POWER MANAGEMENT IN UNIVERSITY FACILITY
POWER MANAGEMENT IN UNIVERSITY FACILITY Goro Fujita Department of Electrical Engineering, College of Engineering Shibaura Institute of Technology ABSTRACT This paper discusses on power management in a university. Electric power is mainly supplied from an electric power utility, supplementary power may be supplied by photovoltaic power generation system or wind generation system. However, relationship between investment and payback should be studied in advance of the installation and operation. Power storage devices such as NaS (sodium-sulfur) battery play a good role in reduction of the electric charge so that leveling of daily load curve is improved. These topics regarding SIT and a few universities in JAPAN are focused as case studies. The purpose of this study is for reduction of the contract electricity by “Peak cut control” achieved by a battery system, and “Enhancing environmental concerns for students”,
improving image on renewable energy. Therefore, this paper discusses the following power supply systems: reducing the electricity receiving power with the generation at a WG (wind generator) which is a new installation and existing PV (photovoltaic) power generation facilities. In addition, a battery can change output power and reduce contract electricity at the peak period, realized by charged power at night period, resulting in cost cut. These facilities are sown in Fig.1. This paper considers about the reduction of the electricity rate by reduction of the contract electricity and the reduction of the receiving power. In addition, this paper discusses the initial cost of a wind generator and the battery, evaluating loss of battery and the cost performance.
(a) NaS (sodium-sulfur) battery
(b) WG (wind generator)
(a) PV (photovoltaic) module
(d) PV indicator Fig. 1. Power facilities
― 287 ―
1. INTRODUCTION Now a day because of the deregulation of the electricity business, electricity business is open to any place, not just the electric power company. In addition, the generation with the distributed power supply attracts its attention from two aspects, many device having little carbon dioxide discharges generally and the possibility of the reduction of the electricity bill [1]. A simple model is constructed which evaluates the generator dynamics using software (MATLAB / SIMULINK). Fig.2 is the outline chart of this system. The storage battery is controlled with PC. The control aimed for “stabilization of the output”, “Decrease of the contract electric power”, and, “Effective use of the electric power at nighttime” is to be scheduled on the PC. Disclosing energy usage condition to the average student is also a target of this study for energy education. 2. ELECTRIC POWER SYSTEM MODEL Simulating model throughout theoretical studies is importance factor for success of the researches. The model consists of generators model and load model and control center model. The model output the signal which added the generators out put to P-tie (tin-line power flow on the feeder from utility) and a difference with the load. the model calculates a frequency deviation from a difference of the electricity then decides the output of P-tie based on it. The model feeds back the output of P-tie and decides output of a battery in the control center. And the model simulates its dynamics.
Generators
a WG
d
c
Utility grid
BT
PC PV
b University load
Fig. 2. University power facility model
Fig.3. shows the battery system, considering the electricity loss caused by battery itself and the corresponding power converter. Loss with a case of 10% and a case of 20% are calculated. Fig.3 is the former 10% loss model. When the amount of the electric power is ordered as a command from the control center, the loss is considered though this model as index SOC, which should be within limitation [2]. Fig.4. shows the load curve that the consumption electricity of the university, obtained from recorded value at a day of July. The reason of focusing July is it is the most electricity demand period during a year. Fig.5. and Fig.6 show assumed output of wind generator and photovoltaic power generation. Both of them are rating 20kW [3].
Fig. 3. Battery system model
― 288 ―
reduction in the amount of the payment for metered electric power and the contract electric power is calculated. This university is contracting to IPP (Independent Power Producer). Table.1 shows the unit price used in the IPP. Table.1. Unit price of new IPP Unit price Contract electric power Preliminary line Receiving power(summer) Receiving power(other season) Amount of fuel adjustment Fig. 4. Load curve
(yen/kW) 1510 60 8.25 7.8 1.28
The contract electricity cost is decided depending on the amount of the receiving power at the peak. Because the introduced storage battery is 20kW, it is 20kW contract electric power decrease. And a basic charge and the preliminary line expense can be reduced by this. Moreover, a basic charge is the discount by moment of power factor, and when moment of power factor is improved on the demand ground, is discounted 15% or less. The value of power factor of university facility is 1.0. Therefore, if it is calculated as followings; Basic charge: 1,510×20×(185-1.0×100)=25,670 [yen] Preliminary line expense: 60×20=1,200 [yen] Total: 26,870 [yen] When the amount of the receiving power decreases, the cost that can be reduced.. Because the unit price of the amount of the receiving power assumes summer in this study, unit price in summer season is used. When the average output of wind power generation is assumed to be 5kW, electricity will be generated by 3600 kilowatt-hour in year. Receiving power reduction: 8.25×3600=29,700 [yen] Total: 26,870 29700 u 12 678,840 [yen/per year]
Fig. 5. WG output
B. Evaluation of initial cost The equipment newly established by this research is a storage battery and a wind generator. First of all, an initial cost of the storage battery is calculated. Peak period is about four hours.. Fig.7 is a power generation unit price for electrical discharge times. 㪠㫅㫀㫋㫀㪸㫃㩷㪺㫆㫊㫋
Fig. 6. PV output. Two cases of 10 % and 20 % an internal loss of the storage battery are evaluated. Considerable difference can not be identified but 20% loss discharge time is longer than 10% loss discharge time. Moreover, the frequency is within 50Hz±0.1Hz that is same to in East Japan, which means stability problem does not exist.
