a plant is located, for example, in the desert, CSP is preferable as the desired solar thermal energy technology, to fully take advantage of the high DNI in the desert. In addition to that, its capability to store energy and provide continuous power to the production plant is a major advantage over the intermittency problems posed by PV plants. According to Aringhoff eta!. (2005), parabolic troughs are the most mature and commercially available CSP technology with proven investment and operating cost along with comparable efficiencies to PV plants. The issue of water requirement from the "closed loop" wet cooling process can be overcome by locating the plants near to the desert coastline with water desalination plants providing this source of water. Therefore, parabolic trough may be preferable.

Krebs (2011) reported that the total CAPEX for a 50MW plants is about 300 million Euros. lEA (2010b) then estimates that 30 personnel for plant operation and 10 for field maintenance are required. Krebs (2010) further reported that land area required would depend on factors like sun irradiation, collector design and storage capacity, which is estimated to be about 200 hectares for a 50MW plant. Process steam could also be drawn from the plant in addition to the generated electricity. From NREL (2011), Andasol-1 is a 50MW solar trough plant operating since 2008 with a turbine efficiency of 38.1% that generates 158,000 MWh/year of electricity.

Example 3 -Algal Production According to the U.S DOE (2009), there are multiple variations of methods to produce algae, but the process illustrated in Figure 2 is assumed to be the general representation of the production process of algae biomass.

3.1 -Algal Species Selection Chisti (2007) reported that microalgae are photosynthetic microorganisms that utilise sunlight to convert CO2 to potential biofuels and other high-value products.

Furthermore, they can produce up to 300 and 770 times more oil per hectare as compared to soybean and corn respectively. Microalgae with high oil productivity is desired for biodiesel production, where species like Nannochloropsis sp. and Schizochytrium sp. have displayed oil contents of about 31-68 wt% and 50-77 wt% respectively. No attempt will be made to pinpoint a specific strain suitable for this project because the strains used vary from company to company.

Example 4 -Algal Cultivation 4.1 Growth Factors According to Posten and Schaub (2009), the photosynthesis reaction by algae can be represented with the overall reaction: nCO., + n1120 -[CH2O] + aO. Ml = (1) Where [CH2O]n represents, for example, glucose, of which the energy required is assumed to be provided by sunlight. The typical n value is 6. From Grobbelaar (2008), a light, carbon and nutrient source is required by microalgae for autotrophic growth, where the carbon source is in the form of dissolved CO2 or HC03. However, although growing algae at optimum temperatures of about 20- °C and optimum light intensity, nutrient and CO2 levels results in a high yield, high rates also need to be realised for effective production. There are several factors that govern the growth rates of microalgae, one of them being the amount of light energy that penetrates the culture, where optical depths of less than 250 mm being the optimum penetration depth to drive photosynthesis. However, this light field will be constantly changing due to variations in culture depth! mixing induced turbulence and areal density, exposing the microalgae to a light (photosynthesis) and dark (respiration) alternation frequency. It has been found that increasing light/dark alternating frequencies and prolonging dark periods in relation to light periods increases photosynthetic rates. Another factor is turbulence because it increases the mass transfer rates of nutrients and metabolites between the microalgae cells and the growth medium, which results in higher growth rates. The final factor is the amount nutrients like Nitrogen(N) and Phosphorus(P) contained in the growth medium. According to Palanisamy S at (1991), Nitrogen:Phosphorus:Pottasium (NPK)fertilisers of ratio 16:20:20 or 14:14:14 can be used for mass culture of algae.

According to Chisti (2007), the only suitable cultivation methods for large-scale production of microalgae are raceway ponds and tubular photobioreactors (PBR).

4.2 -Open Raceway Ponds [Chisti (2007)] A raceway pond is made up of a close loop recirculation channel with depths of approximately 0.3 m. A constant culture is fed in front of the paddlewheel during the day, where it mixes and circulates the flow around the flow channel, with flow around bends being guided by baffles. The paddlewheel is operated continuously to enable continuous broth harvesting behind the paddlewheel and to avoid sedimentation.

4.3 -Closed Tubular PBR [Chisti (2007)] Tubular PBR are usually made up of an array of straight parallel transparent plastic or glass tubes. These solar collectors have diameters of about 0.1 m or less, allowing the penetration of light into the dense culture broth to drive photosynthesis and hence productivity. PBR operate on the basis of continuous circulation of the microalgal broth from the degassing column to the tubular solar collectors and back again. A typical tube arrangement would be the solar tubes being placed flat on the ground parallel to each other and oriented North-South to maximise sunlight capture. Furthermore, sedimentation of biomass is prevented by maintaining a highly turbulent flow in the PBR via mechanical pumps which may cause damage to the biomass or airlift pumps which are less flexible and require a supply of air to operate.

One important operational issue would be the high dissolved oxygen levels along with intense sunlight causing photooxidative damage to algal cells and the inhibition of photosynthesis. This forces the cutture to be constantly degasified via air stripping at the degassing column to avoid the dissolved oxygen levels to exceed the limit of about 400% of air saturation value. Another issue is the increase in pH due to the consumption of C02, which is an acidic gas. To avoid uncontrolled rise in pH or carbon limitation, a pH controller will therefore control the make-up CO2 injection into the degasser with potentially further injection points along the tube intervals. The final operational issue would be the temperature cooling requirements to maintain the optimum culture temperature in the day and the reduction of biomass loss via respiration at night through lower temperatures. This can be done via evaporative cooling in desert climates or heat exchangers located in the degasser or the tubular loop.

4.4 -Technology Selection The closed tubular PBR system is preferable. In terms of growth factors, PBR allow more light penetration which drives productivity along with higher levels of flow turbulence which will increase the light/dark alternating frequencies and mass transfer between the microalgae cells and growth medium. According to Grobbelaar (2008) and Chisti (2007), PBR systems generally have an advantage over raceway ponds in terms of lower contamination risk, less water loss, almost no 002 losses, likely reproducibility of production, less complicated process control, reduced susceptibility to the weather, nearly 30 times higher biomass concentrations during harvesting and require about 30% less land area.

However, PBR systems entail higher construction costs along with increased risk of overheating problems and higher dissolved oxygen levels, which need to be accounted for during the design process.

AlgaeLink, a company based in Netherlands was one of the many prospective companies contacted with regards to their tubular PBR systems. Bol (2011) reported that each system consists of 6 tubes of 6 m length each, which can be supplied within 3-6 weeks and installed in 1-2 days. Furthermore, the plant lifetime is estimated to be about 10 years with 2 personnel requirements for larger commercial sites of roughly 1-5 hectares. In addition, large scale PBR systems integrated with harvesting and drying systems entail a CAPEX of about 250,000 -500,000 per hectare with biomass yields of about 300 tonnes/hectare/year based on Australian climates. The estimated energy requirements of the system is about 1 Wh/m2/hour with an uptime of about 90% annually. Both fresh and saline water is compatible with the system, which suits this project since the desired location for the production plant is near the coastline. Other process parameters include biomass content of 1.5-3 kg/m3 in the culture and CO2 feed requirements of about 1.7-2.8 kg 002 per kg algae biomass.

