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Gasification of biomass and residues for electricityproductionFaaij, A.; Ree, van, R.; Waldheim, L.; Olsson, E.; Oudhuis, A.; Wijk, van, A.; Daey Ouwens,C.; Turkenburg, W.Published in:Biomass and Bioenergy

DOI:10.1016/S0961-9534(97)00010-X

Published: 01/01/1997

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Citation for published version (APA):Faaij, A., Ree, van, R., Waldheim, L., Olsson, E., Oudhuis, A., Wijk, van, A., ... Turkenburg, W. (1997).Gasification of biomass and residues for electricity production. Biomass and Bioenergy, 12(6), 387-407. DOI:10.1016/S0961-9534(97)00010-X

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~ Pergamon Biomass and Bioenergy Vol. 12, No. 6, pp. 387-4(17, 1997

1997 Published by Elsevier Science Ltd. All rights reserved Printed in Great Britain

P I h S0961-9534(97)00010-X 0961-9534/97 $17.00 + 0.00

G A S I F I C A T I O N O F B I O M A S S W A S T E S A N D R E S I D U E S

F O R E L E C T R I C I T Y P R O D U C T I O N

ANDRI~ FAAIJ*, RENI~ VAN REE~', LARS WALDHEIM~, EVA OLSSON~, ANDRI~ OUDHUIS"f, AD VAN WIJK*, CEES DAEY-OUWENSll AND WIM TURKENBURG*

*Department of Science Technology and Society, Utrecht University, Padualaan 14, NL-3584 CH, Utrecht, The Netherlands

tNetherlands Energy Research Foundation, P.O. Box l, NL-1755 ZG, Petten, The Netherlands ++Termiska Processer AB, S-61182, Nyk6ping, Sweden

IlProvince of Noord-Holland, P.O. Box 3088, 2001 DB~ Haarlem, The Netherlands

(Received 16 September 1996; revised 24 Januao~ 1997; accepted 31 Januao' 1997)

Abstract--The technical feasibility and the economic and environmental performance of atmospheric gasification of biomass wastes and residues integrated with a combined cycle for electricity production are investigated for Dutch conditions. The system selected for study is an atmospheric circulating fluidized bed gasifier-combined cycle (ACFBCC) plant based on the General Electric LM 2500 gas turbine and atmospheric gasification technology, including flue gas drying and low-temperature gas cleaning (similar to the Termiska Processer AB process). The performance of the system is assessed for clean wood, verge grass, organic domestic waste, demolition wood and a wood-sludge mixture as fuel input.

System calculations are performed with an ASPEN p~"' model. The composition of the fuel gas was derived by laboratory-scale fuel reactivity tests and subsequent model calculations. The net calculated efficiencies for electricity production are 35.440.3% (LHV) for the fuels studied, with potential for further improvement. Estimated investment costs, based on vendor quotes, for a fully commercial plant are 1500-2300 ECU per kWc installed.

Electricity production costs, including logistics and in some cases negative fuel price, vary between minus 6.7 and 8.5 ECUct/kWh. Negative fuel costs are obtained if current costs for waste treatment can serve as income to the facility. Environmental performance is expected to meet strict standards for waste incineration in the Netherlands. The system seems flexible enough to process a wide variety of fuels. The kWh costs are very sensitive to the system efficiency but only slightly sensitive to transport distance; this is an argument in favour of large power-scale plants. As a waste treatment option the concept seems very promising. There seem to be no fundamental technical and economic barriers that can hamper implementation of this technology. (~, 1997 Published by Elsevier Science Ltd

Keywords---atmospheric gasification; ASPEN'~°~; electricity production; biomass wastes and residues

1. INTRODUCTION At present, in the Netherlands various biomass wastes and residues are landfilled, incinerated, composted or digested. However, landfilling capacity is scarce and a ban on the landfilling of organic materials will be implemented in the short term. Composting gives rise to problems because supply exceeds demand)4 Furthermore, waste incineration combined with electricity production has low conversion efficiencies. This implies that the energy potential of biomass wastes and residues is poorly utilised.

However, biomass-fired integrated gasifier combined cycle (BIGCC) technology is a promising alternative for handling organic wastes. The potentially high efficiency corn-

pared with mass burning and the potentially low investment costs have been demonstrated in a number of ~tudies? ~0 This technology could therefore contribute significantly to the mitigation of CO2 emissions.

For BIGCC, Faaij et al. 6 and van Ree et al. ~ have made an inventory of potential technologies. A preliminary feasibility study for the Province of Noord-Holland has also been made. 6 This province, supported by utilities and the Netherlands Ministry of Economic Affairs, has taken the initiative to set up a BIGCC plant. This technology will also be implemented in other countries. In this connection the Global Environment Facility World Bank project in Brazil should be mentioned especially) 2

As a waste treatment system, BIGCC technology should be capable of meeting the

387

388 A. FAAIJ et al.

very strict emission standards for waste treatment in the Netherlands. It should also be flexible enough to deal with a variety of different biomass fuels. In addition the system should be robust, be competitive and involve a minimum of technical risks.

BIGCC units however have not yet been constructed on a commercial basis. Cost estimates vary, 8' ~3, ~4 but the general conclusion is that the first plants will be expensive. A partial solution that can be proposed is to compensate for the initial high investment costs by using biomass wastes or residues that are available at very low or even negative costs. A disadvantage is that this complicates the conversion facility because residues and wastes have different properties and a higher degree of contamination compared with clean wood, e.g. from energy farming. The properties of various biomass wastes and residues in the Netherlands are discussed elsewhere.-" ~5 A detailed system analysis and cost assessment are necessary to provide more insight into the prospects and performance of a BIGCC system, especially when it is utilised for a variety of biomass fuels. Such an analysis has been carried out for the Province of Noord-Holland and the results are presented in this paper.

2. SELECTION AND CHARACTERISTICS OF BIOMASS WASTES AND RESIDUES

The characteristics of various biomass wastes and residues have been reported elsewhere?' ~5 It was shown that the costs of fuels that are available for energy production differ widely, ranging from a negative value of - 10 up to a positive value of + 5 ECU/GJ. Possible biofuels were found to differ substantially with regard to (chemical) composition, moisture content and ash, concentrations of heavy metals and contents of nitrogen, sulfur and chlorine. It was concluded that in order to meet gas turbine constraints, the ash of the incoming fuel should not be > 10-20wt% of the dry matter content. A moisture content of --~ 70wt% (wet basis) was considered to be a maximum permissible value (for biomass of very low ash). Streams that exceed these limits have either to be treated by other conversion techniques or to be mixed with cleaner materials to meet the maximum permissible values.

The following fuels, representative of the wide variations in fuel characteristics (and prices) and

available in sufficient quantities, have been selected for this system analysis:

• Clean wood (forest thinnings): This stream represents a relatively large potential ( ~ 9 PJL,v/year), 2 but also has relatively high price per GJ. For this study the physical and composition data refer to poplar, which us considered to be representative of biomass residues from forest thinnings.

• Demolition wood: Demolition wood is currently available ( ~ 3 PJLnv/year) at low or negative costs. It is a drier fuel than thinnings.

• Verge grass and organic domestic waste (ODW): These streams have a negative value and will therefore reduce the electricity production costs. Both streams are available in large quantities, 2.1 and 5.3 PJLHv/year respect- ively. ODW could compensate for the absence of verge grass during winter months.

• Sludge: Sludge represents an energy value of about 4 PJL,v/year. Sludge is included in the analysis to illustrate the influence on the performance of a BIG/CL system when a contaminated fuel is used. High nitrogen, sulfur and heavy metal contents make sludge a very difficult fuel. Furthermore, the ash is too high when a GE LM2500 gas turbine is used, as shown in Faaij et al. 2 Consequently, sludge needs to be diluted by a cleaner material to reduce the average ash. For this purpose we select demolition wood.

Table 1 summarises the relevant parameters of the selected fuels. 2~5 Representative base values serve as input for the system calculations as well as for the gasifcation tests and gas composition calculations.

The composition of the fuel gas produced by the gasifier varies according to the fuel used. The gas compositions are derived from lab-scale fuel reactivity experiments and from subsequent separate gasifier model calculations. ~6 The results of this exercise for each selected fuel are given in Table 2. These results serve as input for further system modelling.