㪬㫅㫀㫋㩷㫇㫉㪺㪼 䋨㪈㪇㪇㪇㫐㪼㫅䋯㫂㪮䋩㪅
㪋㪇㪇 㪊㪇㪇
㪣㪼㪸㪻㩷㪸㪺㫀㪻 㪥㪸㪪 㪩㪝
㪉㪇㪇 㪈㪇㪇 㪇 㪇
3. COST EVALUATION
A. Evaluation of contract charge Next, how much cost can be reduced because of the
― 289 ―
㪌 㪈㪇 㪜㫃㪼㪺㫋㫉㫀㪺㪸㫃㩷㪻㫀㫊㪺㪿㪸㫉㪾㪼㩷㫋㫀㫄㪼䋨䌨䋩
Fig.7. Power generation unit price.
The lead-acid battery is the cheapest during four hours in the ratings output time. If the longevity of the storage battery is calculated as 15 years, the calculation result is as follows. Initial cost of battery system 230,000×20÷17=310,000[yen] Next, it is as for an initial cost of the wind generator. The unit price of a wind generator that is medium-scale or small-scale is about 240,000-370,000 [yen/kW]. Now two cases of 240,000 [yen/kW] and 370,000 [yen/kW] are assumed. An initial cost of the wind generator is as follows assuming lifetime is17 years. Initial cost of wind generator A: Case of 240,000[yen/kW] 240,000×20÷17=280,000[yen/per year] B: Case of 370,000[yen/kW] 370,000×20÷17=30,000[yen/per year] Finally, the result of the cost evaluation is as follows. A: Case of 240,000(yen/kW) 678,840Ƚ(310,000+280,000)=90,000[yen/per year] B: Case of 240,000(yen/kW) 678,840Ƚ(310,000+430,000)=60,000[yen/per year] Therefore, it becomes a cost reduction in about 90,000 yen a year in case A. However, about 60,000 yen cost increases during year in case B. No economical advantage is found in case B. 4. CONCLUSIONS Installation of PV and/or WG system is getting popular among small customers associated with increasing concern on environmental issues and countermeasures [4]-[7] . However, feasibility study should be conducted before sating planning, including initial and running costs, understanding electricity bill system. Contribution to the management section is also important factor to run this kind of planning. Further research will focus on critical conditions for the facility investment and appropriate operation of the generation systems.