4.5 -Algae Harvesting/Dewatering According to Uduman etal. (2010), due to the dilute nature of the harvested algae culture, significant energy is required for this process, which results in high OPEX to the overall process. The culture needs to be harvested, dewatered and dried because the biomass gasification stage during fuel production has a biomass water content requirement to be met. In general, this process will concentrate the culture from about 0.02%-0.06% TSS into a slurry with concentrations of about 5%-25% TSS. The stability of microalgae can be attributed to surface charge, steric effects and adsorbed macromolecules. Due to the varied characteristics of microalgae in terms of size and shape, it is hard to specify the best harvesting method.

From Uduman etaL (2010), the first commercially available method is centrifugation, which separate solids and liquids via centrifugal forces and is very reliable. The dynamics of the separation works based on the size of the microalgae particle and the difference in density of the components in the medium. The highest possible yield is about 12% TSS with a water removal factor of 120. However, the high-energy input of 8 kWh/m3 may prove to be too costly for a large-scale project like this.

Another method is filtration and screening where a suspension is passed through a permeable medium, resulting in the solids being retained and the liquid passing through. In addition, microstrainers or vibrating screen filters with specific pore sizes are used to screen the microalgae particles. The overall cost is affected by the flow-through rate of the filter, which depends on the microalgal concentration and screen opening size of which depends on the size of the microalgal species.

Smaller species or high microalgal concentration can cause lower flow rates. The extent of the pressure required to force the fluid through the filter will determine if gravity, vacuum, pressure or centrifugal force should be used. Surface filters are one of the filtration methods that deposit solids on the filter medium in a thin film.

The highest possible yield is about 5%-27% TSS with a water removal factor of 50-245. With moderate energy requirements of 0.88 kWh!m3, very good reliability and simple periodic replacement of filters and screens, this is therefore the suitable method for harvesting and dewatering for a large-scale project.

4.6-Drying According to Kadam (2001), solar dryers can be technically feasible for algae drying. Solar dryers work on the principle of converting sunlight to heat, which heats the drying air, subsequently drying the microalgae. Other measures like insulating layers and replacing damper air with fresh dry air in the dryer ensures constant and efficient drying. From Sander and Murthy (2010), it is assumed that energy inputs can be neglected and no biomass is lost from this process. The resultant biomass from this process will be approximately 9lwt%.

Example 5-Fuel Production According to Hamelinck et aL (2003), gasification of biomass along with Fischer-Tropsch (FT) conversion to biodiesel is potentially a clean and carbon neutral production process to produce biodiesel that can be utilised in current transport infrastructure. Kreutz et at. (2008) reported that a generic process for fuel production via gasification and FT would consist of the system components illustrated in Figure 3. It is also assumed that the feed preparation is covered in the harvesting and drying process from the algae cultivation.

5.1 -Gasification The main purpose of gasification is to produce syngas comprising mainly of CC and H2. Tijmensen et al. (2002) reported typical H2/CO ratios for currently operating biomass gasifiers to be in the range of about 0.45-2. The two main methods widely used for gasification are fixed bed and fluidised bed gasifiers according to Warnecke (2000). Fluidised bed gasification can be divided into bubbling or circulating fluidised beds. Pfeifer et aL (2009) reported that steam gasification of biomass via a dual fluidized bed with circulating hot bed material yields high quality syngas. With bed temperatures of about 850 °C, the biomass goes through several zones in the steam fluidized gasification zone: drying, thermal devolatilisation and partial heterogenous char gasification. Residual biomass char then enters the air fluidised combustion zone, which heats up the bed material to about 920 °C, which then flows back to the gasifier.

The bed material circulation rate and required energy for gasification determines the temperature difference in both gasification and combustion zones. The unique nature of this system is that it is auto-stabilising, where a decrease of temperature in the gasification zone causes a greater amount of residual char to be produced, hence more fuel for the combustion zone. Eventually, because more fuel is fed into the combustion zone, more energy is transported back into the gasification zone and thereby stabilising the temperature. Both zones are operated close to atmospheric pressures. The resultant syngas is generally composed of relatively low contents of tar (2-10 g/m3), less than 1 vol%db of N2 and high H2 content of about 35-40 vol%db. Suitable bed materials like olivine have adequate resistance to attrition and moderate tar cracking. From Calleja et aL (1980), there has been much controversy about the reaction mechanisms occurring in the gasifier. However, Wang et al. (2009) proposed that the main reactions in a steam/air fed fluidised bed gasifier are kj --mo kJ CH2OCU2ai: M=-7E.

CO--d:O-C--H 21a=-435b _*1 t4

L T

---

L2hCm (S ri H=-t-40aS, According to Hamelinck et a!. (2003), circulated fluidised beds are very suitable for large-scale syngas production from biomass. The dual fluidised bed system is a circulated fluidised bed system with a lot of advantages over the fixed bed, which includes lower capital investment requirements, more adaptable and tolerant to fluctuations in fuel material, less area requirement because of scale-up, steady gas compositions due to uniform conditions in the bed, good temperature distribution and a simpler technology with no moving parts.

Therefore this was the chosen gasification method for this project.

5.2 -Gas Conditioning and Acid Gas Removal According to Kreutz et a!. (2008), to ensure tar contents in the syngas is minimal, an external catalytic tar cracker is used to convert the residual tar in the syngas to light gasses. A fire-tube syngas cooler is then used to cool the tar4ree syngas to about 350 °C, which reduces the deposition of small particles and alkali species in the syngas. The final step in the gas conditioning process is the further cooling of the syngas to 40 °C before being fed into the acid gas removal system.

Kreutz et at (2008) also reported Rectisol being a suitable acid gas removal method operating at about 20-70 bar to remove acid gases like CO2 and H2S contained in the syngas, with potentially 100% removal of CO2. The removal of CO2 and H2S is imperative to enhance the kinetics of the FT synthesis and to avoid poisoning of the catalyst in the FT reaction. Because methanol is used as the working fluid and has acid gas solubilities being inversely related to temperature, refrigeration is normally used to increase solubility. Biomass derived syngas contains low levels of sulfur, which then allows the co-removal of CO2 and sulfur species derived from the H2S using a single Rectisol absorber column.

5.3 -Fischer-Tropsch Synthesis The main objective of the FT synthesis is to convert syngas into FT liquids comprising mainly of liquid hydrocarbon (HC) fuels. According to Tijmensen et al. (2002), FT reactors may include fixed bed and slurry reactors coupled with iron or cobalt catalysts in the reaction. From Sie and Krishna (1999), an example of a fixed-bed reactor is a multitubular tixed-bed reactor operated with gas recycles and internal cooling via water-cooled tubes intending to maximise conversion and remove reaction heat. The catalyst is packed into a rectangular box located in the reactor. On the other hand, a slurry reactor works on the basis of contacting syngas with the suspended fine catalyst in the form of a slurry. Internal cooling pipes also remove heat from the reaction to be utliised elsewhere. The slurry reactor is preferable because it has several advantages over the fixed bed reactor. These advantages as reported by Tijmensen et al. (2002) include less down time, lower catalyst consumption, high average conversions of about 80%, greater than 90% C5+ selectivity, lower pressure drop and is considered a proven technology. One disadvantage however is that the wax/catalyst separation is more difficult but still possible.