3. SYSTEM DESIGN AND PERFORMANCE

3.1. System selection and modelling

The selected gasification process is similar to Termiska Processer AB (TPS) technology, which makes use of an atmospheric circulating ftuidized bed (ACFB) gasifier followed by a separate CFB tar cracker. 4"17-19 The main

Gasification of biomass wastes and residues for electricity production 389

Table 1. Characteristics, availability and costs of five selected biomass fuels (derived from Faaij et al? and van Doorn ~5)

Clean Verge Organic domestic Demolition Fuel type woo& grass waste (ODW) wood Sludge Unit

Moisture' 50 60 54 20 20 b wt% of wet fuel Ash ~ 1.3 8.4 18.9 0.9 37.5 wt% of dry fuel LHV 7.7 5.4 6.4 13.9 8.8 MJ/kg a.r. (as-received) HHV 9.6 7.4 8.3 15.4 9.9 MJ/kg a.r. (as-received) Composition wt% dry,

ash-free (daf) C 49. I 48.7 51.9 48.4 52.5 H 6.0 6.4 6.7 5.2 7.2 O 44.3 42.5 38.7 45.2 30.3 N 0.48 1.9 2.2 0.15 7.0 S 0.01 0.14 0.50 0.03 2.7 CI 0.10 0.39 0.3 0.08 0.19

Availability in the Netherlands Gross 13 4 6 3 4 Net 9 4 3 2 4

Cost range Minimum 43 - 9 9 - 107 - 137 95 Maximum 50 11 - 46 - 11 - 38

PJu~v, year

ECU/t dry

"Thinnings from commercial forestry are selected. Composition data for poplar wood are presented. bThe moisture content of sludge from wastewater treatment plants is originally as high as 80-90wt%. After mechanical

dewatering and drying, the moisture content is decreased. 20wt% is taken here as a representative value?' ~The quoted moisture and ash figures are considered representative for the biomass fuels as recieved at the conversion

facility.

reasons for selecting this process with subsequent low-temperature gas cleaning are that it is expected to be able to deal with various biomass fuels with varying fuel properties and degrees of contamination. Moreover, all parts of the system have been proven commercially. There are however still some technical uncertainties, particularly with regard to the integration of various parts, such as the coupling of the gasifier to a gas turbine and a system-integrated dryer.L3 ~4

The gas turbine selected for this study is the General Electric LM 2500. This results in a system with a capacity of ~ 30 MW~. 2° Major arguments for selecting this turbine are that it is under development for low-CV gas applications as part of the G E F World Bank project in Brazil, '~ it is relatively small in size and it therefore requires a relatively modest quantity of fuel. Furthermore, a STIG version of this turbine (steam injected gas turbine) is available which allows larger differences in mass flows; this is necessary for operation on the low-CV gas produced by a direct gasifier. 2~ 24 Being an aeroderivative, this turbine combines a relatively high efficiency with a high turbine outlet temperature, which results in good conversion efficiencies of the combined-cycle plant. 22

The basic BIGCC design is shown in Fig. 1. After gasification of the biomass, the resulting

fuel gas is cracked in a tar cracker using dolomite as a catalyst. The gas is cooled and particulates and alkalis are removed by a baghouse filter. Remaining contaminants, mainly ammonia, are removed in a wet scrubber. Before combustion in the (modified) combustion chamber, the fuel gas is com- pressed. After steam production, the flue gas is led to a fuel gas dryer to dry wet fuels to required gasifier specifications. Table 3 summarises the main parameters of the selected system components. Data on these components have been derived partly from the literature, but more especially by consulting various suppliers. A more detailed description of the system configuration is given by van Ree e t a l . 2~

ASPEN r~°~ is used as a modelling tool for system calculations. With an ASPEN p~"~ model, mass flows, related emissions and the system performance have been calculated for various fuels. The gasification process itself is not modelled in ASPEN p~u~. The gasifier and tar cracker are modelled as a black box for which the input (parameters of incoming fuel) and output (calculated gas compositions on the basis of experiments) are known (see Table 2). The results of the calculations for each fuel are given in Table 4. Detailed descriptions of the process conditions are given in a background report. 25

390 A. FAAIJ et al.

Table 2. Fuel gas composition data for various biomass fuels, from fuel reactivity experiments and gasifier model calculations for each fuel (performed by TPS~6). These gas compositions serve as input data for ASPEN m~ modelling

20wt% Clean Verge Organic Demolition Sludge + 80wt% dem. wood grass domestic waste wood wood b Unit

Air Flow rate 1.40 1.48 1.6 1.26 1.41 kg/kg wet

fueP Temp. 400 400 400 400 400 °C

Dolomite Flow rate 0.0268 0.0279 0.0279 0.0257 0.0261 kg/kg wet

fuel LCV gas

Flow rate 2.37 2.40 2.42 2.27 2.30 kg/kg wet fuel

Temp. 900 900 900 900 900 °C Composition vol% wet gas

C2H6 0.02 0.02 0.02 0.02 0.02 C2H4 0.94 0.87 0.77 0.98 0.88 CH4 2.82 2.61 2.81 2.93 2.63 CO 17.22 14.94 13.98 18.31 15.18 CO2 12.22 12.09 11.80 11.67 12.22 H2 13.25 12.42 11.27 15.07 12.37 H20 13.55 14.49 13.71 13.85 14.34 N2 39.20 41.64 44.59 36.64 41.04 02 0.00 0.00 0.00 0.00 0.00 Ar 0.47 0.50 0.54 0.44 0.49 NH3 0.27 0.33 1.00 0.07 0.78 H2S 0.00 0.03 0.03 0.01 0.04 HCN ppm level HCI 0.03 0.07 0.00 0.02 0.01

Molar 24.86 24.99 25.28 24.28 25.75 kg/kmol mass Tar 12 11 I0 12 13 g/kg wet fuel residues Fly ash 0.036 0.083 0.152 0.032 0.045 kg/kg wet

fuel Ash 65 87 95 61 84 wt% of fly

ash LHV 5.22 4.74 4.39 5.59 4.82 MJ/m 3 (wet gas) c (s.t.p., wet) LHV 5.77 5.31 4.86 6.21 5.6 MJ/m 3 (at (30°C) d 30°C) Gasifier ash

Flow rate 0.0158 0.0158 0.0357 0.00t7 0.0785 kg/kg wet fuel

Ash 90 90 90 90 95 wt% gasifier ash

~Moisture contents of all input fuels to the gasifier are set at 15wt% to permit comparison of the required heat demand for drying. Consequences for resulting low heating values of the fuel gas (in case of verge grass and organic domestic waste) are discussed later.

bBoth dry, ash-free; mass fraction of the mixture determined by the minimal required heating value for the gas turbine. CHeating value of gas after tar cracker. dHeating value of gas after wet scrubber (water condensed at 30°C).

3.2. System efficiency

As shown in Table 4, the net overall energy conversion efficiency of the system (LHV basis) ranges from 35.4% for the wood-sludge mixture to 40.3% for clean wood. As expected, higher ash results in lower conversion efficiency. The same is found for fuels with a higher moisture content. In addition however, several remarks are needed on these results, as follows.

The calculated efficiencies are obtained for specific fuels and for system operation at a design point. In practice it might be that the dryer, feed system, gasifier, fuel gas compressor etc. would all have to be designed to specific boundary conditions, which could possibly result in a lower conversion efficiency.

For all the fuels, the heating values of the fuel gas, which serve as input for the calculations, exclude non-condensable tars, due to uncertainties in the measurements and

Gasi f ica t ion o f b iomass wastes and res idues for electrici ty p r o d u c t i o n 391

Biomass

~ Sizing and screening

A i ~ Solids

Gas . . . . . . . . . Water/steam cleaning . . . . . . Gas

. . . . . . . . . . . . .

Ash Gas coo~ing

. . . . . . . . . . . . . - - - - - t - ; - _ ; . . . . . . . . . /eal s l ; a m ' l

~ Steam " " - . . . . " " Generator ~ t u r b i n e

. . . . . . . . . . . . . . © . . . . . . . . . . . . . . . . . . . ,

Generator ~ ,, ', _ . . ] censor 1 , . . . . . .

~ Combuster - - "

Solids ~ . . . . . . . . . . . . . . . . . . . . Water/steam . . . . ] . . . . . . Gas Fuel gas compressor

Fig. 1. Scheme of the considered integrated direct atmospheric gasification combined cycle system based on TPS gasification technology.

Table 3. Technical data on system components, derived from the literature and specific information from manufacturers. More detailed information is given by Faaij et al. 34 and van Ree et al. "-5

Dryer: b Direct rotary drum dryer, 13.8 t/h water evaporation. Mass flows and temperatures for fuel of ~ 50wt% moisture: "dry" flue gas, 78 kg/s, 200C, 1.1 bar; "'wet" flue gas 81,5 kg/ s, 80C , 1.1 bar. '-5 Gasifier: ~ ACFB type TPS technology, 1.3 bar, 900C (depends on fuel), heat loss 2% of thermal input. Bed material: sand. Gasifier air: 1.3 bar, 400C. ~6 Tar cracker: CFB reactor using dolomite, 1.3 bar, 900C? 6 Fuel gas coolers: 900-140 C (Q ~ 14-15 MW~h depending on the fuel), pressure drop 0.1 bar. -'5 Dust filter: Baghouse filter, pressure drop 0.05 bar?-' Fuel gas scrubber: Spray tower using recirculating water; mass flow 73 kg/s, pressure 1.3 bar, temperature 25C, pressure drop 0,05 bar. 4~ Fuel gas compressor: multistage compressor with intercooling. Cooling duty 2.3 MW,h, isentropic eft. 0.78, mechanical eft. 0.998, pressure ratio Pm/P,,u~ + 33/1.1). -~544 Gas turbine: b General Electric LM 2500 (modified for LCV gas). Pressure drop over valves to inlet combustion chamber 10 bar, heat loss 2 MW~. Compressor mass flow: 65 kg/s, To~, 459'C, mass flow turbine blade cooling 7 kg/s, isentropic eft. 0.91 Combustion chamber: pressure 23 bar, mass flows and To,, depending on fuel type. Expander: Mass flow flue gas and T,, depending on the fuel type, inlet pressure 23 bar, isentropic eft. 0.89, outlet pressure flue gas 1.1 bar. Generator efficiency 0.99. 2°.2~,'-7