[4] M. Matsubara, G. Fujita, T. Shinji, T. Sekine, A. Akisawa, T. Kashiwagi, R. Yokoyama, ‘Supply and Demand Control of Dispersed Type Power Sources in Micro Grid’, Intelligent System Appreciation to Power Systems 2005 (ISAP 2005), No.10 (2005-11, Washington, USA) [5] Y. Takemoto, G. Fujita, K. Hasegawa, K. Koyanagi, T. Funabashi, R. Yokoyama, ‘Experimental Study on Rotary Frequency Converter’, Intelligent System Appreciation to Power Systems 2005 (ISAP 2005), No.60 (2005-11, Washington, USA) [6] Y. Takemoto, G. Fujita, R. Yokoyama, K. Koyanagi, T. Funabashi, W. Chen, ‘Design Consideration and Verification by Experiment of Rotary Frequency Converter’, International Conference on Electrical Engineering (ICEE) 2006, MI1-9 (2006-7, YongPong Resort, Korea) [7] M. Matsubara, G. Fujita, T. Shinji, T. Yamakami, A. Akisawa, T. Kashiwagi, R. Yokoyama, ‘Suitable Control and Supply of Micro Grid by Installation of Battery’, International Conference on Electrical Engineering (ICEE) 2006, SE1-09 (2006-7, YongPong Resort, Korea) Goro Fujita was born in January 1970. He received the B.E., M.E. and Ph.D degrees in electrical engineering from Hosei University, Tokyo, Japan in 1992, 1994 and 1997 respectively. In 1997, He was a research student of Tokyo Metropolitan University. Since 1998, he is in Shibaura Institute of Technology, Tokyo, Japan. At present he is an associate professor. His interest is in power system control including dispersed power sources. He is a member of the IEE of Japan, the Society of Instrument and Control Engineers (SICE) of Japan, and IEEE. He is also a Professional Engineer in Japan (Electrical and Electronics field)
REFERENCES [1] S. Shiki, “Autonomous Decentralized Control of Supply and Demand by Inverter Based Distributed Generations in Isolated Microgrid”, The Transactions of The Institute of Electrical Engineering of Japan, Vol.127-B, No.1, 2007 (in Japanese) [2] Y.Ueda, “Advanced Analysis of Grid-connected PV System’s Performance and Effect of Battery”, The Transactions of The Institute of Electrical Engineering of Japan, Vol.127-B, No.1, 2007 (in Japanese) [3] Y.Hayashi, “Cooperated operation form in supply of electric power system corresponding to expansion of decentralized power supply introduction”, The Transactions of The Institute of Electrical Engineering of Japan, Vol.127-B, No.1, 2007 (in Japanese)
― 290 ―
3rd SEATUC Symposium, Feb. 2009 Johor Bahru, Malaysia
CATALYZED LIQUEFACTION OF EMPTY PALM FRUIT BUNCH (EPFB) IN SUB-CRITICAL WATER Javaid Akhtar, Soo Kim Kuang, NorAishah Saidina Amin Chemical Reaction Engineering Group (CREG) Faculty of Chemical & Natural Resources Engineering, Universiti Teknologi Malaysia, 81310 UTM, Skudai, Johor, Malaysia Corresponding Author : Nor Aishah Saidina Amin Tel: 07-5535588, Fax: 07-5581463, E-mail: [email protected] ABSTRACT Effect of alkaline catalysts (NaOH, KOH & K2CO3) on EPFB biomass liquefaction is investigated under subcritical water conditions in a batch type reactor operating at 270oC and 20 bars for a period of 20 minutes. In this study catalyst performance and suitable biomass to water ratio in order to support higher EPFB conversion, liquefied hydrocarbon yields and lignin degradation were screened. According to the results through GC-MS, FTIR, and UV spectrometer, one typical run could achieve 68 % of liquid hydrocarbons with 72.4 % EPFB conversion and 65.6 % lignin degradation in 1.0 M and 2:10 biomass to water ratio operating at the above said conditions. Liquid output was only 36.4 % when subjected to the same operating conditions in the absence of catalyst. Furthermore, high biomass to water ratios beyond 2:10 decreased both solid mass conversion and liquid hydrocarbons. The order of the catalyst reactivity was in the following order: K2CO3 > KOH > NaOH. Phenols and esters were dominant in the liquid products and K2CO3 yielded the highest value of phenols. The alkaline catalyzed process assisted with hot water treatments seemed promising for production of phenolic-rich bio oils from EPFB. 1
INTRODUCTION
Biomass supplies 12-14 % of energy requirements worldwide and shares around 35-50 % in developing countries. Furthermore, fossil energy depletion and its uneconomical extraction have spurred the idea of utilizing biomass in various applications like bio-fuels and bio- chemicals. It is widely accepted that utilizing biomass as energy source would bring forth social and economical benefits in less developed regions of the world. Other benefits include i) sustainable energy through renewable biomass ii) CO2 neutral substitute of