Sie and Krishna (1999) proposed this reaction as the main reaction in the FT reactor: CD+2fL__(Cff,_ +ThO (7) with -CH2-being the building block for longer hydrocarbons since FT reactions produce hydrocarbons of variable chain length also known as syncrude. The yield of this reaction is determined by the liquid selectivity or C5+ selectivity of the process, which is determined by the chain growth probability (CGP). This is the probability that a hydrocarbon chain grows with a -CH2-group as opposed to chain termination. Since a high liquid selectivity is required to produce long hydrocarbon chains, the Anderson-Schulz-Flory (ASF) distribution can be used to describe the link between hydrocarbon yield and CGP. This distribution describes the molar yield in carbon number as: fraction C = o1(1a), where a is the COP and n being the hydrocarbon length. This then results in (1-ci) being the probability for chain growth termination. Figure 4 displays the product distribution with different CGP, of which diesel is represented by gasoil. Among the factors that affect the selectivity of the reaction include the type and age of catalyst, H2/CO ratio in the syngas, pressure, temperature and the type of reactor. Typical operating conditions are about 20-40 bar and 180-250 °C.

5.4 -Syncrude Refining According to Tijmensen et al. (2002), the FT liquids or syncrude must undergo hydrocracking to eventually produce biodiesel. Firstly, double bonds in the hydrocarbon chains are removed via addition of hydrogen, then the syncrude is catalytically cracked with hydrogen. Typically, the wax cracking conditions can be tailored to produce diesel, kerosene and naphtha with weight distributions of 60%, 25% and 15% respectively. However, this mix can be easily adjusted to suit the desired product mix. Among the benefits of FT liquids is that it is free of sulfur and other contaminants and the biodiesel has a high cetane number.

5.5 -Technology Selection The technology used by Rentech for fuel production included a dual fluidised bed gasifier, slurry bubble column reactor with iron catalyst and a subcontracted upgrading technology from Honeywell UOP. Corwin (2011) reported that 1000- 1500 tonnes/day of dry biomass is required to produce 1500-2000 bbl/day of biofuel with a product mix of 70% biodiesel and 30% naphtha. Furthermore, biomass moisture content should be less than 15% before being fed into the gasifier. Surprisingly, the plant would be self sufficient in terms of energy required because the exothermic energy released from FT synthesis is used to power the other processes, with the potential of marginal energy export via a steam turbine.

The life-cycle carbon footprint of the gasification with FT process using Rentech's technology is reported to be near zero. Ballpark estimates of the CAPEX were about 500-700 million USD for a 2000 bbllday plant. According to ExxonMobil Refining & Supply (2006), the land area required for a fuel production plant would be about 2100 acres for a 501,000 bbllday plant.

Examçle 6 -Systems Level Analysis It was desirable to analyse the technologies on a systems level, which involves preliminary process designs of the technologies offered by the companies that were contacted. Generic process assumptions were assumed for each technology to allow an estimated mass and energy balance to be generated.

6.1 Methodology and C-FAST model description

Since updated technological data was required, one of the main sources of acquiring data was through personal communications with the companies contacted, which occurred via telephone and email conversations.

The C-FAST model is a Microsoft Excel spreadsheet whichbrings selected technologies together to analyse the technical, economic and geographical feasibility of connecting these technologies together for the production of algae-derived biodiesel, powered via CSP. The main idea was to modularise these technologies into separate spreadsheets to allow the analysis of a broad range of technologies to be examined, with the option of connecting these separate technologies together to form a possible production method. These modules will have specified capacities as communicated by the companies. For simplicity, although other technologies were included into the model, only the main technologies chosen from Solar Millennium, AlgaeLink and Rentech will be considered for this model. The main model outputs were the yield, CAPEX, OPEX, energy and land requirements. A more thorough review of the reactions occurring in the process will be discussed in the UNISIM simulation section.

Several biodiesel production capacity scales were considered. These scales were to replace the diesel production capacity of Saudi Arabia, the diesel consumption of UK, an average UK refinery plant and a pilot plant. These production capacities were 1.04x1 08 tonnes/year, 2.25x1 07 tonnes/year [Office for National Statistics (2010)], 1.5x106 tonnes/year [Colquhoun and Ortmans (2010)] and 348 tonnes/year respectively. (See appendix A for calculation of Saudi Arabia and pilot plant).

The model allows technical and economic user defined inputs to be fed into the model. For example, the main types of inputs include component densities, crude oil barrel diesel fraction, SI unit conversion values, exchange rates, commodity prices, scale economy exponents and tax rates. These inputs are global to the model and will apply to all the technologies considered.

The inputs are passed to the three main modular spreadsheets, represented by the Solar Millennium (CSP), AlgaeLink (Algal Cultivation) and Rentech (Fuel Production) process. The calculations performedare mainly based on the feed requirements, yield, efficiency, CAPEX, OPEX and land requirements. See Appendix B, C and D for the preliminary mass, energy and financial calculations for the CSP, algal cultivation and fuel production process.

The outputs of the modular spreadsheets are technology specific and can be used as an input to other technology spreadsheets. For example, the main outputs of the Solar Millennium, AlgaeLink and Rentech spreadsheets are the amount of electricity produced, biomass produced and biomass required respectively for the individual specified capacities of each technology. These outputs will then be collected separately on a common "output spreadsheet" for the preliminary scale calculations. Depending on the biodiesel production capacity desired, the amount of biomass required for the Rentech fuel production process will be directly related to the diesel production capacity, which then allows a simple scaling operation to determine the number of Rentech production units required to match this diesel production capacity. The amount of biomass produced by AlgaeLink can then be scaled to match this amount of biomass required to determine the number of AlgaeLink production units required. Solar Millennium's output of total electricity produced can then be scaled to match the total amount of electricity required by the AlgaeLink and Rentech process, which then determines the number of CSP plants required. These modules also give economic and geographical outputs, which allow total CAPEX, OPEX and land requirements to be calculated for the chosen fuel production method (See Appendix G for OPEX calculations).

Additional tools were added into the modelin order to have a more thorough economic analysis. These were tools to produce NPV graphs and resulting oil pump prices. Options to alter variables like the price of crude oil by different magnitudes and to apply economies of scale to individual technologies based on the scale required were also integrated into the model.

6.2 Explanation of model operation The main purpose of analysing 4 different scales of production capacities was to investigate if enough biomass can be produced, if the land area required is sensible, if the project would be profitable and also how scale economies would affect the economics of the project.

Majority of the assumptions used were based on data obtained from the companies to ensure the project closely represents these technologies. The calculations in Appendix B, C and D have been structured to allow a logical sequence leading to the model outputs. In addition, each individual technology spreadsheet was based on the capacities quoted by the companies. Therefore, a common output spreadsheet was used to gather the model outputs to allow the connection of these separate technologies in terms of mass, energy and finance through scaling methods. A plant capacity of the Saudi Arabia diesel production scale will be used to demonstrate the scaling operation (See Appendix E). Table 1 shows the result of the scaling operation. This result can then be used to decide if scale economies should be applied to the individual technologies.

Table 1: Saudi Arabia scaling results Technology Number of systems required Solar Millennium 1 64x1 o AlgaeLink 2.48x107 Rentech 1 64x1 3 Several assumptions were made according to an internal study done by Helme and Harris (2011). To calculate the NPV of the project, the profitability of the project is divided into revenues and cost. The sale of diesel, naphtha and carbon credits makes up the revenue streams whereas OPEX and tax make up the costs. The CAPEX was assumed to be spent at the beginning of the first year.

Discount rates, inflation and tax rates of 15%, 2.3% and 0.25 respectively were incorporated. The price of diesel, naphtha and carbon credits are assumed to be about £0.60/litre, £0.43/litre and £15.10/tonnes respectively. In addition, the price increase excluding inflation of biodiesel, naphtha and carbon is assumed to be 1%, 5.6% and 5% per annum.