Ambient air: 15C, 1 bar, composition (vol%) 1.01 H_,O, 77.29 N2, 20.7 02, 0.03 CO2, 0.92 Ar. Heat recovery steam generator: c Superheater 1, 40 bar, 450C; superheater 2, 40 bar, 440-'C; air preheater for gasifier and tar cracker air, 400C; evaporator, 40 bar, 256C; economizer, 240C: minimum pinch air preheater (g/g), 15C; mimimum pinch (g/l), 20C; total pressure drop from feedwater to superheated steam, 4 bar. Mass flow of flue gas and steam produced depend on type of fuel. Steam conditions 450°C, 40 bar. Steam turbine: Two-stage partly condensing steam turbine; 40 bar, 450-C to 8.1 bar to 0.07 bar. lsentropic eft. 0.735, mechanical eft. 0.99, generator eft. 0.99 Steam-water cycle: Condenser 0.07 bar, using surface water; water pump eft. 0.82. Deaerator: 3.6 bar, minor steam consumption of 8.1 bar. Water pumps: pressures from 0.07 to 3.8 to 45 bar; eft. 0.99

~Mass flows of gasifier air, dolomite consumption and ash production for selected fuels are given in Table 2. bTemperatures of incoming and outgoing gas for dryer, combustion temperatures and gas turbine expander outlet

temperature depend on the type of fuel -'3 and are given with the results of the model calculations. ~Steam system defined in van Ree et al. 25

392 A. FAAIJ et al.

Table 4. Results of ASPEN p~"~ system calculations with various fuels

Clean Verge Organic Demolition Sludge~lemolition wood grass domestic waste wood wood mixture"

Fuel input (kg/s) 9.30 12.71 12 5.27 total: 6.65 Moisture (wt%) 50 60 54 20 20 Ash (wt% db) 1.32 9.8 18.9 0.9 av. 11.1 LHV (MJ/kg a.r.) b 7.7 5.4 5.9 13.9 8.4- 13.9 HHV (MJ/kg a.r.) b 9.6 7.4 7.8 15.4 10.0- 15.4 Dryer

Moisture after drying (wt%) 15 15 15 15 15 Flue gas dryer T,, - Tou~ (~C) 195 - 71 276 - 67 292 - I 17 179 - 165 179 - 165

Fuel gas LHV (M J/m3; 30'=C) 5.77 5.31 4.86 6.21 5.60 Flow (m3/s, s.t.p.) 10.55 11.46 12.50 9.79 10.87 E-input (MW) 60.85 60.85 60.75 60.80 60.87 Gas turbine expander inlet 1150 1136 1122 1160 1145 temperature (°C) Steam production (kg/s) 11.8 9.85 9.50 12 11.60

Energy balance Input: LHV (MW,h) 72.0 68.8 70.6 73.1 81.9 Input: HHV (MW,h) 89.6 94.2 93.2 81.2 92.3 Output: Gas turbine (MW0) 26.3 26.7 27.1 25.9 27.1

Steam turbine (MWe) 10.3 8.5 8.2 10.4 10.1 Gross (MWe) 36.6 35.2 35.3 36.3 37.2

Electricity consumption of system Dryer (MWJ 0.33 0.44 0.39 0.19 0.19 Fuel gas compressor (MW¢) 6.53 7.27 8.10 5.94 7.29 Gasifier air compressor (MW~) 0.22 0.24 0.28 0.21 0.24 Pumps (MWo) 0.43 0.43 0.43 0.43 0.43 Total (MWe) 7.51 8.38 9.20 7.01 8.15

Net output (MWo) 29.0 26.8 25.6 29.3 29.0 Net system efficiency (LHV 40.3 39.0 36.3 40.0 35.4 a.r.) b,c Net system efficiency (HHV 32.4 28,5 27.5 36.1 31.5 a.r.) b,c

"Ratio of sludge and demolition wood in mixture chosen as 20:80 w/w daf to give a fuel gas with a heating value of 5.6 MJ/m 3 (s.t.p.).

ba.r. implies fuel with moisture content as received at the gate of the facility. CGenerally the system efficiency decreases with increasing ash content of the fuel. This is mainly due to increased work

by the fuel gas compressor because the heating value of the fuel gas falls with increasing ash content; also the combustion temperature decreases with decreasing heating value of the fuel gas.

difficulties in extrapolating laboratory results to full-scale plant. It is therefore uncertain to what extent these tars (which are not removed during gas cleaning) actually appear in the gas. The tars could increase the heating value of the gas by 3-6%. ~6 Since this effect has not been taken into account in the calculations, the efficiencies presented are somewhat pessi- mistic. It should be kept in mind that a 6% increase in heating value of the gas could increase the net conversion efficiency by ~ 2 percentage points.

Another point is that the heat rate de- gradation of the gas turbine during its lifetime will have a negative influence on the efficiency. The turbine is maintained at regular intervals, whereupon the efficiency is restored to its original level. However, even with a normal maintenance schedule a 3-4% drop in efficiency of the gas turbine during its lifetime is observed. 26 This is partly compensated by

a higher expander outlet temperature, which permits increased steam production. Overall, the loss in efficiency will be ,,, 2-3%.

The drop in efficiency as calculated for verge grass and organic domestic waste (see Table 4) is due to the steam system selected. The higher heat demand for drying these wet fuels means that the maximum amount of steam produced and superheated is limited by the minimum pinch point of 15°C for preheating air in the heat recovery steam generator (HRSG). If the gasifier air temperature were lowered somewhat (e.g. 380°C instead of the 400°C chosen), the steam system would operate at the selected design conditions. Lowering the gasifier air temperature would also cause a slight decrease in the heating value of the ga's, but the influence of this decrease on the conversion efficiency is very limited. ~6 These parameters are not optimised in this project.

The limits of the system with regard to the


quality of the incoming biomass are ,-~ 10- 20wt% ash (for dry biomass) and a moisture content of ~ 70% (for biomass of low ash). More ash results in a leaner gas, which requires more compression work and lowers the combustion temperature of the gas turbine. Fuels that are too wet require so much waste heat for drying that steam production drops. Verge grass and especially organic domestic waste produce fuel gas with a heating value below the 5.6 MJ/m 3 (s.t.p.) required for the gas turbine. This problem could be solved by more extensive drying. Verge grass meets the required heating value already at a moisture content of 12wt% instead of the 15wt% taken as the starting point in Table 4. This will have very little influence on the overall efficiency, as steam production is only slightly decreased.

Concerning organic domestic waste, a moisture content of < 3wt% is required to produce a fuel gas with a heating value of 5.6 MJ/m 3 (s.t.p.). The required drying to achieve this will reduce the steam production drastically and might cause unacceptable emissions because the temperature in the dryer will rise and volatile fractions in the biomass might evaporate. However, there are several issues that must be kept in mind: non-condensable tars have been excluded, which could represent 3-6% additional heating value. Also, the required heating value of 5.6 MJ/m 3 might prove to be a conservative constraint. Lower heating values might be allowable with the LM 2500 and certainly with the use of specially developed combustion chambers. To make the processing of organic domestic waste feasible, one can also add wood of low ash (demolition wood). Another possible improvement option is heat recovery from the ash stream back to the gasifier, thus limiting heat losses and reducing the problem of maximum permissible ash. However, the costs of this option are not evaluated in this paper.

3.3. Environmental performance

The emissions after combustion have been investigated and compared with Dutch emission standards. First, Table 5 gives the standards for the required fuel gas quality for the LM 2500 gas turbine. The gas cleaning system will in any case have to meet these standards, to prevent excessive wear and corrosion of the gas turbine.

Table 6 shows the standards for gaseous emissions applicable in the Netherlands for

Table 5. Maximum permissible concentrations of contaminants in flue gas stream to GE LM 2500 turbine ~-'~

Component

Calculated Maximum maximum allowable allowable

concentration concentrations in flue gas to in a typical

expander biogas (ppbw)" (ppbw)

Solids < 10 lain 600 3000 10<d<13 lam 6 30 > 13 ~tm 0.6 3

Lead 20 100 Vanadium 10 50 Alkalis 4 20 (Na + K + Li) Calcium 40 200 Alkali metal 12 60 sulfates Chlorides 500 2500 Condensable tars - - 0.008 b

"Parts per billion by weight. These are the concentrations after combustion, so the permissible concentrations in the fuel gas are five times as high (values for operation on natural gas). Values in the second column are calculated from the first. When low-calorific-value gas is used. the dilution factor is ~ 6 7, depending somewhat on the composition of the biomass used.

hmg/m' at s.t.p.

waste incineration (the so-called BLA standards) and power generation. The first column shows the strictest set of emission standards and is considered to be applicable to a unit that uses biomass wastes and residues.

Dust. Dust emissions are determined by the limits set by the gas turbine and are thus very low. The dust concentration after combustion is lower than the emission constraint in the BLA; the baghouse filter and scrubber together are capable of meeting this constraint.

Hydrogen chloride. Up to 90% of HCI is removed in the tar cracker and the remaining part is bound to (lime) particulates at 140°C in the baghouse filter. ,Lassing et al. ~6 concluded that almost 100% HC1 will be removed. Any HCI that remains will dissolve in the scrubber. HCI emissions from the system will therefore be negligible.