fossil fuel iii) reduction in gases like NOx, SOx due to less sulfur and nitrogen contents present in biomass and iv) abundant availability in all regions of world (Demirbas et. al. 2000, Kucuk et. al. 1997 Mckendry et. al. 2002). Empty palm fruit bunch (EPFB)-biomass used in current study, is one of the major wastes of oil palm plantations. EPFB amounts to 4.4 tonnes per hector per year, approximately concedes 20.4 % of total oil palm biomass. Total 73.4 million tonnes of palm biomass, in Malaysia for example, supplies 14.89 million tonnes EFB and 37.65 million tonnes world wide on yearly basis (Tau et. al. 2007, Yang et. al. 2004). Converting cheap abundant amounts of renewable palm EFB into valuable commodities like bio-fuels would bring forth energy security and social benefits in countries like Malaysia, Indonesia, Thailand and tropical African countries. Liquefaction of biomass feedstock to liquids like bio-fuels and chemicals, is one of the major alternatives for biomass utilization (Chunbao et. al. 2008, Mohan et. al. 2006, Bridgewater et. al. 1995, 2001). Biomass is liquefied into fuels and chemical based commodities through thermal, thermochemical, biochemical and biological routes. Biological means are quite economical for such liquefactions yet very low conversion of solid mass makes these processes unfit for large scale applications. Conversely, liquid yield is quite high (5070 %) in thermal and thermochemical processes. However still issues like low product quality, high temperatures and pressures daunt industrial applications of such processes. In thermochemical methods, direct and indirect conversions are two viable options for biomass liquefaction. Bio fuels and chemicals can be obtained indirectly from biomass gasification via Fischer-Tropsch conversion (Mark et. al. 2004, Charlo et. al. 2004) while direct processes like pyrolysis, extractions, and hydrogenations convert biomass solid to liquids. Direct processes are suitable choices in recent times due to
― 291 ―
simpler processing steps permitted with post- processing of liquid oils in order to increase fuel value. However, selection of a suitable process depends on various factorsbiomass types, product utility, economic aspects, and environmental conditions etc (Chunbao et. al. 2008, Peter et. al. 2002). Fast pyrolysis, wherein biomass is heated rapidly within 400- 850oC at atmospheric pressure usually, has reputation of yielding high amounts of products. However, problems like high water contents in product liquids, chars and a well mixed amount of organic compounds lower product quality and its potential application. Sub and supercritical extraction of biomass in solvents like water, methanol, ethanol, ether and CO2 etc produces bio oil dominated by phenols and esters etc. Thus, super/sub critical liquefaction may be a suitable option for EPFB liquefaction for which current study is carried out. The effect of catalysts like NaOH, Na2CO3, KOH, and K2CO3 was studied on sub critical water liquefaction of woody biomass at 208oC (Selhan et. al. 2005). Uncatalyzed liquefaction of Cunninghamia Lancelolata in water medium yielded 24 % of liquid oils at 280-360oC and 8 gm biomass/100 mL water conditions (Yixin et. al. 2003). In another development, rice straw liquefaction in presence of various liquids like water and ethanol, 2propanol under low temperature and pressure was studied (Yuan et. al. 2007). Depolymerization of lignin by alkali at 290oC in supercritical methanol illustrated lignin decomposition was proportional to base strength (Miller et. al. 1999). Effect of temperature on liquefaction of woody biomass in presence of Na2CO3 catalyst within 280-420oC was studied and 380oC as the optimal temperature was recommended (Yejian et. al. 2007). Water-phenol solvent system to liquefy wood biomass at moderate 250oC in presence of catalysts like NaOH, CuSO4 and (NH4)2SO4 was studied to investigate the effect of catalyst concentration, biomass to solvent ratios, pH of mixture and biomass types on liquids and residues production (Maldas et. al. 1996). In this work, empty palm fruit bunch (EPFB) was liquefied in hot water at moderate operating conditions (200oC, 20-40 bars) and 20 minutes in presence of KOH, K2CO3, and NaOH catalysts to compare liquid yields and biomass conversions in catalytic and non-catalytic runs. Liquids and solids compositions as well as lignin decomposition were analyzed through GC-MS, FTIR and UV Spectrophotometer. The objectives of this work were to investigate effect of base catalysts and suitable EPFB/water ratio to produce bio-chemical rich bio oil. 2
EXPERIMENTAL
Materials Empty palm fruit bunch (EPFB) was collected from FELDA oil palm company in Bukit Besar Kulai, Malaysia. The feed biomass was grounded to particle size ranged from 0.5 mm to 1.0 mm. Sulphuric acid and alkaline catalysts were obtained from Mallinckrodt Chemical Inc., USA and Quality Reagent Chemicals (QREC)., NZ, respectively.
2.2
Hydro-liquefaction The experimental rig consisted of a stainless steel autoclave, an electrical furnace and a product recovery system supported by water cooled condenser as shown in figure 1. Catalyst and crushed EPFB were mixed with water in a specified biomass to water ratio in the autoclave. Temperature, 270oC and pressure, 20-45 bars were maintained for 20 minutes residence times in this base catalyzed hot water liquefaction of EPFB. During reaction small quantity of gas was purged in a sampling tube in order to control pressure and avoid vapors loss. After 20 minutes of heating at 270oC, the operation was halted and cooled in open atmosphere followed by water cooling. Collected product was separated as unconverted solid mass and liquid portions. Effective biomass to water ratio, effect of basic catalysts and its concentration, were parameters notified in the above said procedure.