6.3 -Results and Output of model This section will display the output of the model for the four capacity scales. This comes as a result of the scaling methods performed, which allows the summation of all the model outputs to give a rough estimation of the technical, economic and geographic implications of the entire production process. Table 2 shows the summary of the number of systems required for each technology from the scaling method for all four of the production scales. Table 3, 4, 5 and 6 shows the individual model outputs for each technology for all four of the production scales.

Table 7 then shows the summation of the individual model outputs for all three technologies forming the total output for all four of the production scales.

Table 2: Overall scaling results

NUMBER OF SYSTEMS

TECHNOLOGY REQUIRED

Saudi Arabia Diesel UK Diesel Average UK Pilot Plant Production Consumption Refinery production Solar 1.64x103 3.58x102 2.38x101 5.52x103 Millennium __________________ ________________ _____________ ____________ AlgaeLink 2.48x107 5.39x106 3.59x105 8.33x101 Rentech 1.64x103 3.55x102 2.36x101 5.48x103 From Table 2, the large number of systems required for the larger production scales renders it somewhat financially unrealistic. However, it can seen that for the pilot plant scale, scale economies cannot be applied for Solar Millennium's and Rentech's technology due to its small scale. For the larger production scales, a scale exponent of 0.9 can be applied to the CAPEX of the individual technologies.

Table 3: Saudi Arabia model outputs __________________ __________________ Technology Solar Millennium AlgaeLink Rentech CAPEX (f) 2.09x1011 1.81x1011 2.38x1011 OPEX(E/year) 1.35x101° 1.17X101° 1.53x101° Land Required 3.29x109 2.98x101° 5.54x107 (m2) _____________ _____________ _____________ Electricity 2.61x108 N/A N/A Produced (MWh/year) ____________________ ____________________ ____________________ Electricity N/A 2.61x105 0 Required (MWh/year) ___________________ ___________________ ___________________ CO2 Consumed 0 2.06x109 0 (tonnes/year) Table 4: UK diesel consumption model outputs __________________ Technology Solar Millennium AlgaeLink Rentech CAPEX () 5.29x101° 4.57x101° 6.01x101° OPEX (fjyear) 3.41x109 2.95x109 3.88x109 Land Required 7.15x108 6.47x109 1.20x107 (m2) _____________ _____________ _____________ Electricity 5.67x10' N/A N/A Pioduced (MWh/year) ____________________ ____________________ ____________________ Electricity N/A 5.67x107 0 Required (MWh/year) ___________________ ___________________ ___________________ 002 Consumed 0 4.47x108 0 (tonnes/year) ____________________ ____________________ ____________________ Table 5: UK refinery model outputs _________________ __________________ Technology Solar Millennium AlgaeLink Rentech CAPEX () 4.62x109 3.99x109 5.25x109 OPEX (Elyeai) 2.98x108 2.57x108 3.39x108 Land Required 4.76x107 4.31x108 8.01x105 (m2) ________________ _________________ _________________ Electricity 3.78xl06 N/A N/A Produced (MWh/year) ___________________ ___________________ ___________________ Electricity N/A 3.78x106 0 Required (MWh/year) ___________________ ___________________ ___________________ 002 Consumed 0 2.97x10' 0 (torines/year) ___________________ ___________________ ___________________ Table 6: Pilot plant model outputs _________________ __________________ Technology Solar Millennium AlgaeLink Rentech CAPEX (f) 1.47xl06 2.14xl06 1.67xl06 OPEX (E/year) 9.49x104 1.38x105 1.08x105 Land Required 1.10x104 1.00x105 1.86x102 (m2) ____________ ____________ ____________ Electricity 8.76x102 N/A N/A Produced (MWh/year) ___________________ ___________________ ___________________ Electricity N/A 8.76x102 0 Required (MWh/year) ____________________ ____________________ ____________________ 002 Consumed 0 6.90x103 0 (tonnes/year) ____________________ ____________________ ____________________ Figure 5 sumrnarises the main outputs from Tables 3,4,5 and 6. The CAPEX and OPEX percentages attributed to Solar Millennium, AlgaeLink and Rentech are 33%, 29% and 38% respectively for all the production scales except for the pilot plant scale. This percentage is constant because all three processes were subjected to the same scale exponent for the three capacities (See Appendix F).

The Rentech process therefore requires the most CAFEX, which is due to the nature of the process and the large amount of unit operations involved. Both the gasification and FT reaction occur at high temperature and pressures, which requires costly material reinforcing for safe operation. In addition to that, the Rectisol acid gas removal system has a complex flow scheme and requires solvent refrigeration up to -40°C to -60°C, which requires much power and therefore greater CAFEX and OPEX. On the other hand, Solar Millennium's CSP system also has a comparable CAPEX and OPEX. With solar-to-electric efficiencies of about 15%, it is not surprising that a large solar field area with costly state-of-the-art receivers is required. In addition to that, the CAPEX and OPEX related to the power block is also significant, with costly components like the steam turbine, superheaters, cooling systems and water treatment systems.

Finally, the main CAPEX cost contributors in the AlgaeLink system is the construction cost of the PBR itself. Otherfactors like harvesting and drying cost contribute a significant amount of the OPEX. Furthermore, a slight degree of cooling is required for desert cultivation of algae as optimum growth temperatures are about 20-30 °C, which is slightly lower than desert climate temperatures.

The CAPEX and OPEX percentages for the pilot plant scale attributed to Solar Millennium, AlgaeLink and Rentech are 28%, 40% and 32% respectively. If compared to the case where no scale economy advantages are applied for all three processes, these percentages are about 23%, 51% and 26% respectively.

This is expected because both the Solar Millennium and Rentech process do not have scale economy advantages at the pilot plant production capacity, which causes an increase in their CAPEX and OPEX.

It has also be found from Figure 5 that the AlgaeLink systems take up about 90% of the land area required with Solar Millennium's CSP system taking up the remainder 10%. This is mainly due to the flat horizontal arrangement of the PBR on the ground, which requires increased land area. The same argument applies for Solar Millennium's solar field, which is horizontally arranged on the ground.

Table 7: Overall outputs for the 4 production scales ______________ Production Saudi Arabia UK Diesel Average UK Pilot Plant Scale Diesel Consumption Refinery Production production Biodiesel 1.04x10 2.25x10' l.SOxlOb 3.48x102 Produced (tonnes/year) ________________ ________________ ________________ ________________ Naphtha 4.44x10' 9.66x106 6.43x105 1.49x102 Produced (tonnes/year) ________________ ________________ ________________ ________________ Biomass 8.94x10H 1.94x108 1.29x10' 3.00x103 Prod uced (tonnes/year) ________________ ________________ ________________ ________________ CAPEX (fi) 6.27x1011 1.59x1011 l.39x101° 5.28x10b OPEX (fl/year) 4.05x101° 1.02x101° 8.94x108 3.41x105 Land 3.31x101° 7.20x109 4.79x1OU 1.11x105 Required (m2) ______________ ______________ ______________ ______________ Electricity 2.61x103 5.67x107 3.78x10b 8.76x102 Produced (MWh/year) ______________ ______________ ______________ ______________ Electricity 2.61x10 5.67x10' 3.78x10b 8.76x102 Required (MWh/year) _______________ _______________ _______________ _______________ Net CO2 2.06x109 4.47x108 2.97x107 6.90x103 Consumed (ton n es/year) ________________ ________________ ________________ ________________ Figure 6 summarises the outputs from Table 7. In general for all capacities, the biomass yield is about 27 kg/m2 and the amount of diesel produced is about 3.14 kg/rn2. On a mass basis, the naphtha produced is about 43% of the total biodiesel produced, which accounts for a significant amount of the project's revenues. The OPEX for all capacities is about 6.45% of the CAPEX. The total CAPEX per m2 required for the four capacities analysed from the largest to the smallest is £18.94, £22.08, £29.02 and £47.57 respectively, which clearly shows the significant savings from scale economies. The corresponding OPEX per m2 in that order is £1.22/year, £1.42/year, £1.87/year and £3.07/year respectively.