Hydrocarbons, CO, PCDD and PCDF. Emissions of hydrocarbons, CO and polychlori- nated dibenzodioxins and dibenzofurans after combustion are determined completely by the specifications of the gas turbine. Because of the high temperature in the gasifier and reducing conditions before combustion in the turbine, these compounds are not formed. These specifications are such that all constraints stated in Table 5 are met when the gas turbine operates on natural gas. This is not expected to be

394 A. FAAIJ et al.

Table 6. Relevant emission standards for combustion of solid and gaseous fuels (mg/m 3 at s.t.p.)

Component BLA a BEES b

EU standards for stationary

coal-fired plants

Dust 5.0 HCI 10.0 HF 1.0 CO 50.0 Organic compounds (as C) 10.0 SO2 40.0 NO, 70.0 Total heavy metals 1.0 (Sb,Pb,Cu,Mn,V,Sn,As,Co,Ni,Te) Cd and compounds 0.05 Hg and compounds 0.05 Total PCDD and PCDF 0.1 ~

5 20

35 d 200' 100

aBesluit Luchtemissies Afvalverbranding (Decision on Air Emissions from Waste Incineration); represents emission standards for waste incineration in the Netherlands, at present the strictest in the world.

bBesluit Emissie-eisen Stookinstallaties Milieubeheer (Decision on Emission Regulations for Heat Installations); applicable to boilers of electricity production facilities.

CFor 90% S removal with flue gas desulfurisation. d(65 g/GJ x gas turbine eft.)/30 ~ng(l-TEQ)/m 3 at s.t.p.

different when the turb ine is fired with LCV gas. CO emissions however will be higher than for na tu ra l gas because o f the lower combus t ion tempera ture , but they will not exceed the above-men t ioned s t a n d a r d ? 7

Nitrogen oxides. There are two sources o f NOx; thermal NOx and combus t ion o f a m m o n i a present in the fuel gas. Wi th regard to thermal NOx, s ta te -of - the-ar t G E gas turbines have emission factors as low as 15 p p m v (with 15v01% oxygen in the flue gas). The lower combus t ion t empera tu re ob ta ined by using L C V gas ( ,~ 1150°C instead o f 1230°C) will reduce the thermal NOx fo rma t ion even be low that level. 26' 27

A m m o n i a is p roduced dur ing gasification. The NH3 concent ra t ions in the fuel gas given in Table 2 do not include the removal o f NH3 by dolomi te . F o r each b iomass s t ream the NH3

flOWS in the system are given in Table 7. Test results have shown that , depend ing on the n i t rogen conten t o f the fuel, N is only par t ly conver ted to NH3. Lassing et al. ~6 indicate that between 35% (Miscanthus, waste wood) and 80% (sludge) o f the n i t rogen in the fuel is not found as NH3 in the gas. Mechan i sms are not fully unde r s tood but a large f rac t ion is p r o b a b l y conver ted to molecu la r ni t rogen.

The permiss ible level o f NO,. emissions is 70 mg /m 3 (s.t.p.) (see Table 6). This s t anda rd will be exceeded by all fuels, as shown in Table 7, even when par t ia l convers ion to N2 is taken into account . The est imates o f the f rac t ion o f fuel N that is conver ted to N2 are also given. A m m o n i a dissolves well in water and can be removed f rom the fuel gas us ing a wet scrubber . The removal efficiency o f the scrubber needs to be ~ 80% (for organic domest ic waste) to meet

Table 7. NH3 flows, estimated molecular nitrogen formation and and NO~ formation without a scrubber. Volume flows are derived from the ASPEN p~°s calculations

Organic Clean Verge domestic Demolition Sludge-wood

Fuel wood grass waste wood mixture

Wet gas flow (ma/s at s.t.p.) 10.55 11.46 12.5 9.79 11.49 NH3 (vol% fuel gas) 0.27 0.33 1 0.07 0.78 Estimated N2 formation from fueI-N (%) 50 50 80 35 75 NH3 flow through scrubber (kg/h) 40 55 72 12 62 NO~ without removal (mg/m ~ at s.t.p.) 729 905 2651 190 2025

Gasification of biomass wastes and residues for electricity production

Table 8. H2S flow in fuel gas and corresponding NaOH consumption for 100% S removal

395

Organic Clean Verge domestic Demolition Sludge-wood

Fuel wood grass waste wood mixture

Mass flow of H2S in fuel gas (g/s) 0.55 3.57 3.94 1.64 3.57 Corresponding NaOH consumption (kg/h) 2.31 15.08 16.64 6.92 15.08

the NO, standard. The efficiency can be increased by increasing the water flow or even by adding an acid (such as H2SO4) to the scrubber water. Discharge of the scrubber water to the (aerobic) wastewater treatment system for conversion to nitrate can be considered, but the costs involved are very high.* In this study it is assumed that ammonia is stripped from the scrubber water and removed. Ammonia can possibly be used as a fertiliser.

To some extent ammonia will interact with thermal NO, in the combustion chamber and reduce NOv emissions by the formation of molecular nitrogen. The degree of this interaction is not known.

SulJur dioxide. SO2 emission levels will depend on the concentration of sulfur in the fuel and on the efficiency of removal in various gas cleaning stages. The sulfur contents of the fuel and the fuel gas (H2S) differ widely, as shown in Table 2. Part of this sulfur will react with lime in the cracker to form CaS. When the sulfur content exceeds 0.1wt% of dry matter in the biomass, chemical equilibrium is reached in the gasifier, which leads to an H2S concentration of ~ 200-300 ppmv in the fuel gas) 6 This equilibrium state is reached for sludge, verge grass and organic domestic waste, leading to an SO2 concentration in the flue gas of

100 mg/m ~ (s.t.p.), which exceeds the limit of 40 mg/m ~, so measures have to be taken.

H,S dissolves very poorly in water. Adding a base (NaOH) to the water stream will convert H_~S to Na_,S, which dissolves well in water. Depending on the standards for surface water near the plant, the wastewater stream may or may not be discharged directly to the surface water. In the latter case, costs of operation will increase as a result of wastewater treatment at central facilities. It is also possible to

*Costs are determined by the oxygen demand in aerobic wastewater treatment plants; they amount to 0.47 ECU/kg O_,. which is typical for Dutch conditions. Ammonia is converted to nitrate in wastewater treatment plants, giving an oxygen consumption of 4.57 g O,/g N. 2~ This will lead to wastewater treatment costs of ~ 106 ECU/year for organic domestic waste and for a plant operating for 7400 h per year at full load.

precipitate Na2S, which produces a removable solid salt.

In this study it is assumed that all H2S is removed by sodium hydroxide in a wet scrubber. Table 8 shows the H2S concentrations in the fuel gas for the selected fuels. For verge grass, organic domestic waste and the wood-sludge mixture a concentration of 200 ppmv is assumed? 6 For demolition wood and thinnings it is assumed that 70% of the sulfur in the fuel is bound to lime. The related NaOH consumption (for 100% reaction of H2S to Na + and S 2-) is also given. It is assumed that Na2S is removed from the scrubber as a solid salt.

Heavy metals. These will evaporate partly in the gasifier, most probably to a far greater extent than would happen under combustion conditions. The reducing atmosphere will prevent oxidation of the metals, allowing more evaporation in metallic form. Cooling will condense the metals. All condensation temperatures exceed 140~=C, which is the temperature to which the gas is cooled before it is passed through the baghouse filter. At the time of writing, no experimental data are available on the behaviour of heavy metals under gasification conditions, but it seems likely that all metals will condense during gas cooling. '-9 Possibly some remaining metals will be washed out in the scrubber.

The gasifier ash and the fly ash will contain the heavy metals that, were present in the fuels. The distribution of the various metals will depend on the gasification temperature and the type of fuel. Volatile metals (lead, cadmium, mercury) will concentrate in the fly ash since they evaporate to a greater extent and condense during gas cooling. 3°

Fluoride. No analysis was made of the emission of fluorides, but the figures available for the fluoride content of demolition wood ( < 0'00003 wt% dry matter 3') are extremely low.

The most important unknown factor in the emissions is the flue gas dryer. The flue gas entering the dryer at ~ 200c'C will cause organic compounds to evaporate and will

396 A. FAAIJ et al.

lead to the formation of dust in the dryer. To reduce dust emissions the flue gas will be passed through cyclones (standard equipment for such dryers). The level of hydrocarbon emissions is unknown; possibly additional filters or water scrubbers will be required to meet emission standards.

Another option is to use a steam dryer, which has no effect on the system efficiency 25 but dries the fuel indirectly, thus preventing emission of dust and hydrocarbons. The main disadvantage of steam drying is that investment costs will increase. In addition, more wastewater will be produced (although this can be led to a central wastewater treatment facility). In this study we consider the conventional rotary dryer, taking investment costs for filters into account.

Emissions will also arise from storage (odour) and from the wet scrubber (wastewater). As already discussed, the scrubber water will contain ammonia, which is the main contami- nant. The presence of other compounds and possibly metals will depend on the fuel, although the foregoing gas cleaning steps in principle remove tars, dust and metals. Exper- imental data on this issue are lacking at the moment.