Gas Release
Pressure Gauge Thermocouple
Nitrogen Furnace Water
Autoclave Reactor Fig. 1
Experimental setup
2.3 Analysis 2.3.1 Kappa Number Test In this experiment, the kappa number was derived from the ratio of the absorption spectral intensities at 546 nm wavelength measured at the beginning and end of the reaction of EPFB with permanganate through UV spectrophotometer analysis. Details of procedure can be followed elsewhere (Chai et al. 2000). Kappa number was calculated according to the following formula:
2.1
Where K = Kappa number, a = Volume of 0.02mol/L permanganate solution used in experiment, w = Mass in grams of the solid sample used, Ae = Spectral intensities of blank solution, Ao = Spectral intensities of solution with the solid product
― 292 ―
2.3.2
FTIR analysis The solid residue collected at each operating condition was analyzed by Spectrum One FT-IR spectrophotometer (Perkin-Elmer, Ltd). FTIR analysis determined the structure of the char after the subcritical water treatment. FTIR spectra of the samples were recorded on the FTIR-Spectrum One with the KBr pellet technique. EPFB residue is mixed with laboratory grade KBr, grounded and pelletized with a hydraulic press. Pellet was tested through infrared spectrum in a range of 4000 to 370cm-1.with a resolution of 4cm-1. 2.3.3
GC-MS Spectroscopy GC-MS spectroscopy equipped with capillary column and selective detector (MSD) analyzed liquid product obtained through experiments. A calibrated Agilent 6890 series GC-MS equipped with a flame ionization detector and a capillary column (SPBTM-5, 30m x 0.32mm x 0.25µm) with helium gas as the carrier was used to perform the analysis. Liquid product of 100 µl was pipetted out each from the bottom and upper layer and top up to 10 mL with methanol as diluents in a measuring cylinder. The mixture was shaken to ensure complete mixing. Next, it was filtered into a GC vial and was ready for testing. The GC oven would be kept at 1800C for 2 minutes, ramped at 40C/min up to 2000C for 10 minutes. 3
RESULTS AND DISCUSSION
3.1
Effect of catalyst types Basic cataysts significantly degraded EPFB compared to non-catalystic run in all three parameters discussed in figure 2. Solid conversion jumped from 36.4 %, without catalyst, to 72.4 % in K2CO3 solution. Similar trend was realized in liquid yield and lignin degradation. Results obtained from NaOH, KOH treatmetns were within the said extremes and pretty similar to each other. K2CO3 > KOH > NaOH was the catalyst reactivity order for EPFB degration proved through these experiments. This may inform about superiroty of carbonates in EPFB degration than to hydoxides which may be due to conversion of K2CO3 into bicarbonates as secondary catalyst.
K2CO3 presence in supercritical hydropyrolysis of glucose at 450-550oC increased liquid yield proving effectiness of such catalysts in gasification process (Sinag et. al. 2003). Low temperature base catalyzed liquefaction of wood at 280 oC for 15 minutes also confirmed the sequence of our present study: K2CO3 > KOH >Na2CO3> NaOH. This may also support potasium bases are effective than sodium (Selhan et. al. 2005).
Fig. 2 Effect of various catalysts on amount of liquids in EPFB liquefaction 3.2
Effect of K2CO3 concentration EPFB liquefaction was further analyzed with various concentration of K2CO3 solution at 270oC, 5gram/25 ml water ratio. K2CO3 1.0 M yielded maximum conversion, liquids and lignin degradation. Catalyst concentration supported EPFB breakdown prior to 1.0 M K2CO3 and discouraged liquid yield beyond 1.0 M. K2CO3 possibly promoted re-polymerization at high concentrations. Solid conversion and liquid yield were least affected by catalyst concentrations while lignin degradation varied comprehensively (figure 3). Almost 10 % increase in liquids yield was noticed with 40 % extra lignin degradations. This proved almost one fourth effect of lignin on liquid yield as can be seen by original composition of EPFB wherein lignin is about 20 % of total lignocelluloses (Luis et. al. 1999).
Fig. 3 Effect of K2CO3 concentraion on EPFB conversion and liquid yields Higher conversion with increasing K2CO3 concentrations after analyzing effects of various K2CO3 solutions (0.235 M, 0.47 M, and 0.94 M) on biomass up gradation at 280oC was reported (Selhan et. al. 2006). Furthermore, in our study K2CO3 solution discouraged conversion beyond 1.0 M K2CO3 concentrations.