Furthermore, the total electricity required per m2 is about 7.89x10-3 MWh/year.

Another fort-n of revenue would be the carbon credits gained from the carbon sequestered, with a carbon consumption of about 62 kg CO2 per m2. From Figure 7, on the basis that the process consumes a net amount of CO2 to produce biodiesel, it is therefore assumed that the fuel produced is carbon negative.

To put the production scale into context, most of the parameters analysed have similar or almost similar (CAPEX and OPEX) orders of magnitude differences.

Therefore, the estimated orders of magnitude without decimals for the four capacities analysed from the smallest to the largest is about 1, 3, 4 and 5.

However, it should be noted that the actual values are slightly greater than these estimates.

For comparison purposes, the Saudi Arabian production scale will be used to put into context the worldwide implications of the project. The amount of biodiesel produced is about 1.04x1 08 tonneslyear, which is about 7.6% of the world diesel consumption in 2009. Furthermore, the naphtha produced of about 4.44x1 0' tonnes/year is about 5% of the global production and consumption of refinery naphtha in 2010. In addition, the initial CAPEX involved is about £6.27x1011, which accounts for about 35% the value of Saudi Aramco. The amount of land required is about 3.31x101° m2, which is about 0.4% the land area of the Sahara desert. Finally, the amount of CO2 consumed is about 2.06x109 tonnes/year, which is about 7% of the world CO2 emissions in 2009.

Figure 3 illustrates the main revenue contributors, with diesel being the biggest contributor and carbon credits coming in second. This was an interesting result because it was initially assumed that CO2 would be an additional revenue stream.

However, it is actually a major revenue contributor with an estimated 5.6% annual price increase, which may prove beneficial in future project cashflows.

From Figure 9, the project payback period can be found when NPV equal to zero.

The real extent of scale economies can now be seen, with the Saudi Arabian and UK diesel consumption capacities having payback periods of about 8 and 12 years, whereas the UK refinery and pilot plant capacities have negative NPV even after 20 years, which therefore proves to be non profitable. The scale economy benefits are due to a steep learning curve in production especially in the relatively new technologies like CSP and algae cultivation, which makes the volume of savings much bigger for the larger production capacities. Alternatively according to Towler and Sinnott (2008), fixed costs usually remain constant when plant size increase, which causes the fixed cost per kg of product to decrease.

An oil price factor tool was integrated into the model to allow the scaling of current diesel and naphtha prices to analyse the required diesel pump price for the project to have a payback period of 10 years. From Figure 9, the required diesel pump price per litre for all four capacities from largest to smallest is £1.33, £1.48, £1.81 and £2.69. A fuel duty of £0.58 and VAT of 20% was incorporated to allow comparison with current diesel prices, which is about £1.42/litre. With diesel prices for Saudi Arabia and UK consumption capacities being comparable to current diesel prices, this project holds the potential to be a very attractive prospect for the production of carbon negative transport fuel.

According to Towler and Sinnott (2008), for order of magnitude or ballpark estimates mainly used for this initial feasibility study with minimal design information, an uncertainty of about 30%-50% can be assumed. The resultant CAPEX and OPEX therefore has an uncertainty of about 42% (See Appendix H).

Examijle 7 -UNISIM Process Simulation This preliminary simulation was based on the pilot plant production capacity of 348 tonnes/year and 149 tonnes/year of diesel and naphtha respectively. Majority of the process parameters and reactions assumed were covered in the literature review.

Table 8: Main stream compositions Section CSP ALGAECULTIVAT1ON FUEL PROOUCfloN Process 071 Steani PBS 0:36 Say Akae star Bk Feed Raw Sean Rett Fyn Nap [tie ky 1: ass fy est tos:-vi en3 test rr.as Ga, Sw Sv S p y;dy: I [F,s ye! [u"o [icy gas Sos cruSt Stream 41 46 48 3:; 3..' j4 39 81 5 8 21 26 k'I. 32 TotalFiow 0.1 1.06 0.74 0.37 010 0.11 ftii 8.94 0.13 0.14 4.62 4,62 1.38 4.71 1.11 jg/s) [-07 E-02 5-02 -t7 -1ta 5-02 Total Flow 2.86 5.89 931) 4.35 3.25 1.87 1.73.97 2.93 7.04 -1.31 2.95 9.55 3.28 5.37 rnoi/s) [-[-02 5-03 [--33 [-93 [-03 5-03 5-04 [-09 [-07 5-03 5-03 [-05 [-05 E-03 ______ 04 ________ C-oinooner.-t Mote 36 H20 0 100 49.77555 445 nAB 71.35048.5-i 15-AS 0 0 0 0 9 0 54.2334.27 0 0.02 0.01 0 027.670.3/0.54 0.120-122 Methane u 0 0 0 0 0 0 0 14.30 0 0 0 0 0 Nitrogen 0 0 0 0 0 0 0 0 0 0 0.5-3 0-93 0.02 0 Oxygen 00 0 60.2291.550 1 033.550 1 5 0 5 0 CO 0 0 0 0 0 0 0 0 3 137231.9/125-2662 0 1.4/ Thermtnol 100 0 0 0 0 0 0 0 0 0 0 0 0 0 0 HIS 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Hydrogen 0 0 0 0 0 0 0 0 0 41.37.2255.050.67 0 1,21 C12 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Diesel o 0 0 0 0 0 0 0 0 0 0 176 53.99 0 07.07 ttaphtha 0 0 0 5' 0 0 0 0 0 0 0 1.46 44.38 100 0 Dxtroge 0 -0 0 0 0 U 0 0 0 0 0 0 0 0 0 Algae 0 3-0 0 0 28:532863100 15.92 0 0 0 1 0 0 Bio,nes; Act, 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Methanol 0 0 0 it Ii:1 0 0 (1 tI 0 0 1) 0 0 carbon 0 0 0 0 0 0 0 0! 0 0 0 0 0 0 0 S_Vapour 0 0 0 0 0 0 0 0 0-0.04 0 0 0 0 0 Table 9: Physical properties of hypothetical components Hypothetical Components Physical Properties Algae Biomass MW=1 8Okg/kmol,Density=570kg/rn3 Ash MW=292kg/kmolDensity=5lOkg/m3 Diesel MW=212 kg/kmol,Density=880 __________________________________ kglm3 Naphtha MW=1 lOkg/kmol,Density=B7Okg/m3 Therminol MW350kg/kmol,Density875 ________________________________ kg/rn3 Table 10: Main equipment simulation parameters Iquipinelit Paiarneters (ST PLANT Solar Receivers lherniinoi as HTF, Tin= 25°C lout'-400°C -Delta P = lOkPa Hear Exchanger I Tube side &TherminoL Tin = 400°C. ioo = 25°C \ Shell side (Steam. Tin = 122°C :Tout = 175,5°C 1 Number of shell passes 2, Tube passes per shell Steam Turbine Delta F = -52.47°C, Delta P -iOOkPa, Power produced = 0.1041 MW ALGAE CTJLTI'.'ATION. HARVESTING ANT) DRYING PER Reactkm 6 6C 6H20 Glucose + 602 [Basis = CO1. Conversion = 63.76%} Filtei/Ceutrifage Feed liquid lo solid p*rutiuct stream = 0.9. Food uiid to soiidpoduct stream -Dryer Overheads."Botroms Srjlit liacrions (Wates = 1. CUr I. Oxygen = 1) Fl, FL PRODUCTION Air Separation Ovetheads.?Bottoms Split Fiactions Oxygen = 1. Nitrogen = Ut Unit Gasifier GasifierI 805.9°C, Gasifrer P 28,8 bar, Delta P260kPa. Duty 0.264 MW Reaction 1: L'.S55Algae-Biorrsass "3.Yl3Carbon 2.S5Hydrogen + l.S6Oxygers 0.03 iNitrogen 0.OOSuipin;r 0.O2lAsh [Basis Aigae Biomass. Canversion = Reaction Carbon H2O CO H [Basis = Crboi, Conversion = 10%] Reartrm 3:C.ajaon * 0 -(02 [Rasis = Cathc,e, (o,n'er'sinn = 50%] Reaction I C02 + Cafoon -2C0 Dasis = Carbon. Conversion = 50°] Acid Gas Resuoval Bottom stream P = 3 bar. Overhead stream P = 20.1 bar. Methanol as solvent, Overheads.'Bottrsim Split Fractions C02 = 0X'LNitrogen 1.02 = ,C0 = .1-12 -