The ash stream from the gasifier and the baghouse filter is another emission from the system. Ash from clean wood such as thinnings could be used as fertiliser, although this will depend on specific standards applicable. Contaminated fuels (e.g. waste wood and sludge) will produce ash that has to be land filled.

A BIGCC system capable of converting a wide variety of fuels needs to be equipped with a two-stage scrubber with two absorption units (one with water or acid for ammonia removal and the other with an alkali for sulfur removal). This will increase investment costs and, depending on the fuel, lead to the consumption of NaOH (and H2SO4).

The extent to which sulfur is bound to dolomite and the degree to which fuel nitrogen is converted to molecular nitrogen have to be investigated in more detail in relation to gasification conditions and dolomite quality. However, the behaviour of the tar cracker is very promising in these, respects? 2

With the proposed gas cleaning concept, the BIGCC system seems to be capable of meeting the severe emission standards for waste incineration.

4. COST ANALYSIS*

In this section the electricity production costs are calculated and discussed for the different biofuels. Investment costs, operating and maintenance costs and logistics costs for collection and transport of the fuel are presented as minimum and maximum electricity production or waste treatment costs. The discounting method used is based on annuity.

4.1. Inves tment costs

The investment costs were mainly determined by consulting manufacturers of various system components. Where possible, cost figures are presented in ranges so that uncertainties can be visualized. Total investment costs are determined by summing the lowest cost per system component and lowest engineering costs for the minimum-cost case and summing the highest component costs and highest engineering costs for the maximum-cost case. A first plant will involve high engineering costs. After a number of plants have been built, engineering costs are expected to drop. j2 The high-cost case should therefore reasonably represent the costs of a first commercial plant, the low-cost case the costs of a plant after a number of similar (identical) plants have been built. However, the costs of a first unit may well lie above the maximum cost level given here, owing to uncertainties in the performance, required testing programmes and potential higher costs because of specified guarantees which are a crucial aspect for a new system.

Vendor quotes are used for all system components, except the gasifier and tar cracker, because only a small number of these components have been realized hitherto. For the gasifier, expert opinions are used to estimate the costs of a gasifier based on the TPS concept. With additional information abou t the size, materials used and process conditions of an existing similar gasifier (in Greve, Italy) a cost estimate is made using known factors for steel and cement processing for comparable process equipment such as hot-blast furnaces. The investment costs of the tar cracker are assumed to be the same as those of the gasifier since the design and size are also similar. The uncertainties of such exercises are large but exclude the engineering and development costs.

Other relevant cost factors such as civil works, control systems and interest during

Tab

le 9

. C

osts

of

syst

em c

om

po

nen

ts

Co

mp

on

ent

cost

s (1

0 ~ E

CU

)

Min

M

ax

Per

cent

age

of

inve

stm

ent

cost

s

Min

M

ax

Exp

lana

tory

not

es

Pre

trea

tmen

t C

onve

yors

0.

26

0.26

0.

6 G

rind

ing

0.3

0.3

0.7

Sto

rage

0.

74

0.7

41.7

D

ryer

3.

5 5.

6 7.

8 G

asif

icat

ion

syst

em

Gas

ifie

r 1.

4 2.

3 3.

1

Tar

cra

cker

1.

4 2.

3 3.

1 C

yclo

nes

0.9

1.9

2.1

Fue

l fe

edin

g 0.

3 0.

3 0.

6 G

as c

lean

ing

Gas

coo

ling

2.

1 2.

1 4.

8 B

agho

use

filt

er

1,2

1.2

2.6

Con

dens

ing

scru

bber

0.

9 1.

9 2.

I

Com

pres

sor

1.4

1.9

3.1

Com

bine

d cy

cle

Gas

tur

bine

9.

3 11

,6

20.8

M

odif

icat

ions

LC

V

0,5

0.9

1.0

gas

HR

SG

2.

4 2.

4 5.

4 S

team

tur

bine

+

3,2

3.2

7.2

cond

ense

r W

ater

+

stea

m

0.3

0.3

0,6

syst

em

Coo

ling

0.

3 0.

3 0,

6 O

vera

ll

Con

trol

sys

tem

s 4.

7 2.

3 10

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il w

orks

3.

5 4.

2 7.

9 E

lect

rica

l sy

stem

2.

8 3.

4 6.

3 B

uild

ings

0.

3 0.

3 0.

7 E

ngin

eeri

ng (

3-4%

I.

1

1.7

2.4

of t

otal

inv

estm

ent

cost

s)

Pro

ject

con

ting

ency

--

5+

1 --

In

tere

st d

urin

g 0.

4 0.

8 1.

0 co

nstr

ucti

on

I st

year

Id

em 2

nd y

ear

1.3

2.3

2.9

Tot

al i

nves

tmen

t co

sts

44.6

59

.7

0.4

0.5

1.3

9.3

3.9

3.9

3.1

0.5

3.6

2.0

3.1

3.t

19.5

1.

6

4.1

5.4

0.4

0.5

3.9

7.0

5.6

0.5

2.8

8.6

1.3

3.9

Ass

um

ing

tot

al

100

m

of c

onve

yors

is

requ

ired

on

the

terr

ain.

Cos

t fi

gure

s fr

om +5

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ost

figu

res

from

""

Ass

umin

g st

orag

e ca

paci

ty i

s su

ffÉ

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t fo

r 5

days

ful

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ad o

pera

tion

. C

ost

figu

res

from

'~

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t ra

nge

take

n fr

om 4~

(a

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)

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t es

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f li

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and

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el,

eval

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d w

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furn

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ific

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n pl

ant

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aly 4

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vest

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t co

sts

assu

med

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e as

tho

se o

f ga

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beca

use

of s

imil

ar s

ize,

des

ign

and

proc

ess

cond

itio

ns

Cos

t es

tim

ate

for

four

cyc

lone

s w

ith

sam

e li

ning

as

gasi

fier

and

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cra

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wo

doub

le-s

crew

fee

ders

wit

h ro

tary

val

ves

requ

ired

. C

ost

figu

res

from

46

Cos

t fi

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s fr

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for

a s

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e or

tw

o-st

age

scru

bber

. In

vest

men

t co

sts

for

wet

gas

cle

anin

g ar

e in

crea

sed

by

10 +

EC

U w

hen

addi

tion

al

mea

sure

s ar

e re

quir

ed

to r

emov

e la

rge

quan

titi

es o

f su

lfur

and

nit

roge

n. 4~

C

ost

figu

res

from

44

Cos

t fi

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s fo

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e co

mbi

ned

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d co

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ents

fro

m -'~

-'+'

ST

IG

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ion

LM

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00 i

nclu

ding

gen

erat

or

Add

itio

nal

cost

s fo

r ad

apta

tion

s to

L

CV

gas

HR

SG

fo

r m

odes

t st

eam

con

diti

ons

of 4

0 ba

r

Pre

senc

e of

sur

face

wat

er i

s as

sum

ed,

no c

ooli

ng t

ower

req

uire

d

Deg

ree

of a

uto

mat

ion

det

erm

ines

cos

ts o

f co

ntro

l sy

stem

. F

or a

com

bine

d cy

cle

alon

e, 0

.5

9 x

l0 +

EC

U

is

poss

ible

= '~ T

he r

ange

giv

en h

ere

is a

n as

sum

ptio

n. M

ore

exte

nsiv

e co

ntro

l im

plie

s fe

wer

ope

rati

ng p

erso

nnel

, w

hich

is

why

low

er c

osts

are

giv

en f

or t

he m

axim

um

-co

st c

ase.

P

erce

ntag

e of

tot

al i

nves

tmen

ts ~°

P

erce

ntag

e of

tot

al i

nves

tmen

ts"

Ass

um

ing

tha

t an

off

ice,

lab

orat

ory

and

port

ers'

bui

ldin

g ar

e re

quir

ed.

Bas

ed o

n 45

E

ngin

eeri

ng c

osts

at

leve

l fo

r el

ectr

icit

y ge

nera

tion

pla

nts,

ass

um

ing

kno

wn

tech

nolo

gy i

s us

ed 4"

Pro

ject

con

ting

ency

is

incl

uded

onl

y in

the

hig

h co

st c

stim

ate;

10

%

of

inve

stm

ents

E

xpec

ted

cons

truc

tion

tim

e 2

year

s; i

nves

tmen

t in

fir

st y

ear

25%

of

tot

al

Inve

stm

ent

in s

econ

d ye

ar 7

5%

of t

otal

ran

O

O

O

~z

3 ~

,.-,g

B

O

398 A. FAAIJ et al.

Project contingency (8 .6%) Pre-treatment

Building interes ~ (11.9%) (5.2 % ~ ~ / ~ ~ ~ s f f i c a t i o n ( l 1.3%)system

~ 1 ~ ~ G a s cleaning Control (8.6%) systems / ~

(3.9%) ~ ~ Compressor 7 (3.1%)

Combined cycle (31.3%)

Fig. 2. Breakdown of investment costs (high-cost case) for the selected ACFB-CC system based on the GE LM 2500 as obtained in this study. Total investment costs amount to 60 million ECUI~9 4. "Overall"

covers civil works, engineering, buildings and piping.

construction are obtained from cost data of comparable installations.