― 293 ―
3.3
Effect of biomass to water ratio Higher concentrations of EPFB biomass decreased amount of liquids and lignin degradation. As from figure 4, 68% liquids were achieved with 2:10 EPFB to biomass ratio converting 72% of solid mass at experimental conditions of 270oC, 40 bars, 1.0 M K2CO3 solution. 8:10 EPFB to biomass ratio resulted in the lowest degradation, liquids and solid mass conversion. In a similar study, cunninghamia lanceolate was liquefied in water in presence of 280-360oC with different biomass to water ratios (8g, 10g, 12.5 g per 100 ml each) (Yixin et. al. 2003). Results proved high amount of biomass led to low conversion and liquid yield as said in our study.
Table 1 Percentages of organic groups obtain through GC-Mass analysis of liquid oil under various conditions Reaction Condition Temperature = 270 oC Pressure = 40bar Reaction time =20min
% Area Phenol
Methyl Ester
Benzoic acid
5g EPFB/25ml Water Without catalyst
-
26.44
-
K2CO3 1.0 M
60.08
39.92
-
KOH 1.0 M
18.40
81.6
-
NaOH 1.0 M
6.00
86.45
-
K2CO3 0.1 M
1..33
2.88
2.89
K2CO3 0.5 M
1.77
63.48
4.85
K2CO3 1.0 M
60.08
39.92
-
K2CO3 1.5 M
34.50
68.50
-
K2CO3 2.0 M
34.79
65.21
-
K2CO3 1.0 M
Fig. 4 Effect of EPFB/water ratio on EPFB conversion, lignin degradation and liquid yields Although smaller biomass to water ratio resulted in better conversion, the use of large amounts of water should be avoided as the high energy inputs incurred high cost. 3.4
Liquid oil composition Liquid products distribution depended strongly on catalyst types and biomass to water ratio as shown in table 1. For 5:25 EPFB to water ratio, maximum ester yield was 86.45 % in 1.0 M NaOH solution while 1.0 M K2CO3 produced 60.08 % phenols. Subcritical hot water system could produce fuel grade bio oil dominated by phenols and esters (see table 1). Similar results have been published in literature (Selhan et. al. 2006). EPFB and char characterization Fourier transform infrared (FT-IR) spectroscopy characterized raw EPFB and chars obtained in liquefaction process said above within wave number range 4000 – 370 cm-1 (figure 5). Various bands in spectrum were identified as O-H (3446.9 cm-1), methoxyl (2924.0 cm-1), methoxyl (2924.0 cm-1), aliphatic C-H bonds (3000-2860 cm-1), stretching of aromatic C=C groups (1680-1570 cm-1), stretching and bending modes of saturated aliphatic hydrocarbon (2980-2850 and 14001300 cm-1, respectively) and bending of aromatic C-H groups (900-700 cm-1).
2.5gEPFB/25ml Water
0.61
94.29
1.72
5gEPFB/25ml Water
60.08
39.92
-
10gEPFB/25ml Water
0.44
41.34
-
15gEPFB/25ml Water
7.63
-
24.28
From figure 5, it is accessed for no catalyst runs chars showed sharp peaks within 1680-1570 cm-1 band region indicating presence of C=C bonds wherein no such bonds were found in case of catalyzed chars (K2CO3, KOH, NaOH). This proved the reactive nature of catalyzed chars under said process conditions. However, peaks of O-H bonds (at wave number of 3440-3450cm-1) which were still present in catalyzed char residues reflected stability of phenols and alcohols.