_________________________ I

Fiseher-Tropseb Reactor 7= 90.3°C, Reacror P = 23. bar.Dury 2.96510r MW Reacto, Reaction 5 0.3C0 * 0.6112 -s C'.OJDiesel C'.O26Naphtha Bas,s = CO.

Conversion = 35.5%] Distillation Li7hrkey (Napistha; in bo:torns = 0. Heavy key (Diesel) in distillate = 0, Condenser Column and Rehoiler Pressure = 20 Oar, Fxte.rnal Reflex Ratio 2 Table 11: Energy and 002 balance Process CSP Algae Fuel Production _________________ Cultivation Net Energy (kW) + 104.1 -100 + 12.86 NetCO2(kg/s) 0 -0.131 0 Table 8 displays the stream compositions of the main streams whereas Tables 9 and 10 show the parameters assumed for the components and equipments in the simulation.

For CSP, therminol is assumed to be the HTF because it is a synthetic oil that is low-fouling and thermally stable at high circulation temperatures of about 400°C.

For the steam turbine, the power produced is about 100 kW or 8.76x102 MWh/year, which matches the pumping electricity requirements of the algae cultivation process. However, the water consumption of about 1.061 kg/s equates to about 38,000 litres/MWh, which is considerably higher than the model assumption of 3000 litres/MWh. This is mainly due to the absence of a closed loop water recycle in the preliminary simulation, which will significantly reduce the consumption figures closer to the model estimates.

For the algae cultivation process, photosynthesis is the assumed reaction in the PBR. The conversion of 63.76% of the feed CO2 into glucose (dextrose) was assumed to match the yield quoted by AlgaeLink. Dextrose is then assumed to take the form of the algae biomass. The degasser is used to vent the gasses like CO2 and 02. The model however assumes full consumption of CO2 in the PBR, which is about 0.075 kg/s of CO2 greater than that from Table 11. This may be due to proprietary operating conditions and reactions taking place, leading to greater CO2 consumption. Furthermore, the model yield is based on multiple PBR systems whereas the simulation combines them into one single reactor.

Majority of the process parameters for the fuel production process was obtained from Kreutz et aL (2008). The assumed reactions taking place in the gasifier was simplified to four main reactions to allow a reasonable syngas composition to be obtained, with a H2:C0 ratio of about 2.1. The gasifier in the model was assumed to be a dual fluidised bed gasifier, although a single fluidised bed is used in this preliminary simulation. The main function of the acid gas removal column is to remove CO2 from the raw syngas to produce clean syngas by using methanol as a solvent. This dissolved CO2 can then be retrieved from methanol to be fed into the PBR. The reaction in the Fischer-Tropsch reactor is simplified to match the yield quoted by Rentech, with a CO conversion of about 35.5% to produce syncrude that contains both diesel and naphtha. This simplification then negates the need for hydrocracking of the syncrude, where a distillation column is used instead to separate out the products with diesel and naphtha being the heavy key and light key respectively.

The results from Table 11 assume that the energy required by the solar receiver and photosynthesis is derived from the sun. Furthermore, the fuel production process appears to be energy neutral with the slight capacity to export excess electricity.

The technological, economic and geographic feasibility of the solar powered production of biofuels from algal biomass have been evaluated both on a systems level and using a dynamic UNISIM simulation, rendering the objectives of the project achieved.

The ability to analyse the impact of individual technology parameters on the total required investment, land area requirements, electricity requirements and CO2 lifecycle have been made possible with the C-FAST model. The four production capacities analysed from the smallest to the largest were of the order of magnitudes of about 1,3,4 and 5. Furthermore, the scale exponent of 0.9 was found to be reasonable to estimate scale economy effects. For the larger production scales, 33%, 29% and 38% of the total CAPEX and OPEX is attributed to the CSP, algae cultivation and fuel production process respectively.

In addition, the algae production process occupies about 90% of the total land area required, with the CSP plants occupying the remainder 10%. Among the common features for all four production capacities is the biomass yield of 27 kh/m2, biodiesel production capacity of 3.14 kg/rn2, electricity requirements of 7.89x103 MWh/year/m2 and CO2 consumptions of 62 kg/rn2. On the other hand, the total CAPEX required for the four production scales from the largest to smallest is £18.94/m2, £22.08/m2, £29.02/m2 and £47.57/m2 respectively. The corresponding OPEX is £1.22/year/m2, £1.42/year/m2, El.87/year/m2 and £3.07/year/m2 respectively. In terms of global impact, the Saudi Arabian diesel production scale has the potential to provide for 7.6% of the world diesel consumption and consume 7% of the world CO2 emissions in 2009 but require about 0.4% the land area of the Sahara desert. In terms of profitability, the two largest production scales have payback periods of about 8 and 12 years respectively, whereas the other two production scales never breaks even after 20 years. Finally, the required diesel pump price for a 10-year payback duration for the four production scales from the largest to the smallest is £1.33/litre, £1.48/litre, £1.81/litre and £2.69/litre respectively, with the two largest production scales having comparable prices to current diesel prices. It is clear that larger production scales will therefore be favourable towards economic feasibility but poses difficulty in terms of technical and geographic feasibility.

The UNISIM simulation confirms the compositions of the main streams, with comparable algal biomass and biodiesel yields to the C-FAST model. However, due to the simulation being in the preliminary stage without detailed equipment designs, other parameters like the energy balance and total CO2 consumption differ from the model. However, the simulated process does give a good dynamic framework for a more detailed component, energy and equipment analysis for the whole production process.