The investment costs of the system components are given in Table 9. Where possible, ranges are given. Figure 2 presents the breakdown of investment costs for the high-cost case (clean wood as fuel). In this case a substantial project contingency is included, which is expected to be unnecessary in the low-cost case, where it is assumed that a number have been built already. The total investment costs range from 45 to 60 million ECU.

The gasifier and cracker do not dominate the overall investment costs; they represent 9-12% of the total. The combined-cycle unit, which represents one-third of the investment costs, is the major component. The entire pretreatment system is also a significant cost factor (10-12% of total investment), although uncertainties here are large, However, when only one type of biofuel is used, the pretreatment could remain relatively straightforward. However, when a variety of very different fuels is to be used, different feeding lines might be required which will increase investment costs. In particular, densification or even pelletising equipment that might be required for a fuel such as verge grass would raise the pretreatment costs.* Costs

*Pelletising is an expensive pretreatment option. Feenstra et al. 33 report pelletising costs of ~ 8 ECU/t when done at the conversion facility itself. This excludes drying. Just pelletising (excluding drying) of wood and other biomass residues in a separate facility (20-40 kt/year capacity) costs

15 ECU/ t . 34 However, densification may well be sufficient for feeding fluffy biomass material to a gasifier operating at near atmospheric pressure. Such feeding would also be favoured from the energy point of view, since pelletising requires substantial electricity and heat inputs. More practical experience with fluff feeding of fuels such as verge grass and organic wastes is desirable.

might also increase because of the need for additional equipment attached to the dryer to prevent the emission of dust and odour, although the investment costs of the dryer already include various filters.

The costs of land and possibly of additional infrastructure are not taken into account. These factors depend strongly on the exact location of a conversion unit.

4.2. O p e r a t i n g cos t s

The costs of operation include personnel, maintenance and insurance. Variable costs relating to the operation of the plant are those of the catalyst (dolomite) and of ash disposal, which can both be derived from the gas composition data in Table 2. Water use and costs of wastewater treatment and additives are included when necessary. Relevant cost figures for the operation of the plant are given in Table 10. Figure 3 presents the annual operating costs for each fuel, assuming baseload operation (75% load factor in the maximum-cost case and 85% in the minimum-cost case).

It is assumed that NH3 and sulfur can be removed by several wet scrubbing steps. Although additional investment costs for extensive scrubbing are included in the economic evaluation, a more detailed study of this component is desirable.

4.3. L o g i s t i c s

The results of a logistic study of the supply of biomass waste streams for a BIGCC unit in the Province of Noord-Hol land are used) 3 To calculate the costs of the fuel, including transport, a number of assumptions were made regarding average transportation distances, location of the conversion facility, source

Gasification of biomass wastes and residues for electricity production

Table 10. Operating costs (input parameters for Dutch conditions)

399

Cost category Costs Description, assumptions and sources

Maintenance 2% of investment Personnel 32 500 ECU per

person-year

Water 0.37-1.4 ECU/m '

Dolomite

Ash disposal

NaOH

Insurance

27.9 ECU/t

46.5 ECU/t

1302 ECU/t

1% of annual depreciation

2% of investment. Assumption based on normal operation of power plants? ~ 5 crews of 2-4 persons for shift work; 4 persons other activities. With a more advanced control system, fewer personnel are required.

Water consumption expected to be minimal. The steam system is a condensing system and the waste water stream from the scrubber is expected to equal the condensed water from the fuel gas. 45

Dolomite consumption per stream is given in ~6

Ash disposal costs will vary with location and degree of contamination. Tariffs for landfilling will be increased to the level of waste incineration (116 ECU/)? 9

Cost figure for bulk quantities of solid NaOHY '

Data from composting and digestion plants) ~

location of the fuel, supply patterns of fuels and type of transport. Other relevant aspects taken into account are drying during storage, costs and capacity of storage and pretreatment (chipping or pelletising) of fuel before it reaches the conversion facility. These data have been calculated for a number of potential fuels (thinnings, prunings, demolition wood, waste paper and sludge). To determine the average transportation distances, several locations for the BIGCC system and various source locations were selected. In general these distances are substantial (75 km one way for thinnings, which covers a large part of the Netherlands). In general it is concluded that transport by road, central storage and pretreatment (at the conversion facility) is the cheapest route. Here, the minimum-cost scenarios for transport, storage and pretreatment are used for further calculations. For the collection and transport costs of organic domestic waste and verge grass, other sources are u s e d . 3'35"36

Table 11 summarizes the minimum-cost scenarios for logistics for the selected fuels. Pretreatment of waste before it reaches the central facility is logically possiblC 7, but in all cases central pretreatment is cheaper, and costs of chipping and drying are therefore included in the conversion costs.

4.4. Cost of electricity and waste treatment

The calculated minimum and maximum costs of electricity and waste treatment, based on the real interest rates, lifetime, load factor and construction time in Table 12 are presented in Table 13. The minimum-cost scenarios are the cases in which all parameters (investments, fuel

costs, costs of logistics, load factor etc.) are the lowest. In the maximum-cost cases, all parameters result in the highest costs. For verge grass, organic domestic waste and the sludge- wood mixture, additional investments are included to cover a more extensive scrubbing unit.

Figure 4 shows the breakdown of (annual) electricity production costs into capital cost, operating and maintenance cost, fuel cost and logistics. For thinnings the fuel costs represent half the electricity production costs. All other fuels in the minimum-cost case show that strongly negative costs of biomass wastes compensate all other costs. Figure 5 shows the electricity production costs in ECU/kWh assuming that the negative value of the fuel (that represents waste treatment costs) serves as income to the plant. This leads to wide ranges in, and potentially negative, electricity production costs.

The costs of electricity (COE) cover a wide range, namely from minus 6.7 up to plus 8.6 ECUct/kWh. When the fuel costs are set at zero, electricity costs are 2.9-4.8 ECUct/ kWh, compared with 4 ECUct/kWh for average Dutch electricity production in 1994. 38

Figs 6 and 7 show the sensitivity of the electricity production costs to variation in various parameters. The best way of reducing the COE is to increase the system efficiency. An increase in efficiency to 50% will bring the COE down by 25%. Such an improvement is possible with improved system integration and gas turbines (possibly with intercooling). A high load factor (and high reliability) is crucial for obtaining low electricity production costs.

400 A. FAAIJ et al.

c- O

e ~ O

4000000

3000000

2000000

1 0 0 0 0 0 0

l

0 ~1_ 1 l_ m i n max min

• Maintenance [ ]

[ ] Ash disposal [ ]

12 max min max

Personel

I

l , y'r

N

i = i2 min max rain max

[ ] Dolomite consumption

NaOH consumption • Insurance

Fig. 3. Breakdown of calculated minimum and maximum operating and maintenance costs of electricity production with the selected ACFB-CC system as a function of the fuel. Differences are caused particularly by ash disposal costs, which for thinnings can be zero when the ash is used as fertilizer,

although this is not shown in the graph.

Another important outcome is the low sensitivity of kWh costs to the transportation distance. Selected scenarios for various fuels already include substantial transport distances, but even when biomass is transported from all over the Netherlands (100 km diameter) the kWh costs are only modestly affected. The COE are obviously dominated by the fuel costs.

Waste treatment costs are calculated by considering the value of electricity produced by the plant. Reimbursement levels for decentrally produced power are 2.42 ECUct per kWh produced and 98 ECU per kW installed per year

in the Netherlands. 39'4° The results for waste treatment are given in Table 13, although for thinnings this stream should not be seen as waste. In several cases the reimbursements paid for decentralised power production in the Netherlands, which thus serve as income to the facility, outweigh the costs of the plant operation. This results in negative waste treatment costs for all minimum-cost cases.

The waste treatment costs (and efficiency) are compared with other state-of-the-art waste treatment options for organic waste in Table 14. From the point of view of both efficiency and

Table I 1. Minimum cost scenarios for logistics (all transport by road and all pretreatment centralized at the gasification plant)

Demolition Thinnings" Verge grass ODW ¢ wood b Sludge

Assumed moisture content (wt%) d 50 60 54 15 20 Density (t/m 3 db) 0.15 0.16 0.5 0.213 0.56 Average transport distance (km) (two-way) 150 30-50 89 58 Transport costs (ECU/t wet) ¢ 5.44 4.65-9.30 6.97-11.62 3.22 2.11 Transfer & storage costs (ECU/t wet) f 0.29 0.32 0.22 0.63 0.23 Total costs of logistics 5.73 4.97-9.62 7.19-11.84 3.85 2.34

~Thinnings are expected to be delivered as chips. Partial storage at lower landing (in the forest) is assumed. bWaste wood is expected to be delivered in shredded form. Costs of shredding are already included in the fuel costs

(presented in Table 1). The material is supplied by specialized companies? -'.53 q~ransport costs for ODW are relatively high since they include the collection of waste in residential areas and the high

moisture content 36. Also for verge grass the costs are relatively high because of high moisture content and inclusion of hauling costs (mowing). 3.3~

dMoisture content assumed for transport costs. Especially for sludge and verge grass the moisture content can vary considerably.

'Road transport is in all cases more economic. Specific data for road transport in the Netherlands: for a capacity of 25 t or 80 m 3 the costs are 0.91 ECU/km with an average speed of 50 km/h. 33

fTransfer costs are 0A6 ECU/m 3 (capacity 170 m3/h) for a shovel and 0.11 ECU/m 3 (capacity 275 m3/h) for a crane. 33 One transfer is assumed for all fuels.