3.5
Fig. 5 FTIR analysis of raw EPFB, and residue char on concentration
― 294 ―
CONCLUSION Among various base catalyst NaOH, K2CO3 and KOH screened in this study, K2CO3 produced maximum liquids being 68.0 % and degraded 65.62 % lignin under the same operating conditions. Catalysts reactivity order is confirmed as K2CO3 > KOH > NaOH based on liquid yields and solid mass conversion. Furthermore, 1.0 M K2CO3 produced the maximum value of solid mass conversion, lignin degradation and liquids when compared with other concentrations of same catalyst. Possibly at high K2CO3 concentrations beyond 1.0 M, repolymerization of fragmented components reduced liquid yield. Higher amounts of EPFB mass also decreased liquid yields and the optimum value obtained through experiments was 2 g/25 ml water. Liquid bio oil thus produced dominantly consisted of phenols and esters according to GC-MS analysis. This confirms superiority of sub critical technique compared to pyrolysis for example wherein a large number of liquid product components daunt oil quality and increase post processing costs. REFERENCES Carlo, N.H., Andre´, P.C.F., Herman, D.U., and Harold, B., Production of FT transportation fuels from biomass; Technical options, process analysis and optimization, and development potential, Energy, vol. 29 pp 1743–1771, 2004 Chai, X.S., Luo, Q. and Zhu, J.Y., A Simple and Pratical Pulp Kappa Test Method for Process Control in Pulp Production, Institute of Paper Science and Technology, Atlanta, Georgia, 2002 Chunbao, X., and Timothy, E., Hydro-liquefaction of woody biomass in sub and supercritical ethanol with iron based catalysts, Fuel, vol. 87, pp 335-345, 2008 Malsdas, D., and Shiraishi, N., Liquefaction of biomass in the presence of phenol and H2O using alkalis and salts as catalysts, Pregamon, pp 74-8, 1996 Miller, J.E., Evans, L., Littlewolf, A., and Trudell, D.E., Batch micro-reactor studies of lignin and lignin model compound depolymerization by bases in alcohol solvents, Fuel, vol. 78, pp 1363–1366, 1999 Tau, L.K.Y., Keat, T.L., Abdul, R.M., and Subhash, B., Potential of hydrogen from oil palm biomass as a source of renewable energy worldwide, Energy Policy, vol. 35, pp 5692-5701, 2007 Kukuk, M., and Demirbas, A., Biomass conversion processes, Energy Conversion Management, vol. 38, pp 151-165, 1997 Luis, F.G., Óscar, J. S., and Carlos, A. C., Process integration possibilities for biodiesel production from palm oil using ethanol obtained from lignocellulosic residues of oil palm industry, Bioresource Technology, Vol. 100, no. 3, pp 1227-1237, 1999 Mark, J.P., Krzysztof, J.P., and Frans, J.J.G.J., Exergetic optimisation of a production process of Fischer–Tropsch fuels from biomass, Fuel Processing Technology, vol. 86, pp. 375– 389, 2004
Minowa, T., Fang, Z., and Tomoko, O., Cellulose decomposition in hot compressed water with alkali or nickel catalyst, J. Supercritical Fluids vol. 13, pp. 253259, 1998 Peter, M., Energy production from biomass (part 1): Overview of biomass, Bioresource Technology, vol. 83 pp. 37-46, 2002 Peter, M., Energy production from biomass (part 2): conversion technologies, ‘Bioresource Technology, vol. 83, pp. 47-54, 2002 Selhan, K., Thallada, B., Akinori, M., Yusaku, S., Toshiyuki, O., and Tamiya, K., Low temperature treatment of wood biomass analysis of liquid products, Chemical Engineering Journal, vol. 108, pp. 127-137, 2005 Selhan, K., Thallada, B., Akinori M., and Yusaku S., Hydrothermal upgrading of biomass: Effect of K2CO3 concentration and biomass/water ratio on products distribution, Bioresource Technology, vol. 97, pp 90–98, 2006 Sinag, A., Kruse, A., and Schwarzkopf, V., Key compounds of the hydropyrolysis of glucose in supercritical water in the presence of K2CO3, Ind. Eng. Chem. Res., Vol. 42, pp. 3516-3521, 2003 Yuan, X.Z., Li H., Tong, G.M., Tong, J.Y., and Xie, W., Sub and supercritical liquefaction of rice straw in the presence of ethanol-water and 2-propanol-water mixture, Energy, vol. 32, pp. 2081-2088, 2007 Yang, H.P, Yan, R., Chen, H.P, Lee, D.H, Liang, D.T, and Zheng, C.G, Pyrolysis of palm oil wastes for enhanced production of hydrogen rich gases, Fuel Processing Technology, vol. 18, pp. 1814-1821, 2004 Yejian, Q., Chengji, Z., Jian, T., and Jianhui, H.,Structural analysis of bio-oils from sub and supercritical water liquefaction of woody biomass, Energy vol. 32, pp. 196-202, 2007 Yixin, Q., Xiaomin, W., and Chongli, Z., Experimental study on the direct liquefaction of Cunninghamia lanceolata in water,Energy, vol. 28, pp. 597-606, 2003
― 295 ―
Prof. Dr. Nor Aishah Saidina Amin is the deputy dean for research and post graduate studies at the Faculty of Chemical and Natural Resources Engineering UTM, Malaysia. She also heads the Chemical Reaction Engineering Group (CREG). She received her PhD degree (1996) in chemical Engineering from Illinois Institute of Technology (IIT), Chicago, USA. Her research interests include bio-fuels, plasma chemical technologies, and methane reforming.