APPENDICES

A) Production Capacity Calculations i)Saudi Arabia Saudi Arabia oil production = 9.764x106 bbl/day Diesel fraction of an oil barrel = 22% Annual crude production = 9.764x106bb1/day x 3e5days = 3,563,860,000 bbl/year Volume crude produced = 3,563,860,000 bbl/year x 0.1589873 m3/bbl = 566,608,479 m3/year Volume diesel produced = 22% x 566,608,479 m3/year = 124,653,865 m3/year Mass diesel produced = 124,653,865 m3/year x 832 kg/m3 = 1.03712x108 tonnes/year ii)Pilot Plant Production capacity based on a 100,000 m2 AlageLink system.

AlgaeLink biomass yield (1200 m2 system) = 36 tonnes/year Number of systems required = 100,000 m2/1 200 m2 = 83.3 Amount of biomass produced = 83.3 x 36tonnes!year = 3000 tonnes/year Biomass:Biofuel(Rentech) = 6.03 Amount of biofuel produced = 3000 tonnes/year / 6.03 = 497.5 tonnes year Biodiesel:Naphtha = 70:30 Amount of Diesel produced = 497.5 x 70% = 348 tonnes/year B) CSP(Solar Millennium) Turbine Capacity = 50 MW Turbine Efficiency = 38% Uptime = 95% Operational Hours = 24 hours/day Annual Electricity Production = 50 MW x 38% x 95% x 24 hId x 365 days = 1.59x105 MWh/year Water Consurnption(Wet Cooling) = 3000 kg/MWh x 1.59x105 MWh/year = 475602300 kg/year Land Area Required = 2,000,000 m2 CAPEX = 300,000,000 x 0.887464 £I =f266,239,200 OPEX = 6.45% x £266,239,200 = £ 17,172,428 C) Algae Cultivation(AlgaeLink) System Volume = 140 m3 Biomass content in culture = 1.5656 kg/m3 Algal Growth Duration = 1 day Harvest Rate = 50% Harvested biornass per system = 140 m3x 1.5656 kg/m3 x 50%/i day = 109.59 kg/day Biomass wt% in harvested culture = 25% Mass of water in harvested culture = 75% / 25% x 109.59 kg/day = 328.8 kg/day Moisture content in biomass after drying = 15% Uptime (Annually) = 90°Jo Annual biomass obtained per system = 109.59 kg/day x 365 days x 90% = 36 tonnes/year Ratio of CO2 required:Biomass Obtained = 2.3 Mass of 002 consumed = 2.3 x 36 tonneslyear = 82.8 tonnes/year Land Area Required = 1200 m2 Energy Requirements = 1 Wh/m2/hour Total Energy Required = 1 Wh/m2/hour x 24 hours x 365 days/yearx 1200 = 10.51 MWh/year CAPEX = 375,000 /hectare /10,000 m2/hectare x 1200 rn2 x 0.887464 £/ = £39,936 OPEX = 6.45% x £39,936 =f2,576 D) Fuel Production(Rentech) Diesel volume fraction in barrel = 0.7 Naphtha volume fraction in barrel = 0.3 Density of barrel produced = (0.7 x 832 kg/rn3)+(0.3 x 665 kg/rn3) = 781.9 kg/rn3 Production capacity = 2000 bbl/day x 365 Wy x 0.159 m3/bbl x 781.9 kg/m3 = 9.075x104 tonnes/year Amount of biomass required = 1500 tonnes/day x 365 days/year = 547,500 tonnes/year Ratio biomass:biofuel = 547,500 tonnes/year / 9075x1 o tonnes/year = 6.03 Amount of diesel produced = 0.7 x 9.075x1 o tonnes/year = 6.35x1 o tonnes/year Amount of naphtha produced = 0.3 x 9.075x104 tonnes/year = 2.72x1 o tonnes/year Totat Energy Requirements = 0 MWhfyear(Self-sufficient) Land Area Required = 2000 bbl/day/ 501,000 bbl/dayx 2100 acres x 4046.86 m2/acre = 33,926 m2 CAPEX = $ 500,000,000 x 0.61 £/$ = £ 3.05x108 OPEX = 6.45% x £ 3.05x1 8 =f1.97x10' F) Scaling Of Technologies Saudi Arabian biodiesel production capacity = 1.O4xlo8tonneslyear From Appendix D (Rentech), Electricity required per system = 0 MWh/year(Self-sufficient) Diesel Produced by 1 Rentech system = 6.35x104 tonnes/year No. of systems required = 1.04x1 8 tonnes/year / 6.35x1 o4 tonnes/year = 1.64x103 systems Amount of biomass required = 1.64x103 systems x 547,500 tonnes/year = 8.95x1 8 tonnes/year From Appendix C (AlgaeLink) Electricity required per system = 10.51 MWh/year Amount of biomass produced by 1 AlgaeLink system = 36 tonnes/year No. of systems required = 8.95x1 08 tonnes/year /36 tonnes/year = 2.48x107 systems Total Electricity Required = 2.48x107 systems x 10.51 MWh/year = 2.61 xi 08 MWh/year From Appendix B (Solar Millennium), Electricity produced per plant = 1.59x105 MWh/year Total electricity required by AlgaeLink and Rentech = 2.61x10° MWh/year + 0 MWh/year = 2.61x108 MWh/year No. of CSP plants required = 2.61x108 MWh/year/ 1.59x105 MWh/year = 1.64x1 o systems F) Scale exponent calculation example For CSP plant, CAFEX(C1) = £2.66x108 Electricity Production Capacity (Si) = 1.59xi o MWh/year According to Towler and Sinnott (2008), for order of magnitude estimate; C2 = Cl x(S2/Si)n With typical n = 0.9 (For processes with considerable mechanical From E, = 2.6ixiO8 MWh/year/ 1.59x105 MWh/year (S2/Si) = 1.64xi o systems Therefore, C2 = £ 2.66x108 x (i.64x103)0.9 = £ 2.09x1011 (Similar calculation of CAPEX for AlgaeLink and Rentech) G) OPEX calculations example[Modified from Sinnott (2005)] CAPEX = £ 3.05x108 Fixed Costs i) Maintenance = 5% of CAPEX ii) Operating Labour = 5% of (i) iii) Laboratory Costs = 20% of (ii) iv) Supervision = 20% of (ii) v) Plant Overheads = 40% of (U) Variable Costs vi) Raw Materials = 1% of CAPEX (Estimate) vii) Utilities = nil (Power obtained from CSP) Total OPEX = 5%(CAPEX) + 5%[5%(CAPEX)] + 80%[5%[5%(CAPEX)]] + 1%(CAPEX) = 5% CAPEX + 0.25% CAPEX + 0.20% CAPEX + 1% CAPEX = 6.45% CAPEX = 6.45% x £ 3.05x1 08 =E1.97x10' H) Sensitivity Analysis AlgaeLink biomass yield = 36 tonnes/year Assuming uncertainty and CAPEX = £39,936/system, 60% 100% 140% Yield(tones/year) 21.6 36 50.4 Biomass 3000 3000 3000 Requirement (tones/year) No. of systems 139 83 60 req ui red (Max-min/2)/median% 48% (No. of systems 85 54 40 required)A0.9 (Max-min/2)/median% 42% CAPEX 3.39x106 2.14x106 1.58x106 (Max-min/2)/median% 42% References Abengoa Solar, 2011,[online]Available from: <http:/twww.abengoasolar. comlcorp/webten/technologies/photovoltaiclwhat_is_itt index.html>[Accessed March 28 2011] Aringhoff ef aL, 2005,[online]Available from: <http://www.greenpeace.org/internationallGlobal/international/planet- 2/report/2006/3/Concentrated-Solar-Thermal-Power.pdf>[Accessed March 31 2011] Bol, M.(Sales AlgaeLink),Pei-sonal Communication(201 1) Calleja, etal., 1980,Chemical Engineering Science,Vol. 36,l98l,pp919-929 Chisti, Y., 2007, Biotechnology Advances 25,pp294-306 Colquhoun, A.,Ortmans, L.,2010,[online]Available from:chttp://www.decc.gov. uktassets/decctstatistics/publications/trends/articles_i ssue/565-trendssepl 0-uk-refinery-output-article.pdf>[Accessed 18 May 2011] Corwin, M(Licensing Rentech),Personal Communication(2011) ExxonMobil, 2006,[online]Available from:<http://www.exxonmobil.com/NA-English/Files/2006_BRRF_Fact_Sheet.pdf> [Accessed 4 April 2011] Glennon, R., Reeves, AM., 2010,Arizona Journal of Environmental Law & Policy 1,91-137 Grobbelaar, J.U., 2008, J AppI Phycol 21,489-492 HamelincketaL,2003, Energy 29 (2004)1743-1771 helme, T., Harris, T., 2011,cmcl innovations-Internal report IEA,2010,Technology Roadmap:Solar Photovoltaic Energy[online]Available from: <www.iea.org/papers/201 0!pv_roadmap.pdf>[Accessed March 28 2011] I EA,20 1 0,Technology Roadmap:Concentrating Solar Power[online]Available from: <www.iea.org/papers/201 0/csp_roadmap.pdf>[Accessed March 28 2011] Kadam,K.L.,2001,[online]Available from: <http://www.fao.org/uploadslmedialOl06NREL- _Microalgae_production_from_power_plant_flue_gas.pdf>[Accessed March 29 2011] Krebs, S.,(Corporate Solar Millennium),Personal Communication(201 1) Kreutz, et aL, 2008,[online]Available from: <http://web.mit.edu/mitei/docs/reports/kreutz-fischer-tropsch.pdf> [Accessed 30 March 2011] NREL, 2011,[online]Available from: <http://www.nrel.gov/csp/solarpaces/project_detail.cfm/projectl D=3>[Accessed March 252011] Office for National Statistics, 2010,[onlinelAvailable from:chttp://www.statistics.gov.uk!STATBASE/ssdataset.asp?vlnk=4295&More Y> [Accessed 18 May 2011] Palanisamy, V., Latif, F.A., Resat, R.B.M., 1991, Department of Fisheries, Ministry of Agriculture, Malaysia,pp 23 Pfeifer etaL, 2009, Chemical Engineering Science 64 (2009),5073 -5083 Posten, C., Schaub, G., 2009, Journal of Biotechnology 142 (2009) 64-69 Sander, K., Murthy, G.S., 2010, Int J Life Cycle Assess 15,704-714 Sie, S. T., Krishna, R., 1999, Applied Catalysis A: General 186 (1999),55-70 Sinnott, R. K., 2005, Coulson & Richardon"s Chemical Engineering Design, Volume 6 4th Edition, Elsevier Butterworth-Heinemann, Oxford,260-270 Tijmensen, eta!. ,2002, Biomass and Bioenergy 23 (2002), 129 -152 Towler, G., Sinnott, R., 2008, Chemical Engineering Design, Butterworth-Heinemann, London,297-388 U.S DOE,2009, [online]Available from:<https:IIe-center.doe.gov/iips/faopor.nsf/UNI D/79E3ABCACC9AC1 4A852575CA00799099/ $file/AlgalBiofuels_Roadmap_7.pdf>[Accessed 19 March 20111 Uduman eta/.,2010,Journal of Renewable and Sustainable Energy 2, 012701(2010) Wang etaL,2009, Natural Science 1(2009)195-203 Warnecke, R., 2000, Biomass and Bioenergy 18(2000)489-49 Nomenclature C-FAST -Carbon Negative Fuels Derived from Algal and Solar Technologies Bbl -Barrel C5÷ -Hydrocarbon chain with more than 5 carbon molecules CAPEX -Capital Expenditure CGP -Chain Growth Probability CSP -Concentrating Solar Power FT -Fischer-Tropsch HTF -Heat Transfer Fluid MW -Megawatt MWh -Megawatt-hour NPV -Net Present Value OPEX -Operational Expenditure PV -Photovoltaics PBR -Photobioreactors TSS -Total Suspended Solids Vol%db -Volumetric percentage thy basis