Gasification of biomass wastes and

Table 12. General economic parameters and assumptions used in this study

Minimum-cost Maximum-cost case case

Real interest rate (%) 4 6 Expected lifetime of plant

(years) 25 20 Load factor 0.85" 0.75 h Construction time (years) 2 2

"7400 h h6750 h

costs, gasification appears favourable compared with the main alternatives currently available.

5. DISCUSSION

The main arguments for selecting the GE LM 2500 and an ACFB gasification process were that the BIGCC system could be constructed in the near future and the system should be flexible enough to treat various biomass residues and wastes. This fixes the scale of the system and excludes other (pressurized and indirect) gasification processes. In the longer term, other systems should be considered as well, especially systems that are used for clean fuels only or for the production of methanol and hydrogen.

The modelling has been performed relatively statically. For example, the behaviour of the gas turbine (combustion temperature, mass flows, behaviour in part-load conditions and operation on LCV gas below 5.6 MJ/m 3) is dealt with relatively simply. However, more elaborate dynamic modelling is not useful at this stage, because further experimental data first need to be collected. Dynamic aspects of the system, such as behaviour with fluctuating fuel gas composition and heating value, have to be investigated by testing, e.g. on the pilot scale. A related issue is the extent to which the dryer can produce biomass with a constant moisture content and can be regulated to respond to fluctuations in the compostion (moisture and ash) of the biomass delivered. There is also the (slight) risk of dust explosion under certain conditions. Drying with flue gas is selected here since it seems to be the cheapest and simplest way to reduce the moisture content of biomass fuels. However, steam drying can provide a good (though somewhat more expensive) alternative when flue gas drying meets problems.

Further improvements in the system investigated are possible. One-shaft arrangement, a modified turbine combustion chamber and

residues for electricity production 401

expander inlet, allowing higher combustion temperatures, higher steam temperatures and pressures, and especially scale-up are the main options to obtain higher efficiency and lower costs per kWh. Further system integration can lead to a better use of the available waste heat. In the longer term, intercooling of the gas turbine compressor can be an interesting improvement option. The constraints on ash and moisture might be relaxed to some extent by further system improvements. These improvements include heat recovery from the gasifier ash, allowing higher-ash fuels, use of various waste heat sources for fuel drying that reduce waste-heat requirements from the flue gas and especially modified combustor design that could allow fuel gas with lower heating values.

From an environmental point of view the flue gas dryer is the most uncertain factor. Dust emissions can be controlled by using cyclones. Emission of hydrocarbons and possibly ammonia and other compounds might be too high unless precautions are taken. Experimental data are needed so that the emission levels for drying can be confirmed. Additional filters (for reducing dust and odour) might be necessary. Steam drying can also be considered, for it will hardly influence system efficiency, although it will increase the investment costs to a limited extent. 2•

Investment costs are mainly based on vendor quotes. Uncertainties are included by present- ing cost ranges and differences in engineering costs. The high-cost estimate (2300 ECU/kW, for the most contaminated fuel) seems representative for a first fully commercial plant. The low-cost figure (1500 ECU/kW) is an estimate of the obtainable cost level after a number of identical plants with this capacity (30 MWe) have been constructed. For comparison: Elliott and Booth t2 suggest a cost level of 3000 U$/kWo installed (2230 ECU/kW) for a first BIGCC (25 MWe), potentially falling to 1300 U$/kWo installed (970 ECU/kW0) for the tenth identical plant.

Not only lower investment costs but especially a further increase in efficiency will have a significant influence on the costs per installed kWe. The low-cost estimate presented should therefore not be seen as the cost level for the longer term. To obtain insight into such figures, further study on long-term developments of system components and further system integration as discussed above is required.

Tab

le 1

3.

Res

ults

for

the

sel

ecte

d fu

els.

Out

com

es a

re p

rese

nted

in

rang

es b

ased

on

the

unce

rtai

ntie

s (r

ange

s) a

bout

inv

estm

ent c

osts

, ra

nges

of

(neg

ativ

e) f

uel

cost

s, t

rans

port

and

oth

er p

aram

eter

s .~

Thi

nnin

gs

Ver

ge g

rass

O

DW

D

emol

itio

n w

ood

Slu

dge

and

Wo

od

mix

ture

Min

M

ax

Min

M

ax

Min

M

ax

Min

M

ax

Min

M

ax

Bio

mas

s fu

el

Fue

l co

st (

EC

U/w

et t

on)

27.9

32

.6

-60

.5

7.0

-65

.1

-27

.9

- 11

6.3

-9.3

-

109.

7 -

16.8

M

oist

ure

cont

ent

(w.b

.)

50

50

60

60

54

54

20

20

20

20

Ash

con

tent

(d.

b.)

1.32

1.

32

9 9

18.9

18

.9

0.9

0.9

8.2

8.2

LH

V (

GJ/

wet

ton

) 7.

74

7.74

5.

41

5.41

5.

88

5.88

13

.86

13.8

6 12

.3

12.3

T

otal

cos

t of

logi

stic

s (E

CU

/wet

tun

) 5.

73

5.73

4.

97

9.62

7.

19

11.8

4 3.

85

3.85

3.

42

3.42

Syst

em p

aram

eter

s L

HV

eff

icie

ncy

(%)

40.3

40

.3

39.0

39

.0

36.3

36

.3

40.1

40

. I

35.4

35

.4

Fue

l in

put

(wet

ton

/hou

r)

33.5

33

.5

45.8

45

.8

43.2

43

.2

19.0

19

.0

23.9

23

.9

Fue

l in

put

(MW

,h)

72.0

72

.0

68.8

68

.8

70.6

70

.6

73.1

73

.1

81.9

81

.9

Net

pow

er o

utpu

t (M

Wo)

29

.0

29.0

26

.8

26.8

25

.6

25.6

29

.3

29.3

29

.0

29.0

D

olom

ite

cons

umpt

ion

(ton

/hou

r)

1.13

I.

13

0.90

0.

90

1,07

1.

07

1.77

1.

77

2.01

2.

01

Tot

al a

sh p

rodu

ctio

n (t

on/h

our)

1.

4 1.

4 2.

6 2.

6 4.

8 4.

8 1.

9 1.

9 4.

2 4.

2 N

aOH

re

quir

ed (

kg/h

our)

2.

3 2.

3 15

.1

15. I

16

.6

16.6

6.

9 6.

9 15

.1

15.1

Cos

ts o

f op

erat

ion

Mai

nten

ance

(kE

CU

/yr)

89

3 1,

195

893

1,19

5 89

3 1,

195

893

1,19

5 89

3 1,

195

Per

sone

l (k

EC

U/y

r)

456

781

456

781

456

781

456

781

456

781

Dol

omit

e (k

EC

U/y

r)

234

208

186

166

220

195

365

324

415

369

Ash

dis

posa

l (k

EC

U/y

r)

467

414

878

779

1,65

9 1,

473

655

582

1,43

7 1,

276

NaO

H c

onsu

mpt

ion

(kE

CU

/yr)

22

20

14

5 12

9 16

0 14

2 67

59

14

5 12

9 In

sura

nce

(kE

CU

/yr)

29

52

29

52

29

52

29

52

29

52

T

otal

ope

r. c

osts

(kE

CU

/yr)

2,

100

2,67

0 2,

611

3,12

9 3,

441

3,86

7 2,

464

2,99

3 3,

253

3,82

9 F

uel

cost

s (k

EC

U/y

r)

6,91

4 7,

161

- 20

,473

2,

097

- 20

,816

-

7,92

1 -

16,3

31

- l,

160

-

19,4

24

- 2,

709

Cos

ts l

ogis

tics

(kE

CU

/yr)

1,

420

1,26

0 1,

683

2,89

2 2,

301

3,36

3 54

2 48

1 60

7 53

9 Fu

el c

osts

at

plan

t (kE

CU

/yr)

8,

333

8,42

2 --

18,7

90

4,99

0 --

18,5

16

--4,

558

--15

,789

--

678

--18

,817

--

2,17

0

Rei

mbu

rsem

ents

b P

rodu

ced

elec

tric

ity

(kE

CU

/yr)

5,

197

4,61

4 4,

803

4,26

4 4,

582

4,06

8 5,

246

4,65

7 5,

192

4,61

0 In

stal

led

pow

er (

kEC

U/y

r)

2,83

6 2,

836

2,62

1 2,

621

2,50

0 2,

500

2,86

3 2,

863

2,83

3 2,

833

Tot

al (

kEC

U/y

r)

8,03

3 7,

450

7,42

4 6,

886

7,08

2 6,

568

8,10

8 7,

520

8,02

5 7,

443

Tot

al i

nves

tmen

t co

sts

(kE

CU

) 44

,632

59

,734

45

,802

61

,051

45

,802

61

,051

44

,632

59

,734

45

,802

61

,051

D

epre

ciat

ion

cost

s (k

EC

U/y

r)

2,85

7 5,

208

2,93

2 5,

323

2,93

2 5,

323

2,85

7 5,

208

2,93

2 5,

323

Mai

n ec

onom

ic p

aram

eter

s kW

h co

sts

(EC

Uct

/kW

h) •

6.2

8.5

-6.7

7.

6 -6

.4

2.8

-4.8

3.

9 -5

.9

3.7

EC

U/k

W i

nsta

lled

15

37

2057

17

07

2275

17

89

2385

15

23

2038

15

79

2105

W

aste

tre

atm

ent

cost

s (E

CU

/ton

) -

12

2 -6

5

-2

9 -2

0

6 -

10

11

> ;>

> 2

~Cal

cula

ted

pow

er p

rodu

ctio

n co

sts

incl

ude

the

pres

ent

biom

ass

fuel

cos

t le

vels

, whi

ch a

re n

egat

ive

in t

he c

ase

of v

erge

gra

ss,

OD

W,

dem

olit

ion

woo

d an

d sl

udge

. T

he c

alcu

late

d w

aste

tre

atm

ent

cost

s sh

ow t

hat

thos

e st

ream

s ha

ve a

val

ue (

nega

tive

tre

atm

ent

cost

s) a

s fu

el:

the

reim

burs

emen

ts f

rom

ele

ctri

city

pro

duct

ion

are

high

er t

han

the

dep

reci

atio

n an

d op

erat

ion

and

mai

nten

ance

co

sts.

Wh

enth

is v

alue

is

reco

gniz

ed t

he (

nega

tive

) co

st o

f th

e fu

el m

ight

inc

reas

e, e

spec

iall

y w

hen

larg

e qu

anti

ties

of

a st

ream

are

uti

lize

d.

hRei

mbu

rsem

ent

leve

ls f

or e

lect

rici

ty p

rodu

ced

dece

ntra

lly

are

2.42

EC

Uct

/kW

h a

nd 9

8 E

CU

/kW

~ i

nsta

lled

. ~~


20000000

"U -10000000

-20000000' >.

- - Demolition

I O00000G ~ [ ] m " I w°°d I

o L ! ! - ! ! - II . . ! !

• Depreciation [ ] Operation • Logistics [ ] Fuel

-30000000 I I L I I I k L I min max min max rain max rain max rain max

Fig. 4. Breakdown of minimum and maximum calculated yearly costs o f electricity product ion with the selected A C F B - C C system as a function of the biomass waste and residue streams.

Investment costs and operational costs might however increase when more extensive pretreatment is necessary. A multi-fuel plant might require different storage bunkers and sizing equipment. For example, experience with feeding fuels such as grasses into gasification equipment is still very limited, and densification might be required, which will increase handling costs. These aspects are mentioned only briefly here but deserve more attention.

Although logistics appear to be a relatively small cost factor (especially in relation to the transport distance), it has been dealt with in a relatively simple way. The logistics can become quite complex, specially when a variety of

biomass streams is involved. Organizational aspects, variations in availability, storage required and backup fuel, especially in winter months, are issues that require more detailed study.

A crucial factor in the overall economic performance is the (negative) biomass fuel cost. Negative biomass costs, due to present waste treatment costs, can even give rise to negative electricity production costs. However, future developments, and especially an increased demand for biomass residues for energy applications, might increase those costs, thus affecting the COE. This aspect was not part of the analysis given here.

0, I 0.05[

,"6

-0.0

• kWh costs (fuel cost included)

-O.l min max rain max rain max min max min max

Fig. 5. Minimum and maximum calculated electricity product ion costs with the selected A C F B - C C system as a function of the fuel (including fuel costs).

404 A. FAAIJ et al.

200| 180 F

160 -

140 .g

120-

100-

8 0 - e-

60-

40 -

20 -

Load factor

Interest rate I

Lifelinils ~

Efficiency

t J J I I I I I 1 20 40 60 80 100 120 140 160 180 200

Variation of parameter (%)

Fig. 6. Sensitivity of electricity production costs to load factor, lifetime, investment costs, net efficiency and interest rate. Percentual variations per parameter show the percentage changes in kWh costs; 100% represents the average case for all relevant parameters. Values used for this sensitivity analysis refer to

the clean wood case.

200

180

160

140

1 2 0

100

80

60 i

4o i

201

Transportation distance

Fuel price

I I I I I I I F I 0 20 40 60 80 100 120 140 160 180 200

Variation of parameter (%)

Fig. 7. Sensitivity of electricity production costs to fuel price and to distance over which the fuel is transported. Values used for this sensitivity analysis refer to the clean wood case.

Table 14. Comparison of the BIGCC concept with composting, anaerobic digestion and large-scale waste incineration in the Netherlands with respect to waste treatment costs and

conversion efficiency

Waste treatment option

Efficiency of conversion Cost of waste treated to electricity

(ECU/t) (% LHV)

ACFBC concept in this study Large-scale waste incineration 49

20--11 35-40 56-111

12-22 Anaerobic digestion 5~ 28-118 ~ 12 ~ Composting 5~ 28-78 energy input ~ 30 kWh/t

"The net energy yield of digestion depends on the utilisation of the biogas produced. Utilisation in a gas engine is assumed here.


6. CONCLUSIONS

The BIGCC atmospheric gasification process based on TPS gasification technology coupled to a General Electric LM 2500 gas turbine seems flexible enough to deal with a wide variety of fuel properties. "Difficult" biomass fuels such as sludge, with very high ash content or very wet streams (or a combination of these such as organic domestic waste), can be used to only a limited extent and have to be mixed with cleaner materials.

The limits of what the proposed concept can handle are: ash 10-20wt% (for dry fuel) and moisture contents ~ 70wt% (for ash-free fuels). These limits are due to the gas turbine, which requires gas with a minimum heating value of 5.6 MJ/m 3 (s.t.p.).

Model calculations for thinnings, verge grass, organic domestic waste, demolition wood and a wood-sludge mixture have yielded net system efficiencies that vary between 35,4 and 40.3% (LHV basis). These calculated efficiencies make it possible to compare the performance of the system when using different fuels. However, it should be noted that optimization of the system is still possible.

The system concept seems capable of meeting the strict environmental standards that are applicable to waste incineration in the Nether- lands. The behaviour of the flue gas dryer is the most uncertain factor in this respect. If fuels such as sludge, organic domestic waste and verge grass are used, H2S has to be removed from the fuel gas to meet emission standards. Adding a base such as sodium hydroxide to the scrubber medium is an option. Ammonia has to be removed from the fuel gas in all cases to meet NO, standards. For a system capable of using a wide variety of biofuels, a two-stage scrubber is recommended.

The investment costs cover a relatively wide range: 1500-2300 ECU/kW, with a total investment of 45-60 million ECUI995 for a 25-29 MWe plant. A first fully commercial plant (with still higher engineering and development costs) will be at the upper end of this range. When similar plants (of the same concept and scale) are built, engineering costs will become less important and the cost will be at the lower end of this range. Demonstration units or installations which are semicommercial and precede fully commercial facilities may however lead to cost levels above the figures mentioned, because of the necessary extensive testing and engineering.

More experience with BIGCC systems will rationalize the design and equipment costs. Major cost reductions for this concept seem possible in particular by improving the conversion efficiency and thus lowering the costs per kWe installed.

The calculated kWh costs vary between minus 6.7 and plus 8.6 ECUct/kWh. This very wide range is caused in the first place by the present very wide range of fuel costs.

In a number of cases (verge grass, demolition wood), negative fuel costs compensate for all other costs of the plant, which results in negative electricity production costs. The upper range represents a plant with investment costs at 2057 ECU/kWe and thinnings as fuel (4 ECU/ GJL~v, which is comparable with the projected costs for energy crops). The overall electricity production costs depend strongly on the fuel costs, but for most available biomass wastes and residues in the Netherlands the COE can compete with current power production costs. Larger-scale conversion units seem attractive because of the low sensitivity of the COE to the transportation distance and the importance of high efficiency, especially when high-cost fuels such as thinnings or energy crops are used.

As a waste treatment facility the BIGCC concept seems very attractive compared with other treatment options currently applied to biomass waste streams: landfilling, waste incineration, anaerobic digestion and composting. Costs per tonne of waste treated are far lower and the efficiency is highly favourable.

From this research it is concluded that gasification of biomass residues and waste streams is technically and economically feasible and is likely to have limited environmental impacts. No fundamental technical problems hamper the implementation of this option. However, more experimental data on biomass drying with flue gas and gas turbine tests will have to be collected. Dynamic system behaviour (sensitivity to fluctuations in fuel gas quality and mass flows) and pretreatment and feeding non-woody materials should be investigated by practical experience.

Acknowledgements--The authors are grateful for sponsoring by CEC DG XII, within the framework of the EC JOULE II + programme. Co-sponsoring was provided by the Noord-Holland gasification project and NUTEK. The authors also wish to express their gratitude to the many people who provided information and discussed specific technical aspects. Special thanks are due to Chuck Nielson and Doug Sharer of General Electric, Arnoud Carp of Hoogovens Technical Services BV. Garrett Blaney of

406 A. FAAIJ et al.

Electricity Supply Board International, Erik Larson of Princeton University and Bertil Prins and Harry Steenhuis of Thomassen Stewart and Stevenson International BV. The authors are grateful to Sheila McNab for linguistic assistance.

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Gasif icat ion of biomass wastes and residues for electricity p roduc t ion 407

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