Claims (1)

1. <claim-text>CLAIMS1. A method for producing hydrocarbon compounds, comprising: a) generating power using a renewable energy generator; b) cultivating, harvesting and drying algal biomass; and c) generating hydrocarbon compounds from the algal biomass, wherein step b) and/or step c) utilise the power generated by the renewable energy generator.</claim-text> <claim-text>2. A method according to claim 1, for generating biofuels.</claim-text> <claim-text>3. A method according to any preceding claim, for generating biodiesel, kerosene or naptha.</claim-text> <claim-text>4. A method according to any preceding claim, in which the renewable energy generator is a solar power system.</claim-text> <claim-text>5. A method according to claim 4, in which the solar power system is a concentrating solar power system (CSP).</claim-text> <claim-text>6. A method according to any preceding claim, in which step c) comprises subjecting the algal biomass to gasification and Fischer-Tropsch (FT) synthesis.</claim-text> <claim-text>7. A method according to claim 6, comprising subjecting a product of gasification to gas conditioning and acid gas removal.</claim-text> <claim-text>8. A method according to claim 6 or claim 7, comprising subjecting a product of FT synthesis to hydrocracking.</claim-text> <claim-text>9. A method according to any of claims ito 5, in which step c) comprises extracting algal oil from the algal biomass and subjecting the algal oil to transesterification.</claim-text> <claim-text>10. A method according to any preceding claim, in which the drying of the algal biomass is achieved using a solar dryer.</claim-text> <claim-text>11. A plant, for producing hydrocarbon compounds, comprising: a renewable energy generator; an algal biomass cultivator; an algal biomass harvester; an algal biomass dryer; and a means for generating hydrocarbon compounds from the algal biomass, in which the algal biomass cultivator, the algal biomass harvester, the algal biomass dryer and/or the means for generating hydrocarbon compounds are arranged to utilise power generated by the renewable energy generator.</claim-text> <claim-text>12. A plant according to claim 11, in which the renewal energy generator is a solar power system.</claim-text> <claim-text>13. A plant according to claim 12, in which the solar power system is a CSP.</claim-text> <claim-text>14. A plant according to any of claims 11 to 13, in which the algal biomass cultivator is an algae bioreactor.</claim-text> <claim-text>15. A plant according to any of claims 11 to 14, in which the means for generating hydrocarbon compounds comprises a gasifier for gasifying the cultivated algal biomass and a FT reactor for generating hydrocarbon products from the gasified cultivated algal biomass.</claim-text> <claim-text>16. A plant according to any of claims 11 to 15 in which the algal biomass dryer is a solar dryer.</claim-text> <claim-text>17. A plant according to any of claims 11 to 16, in which the renewable energy generator is arranged to supply electricity to an electricity grid.</claim-text> <claim-text>18. A plant according to any of claims 11 to 17, in which the renewable energy source is used to produce desalinated water, preferably by multi-effect desalination or reverse osmosis.</claim-text> <claim-text>19. A method substantially as hereinbefore described with reference to the drawings or figures.</claim-text> <claim-text>20. A method substantially as herein described with reference to the drawings or figures.</claim-text>