Javaid Akhtar is a PhD Chemical Engineering student at CREG UTM. He completed his Masters in chemical engineering (2005) from KAIST, South Korea and B.Sc (2002) from Punjab University, Pakistan.
Soo, Kim Kuang is a final year undergraduate chemical engineering student at the chemical reaction engineering laboratory (CREG), Universiti Teknologi Malaysia (UTM)
― 296 ―
APPLICATION OF OPTIMIZATION MODEL TO ANALYZE THE DEVELOPMENT OF VIETNAM ENERGY SYSTEM CONSIDERING CO2 EMISSION CONSTRAINT Bui Thanh Hung1, Hoang Ba Chu1, Bui Huy Phung2 1. Department of Thermal Energy System, Institute of Heat Engineering and Refrigeration, Hanoi University of Technology 2. Institute of Energy Science, Vietnam Academy of Science and Technology
ABSTRACT In Vietnam, energy consumption has been increasing because of rapid industrialization and economy development. At present, Vietnam is the energy producer and exporter, but as forecasting Vietnam need to import coal for electricity production after the year 2020. The paper presents the application of MESSAGE model, an optimization model developed by IAEA, to analyze the development of Vietnam energy system considering CO2 emission constraint. The analysis shows that using nuclear power plant and application of clean development mechanism (CDM) can be efficient measures for achieving energy security, decreasing CO2 emission and sustainable development for Vietnam. Keywor dss: Optimization model, energy system, CO2 emission 1. INTRODUCTION In Vietnam there are some applied projects and studies analyze the optimal development strategy for electric power system and the whole national energy system (Bui Huy Phung, et. al., 2006). Some optimization models are used such as MARKAL, EFOM-ENV, MESSAGE,... But in most of these studies, the impacts of environment factors on energy system were not examined. In recent years, with economy developing rapidly the energy consumption increases promptly. GDP increased from 20.21 mill. USD in 1995 to 53.66 mill. USD in 2005. Energy demand increased from 7.16 MTOE in 1995 to 20 MTOE in 2005. Electricity generation increased from 14.65 TWh in 1995 to 53.46 TWh in 2005. Vietnam now is an energy producer and exporter. In 2005, energy exportation of Vietnam is: 18 Mton of coal, 18 Mton of crude oil. This energy exportation can continue to the year 2020. But after 2020, as forecasting, Vietnam has to import coal for electricity generation. Many problems related to energy supply and use must
be addressed for Vietnam such as environment pollution, energy conservation and efficiency, energy security and sustainable development. In this study, we use MESSAGE model, an optimization model transferred by IAEA, to analyze and develop national, cost-effective strategies for CO2 emission reduction. Beside that, we also analyze to point the important role of nuclear power plant to ensure energy security for Vietnam in the future. 2. METHODOLOGY 2.1 Description of MESSAGE model (IAEA, 2007) MESSAGE (Model for Energy Supply Strategy Alternatives and their General Environmental Impacts) is a tool for medium- to long-term planning of the operation and extension of energy supply and use systems. The MESSAGE model is a multi-period linear optimization model. A predefined demand vector for the planning horizon is to be optimally covered (with respect to one or several target functions) using the resources and technologies available and observing exogenous constraints. MESSAGE was originally developed at International Institute for Applied Systems Analysis (IIASA). The IAEA acquired latest version of MESSAGE and several enhancements have been made in it, most importantly addition of a user-interface to facilitate its application. The most recent version of the model is MESSAGE V. MESSAGE identifies the flow of energy from primary-energy resources to useful-energy demands that (1) is feasible in a mathematical and an engineering sense, and at the same time (2) represents the investment choices that lead to the least cost of all feasible energy supply mixes to meet the given energy demand. Engineering feasibility is ensured by making energy flows consistent with model constraints on primary-energy availability and extraction, energy conversion and transportation as well as on end-use technologies and limits on the environmental impact of
― 297 ―
energy conversion. Energy flows are further determined by constraints on the rate of new capacity installation, the substitutability among energy forms, renewable-energy potentials and others. One important technical feature of MESSAGE is the so-called mixed-integer option. Expressed in less technical terms, this means the ability of the model to consider fixed sizes of technologies. Minimization of the total system cost is the criterion used for optimization of the model developed using the MESSAGE. The total system cost includes investment costs, operation cost and any additional penalty costs defined for the limits, bounds and constraints on relations. For all costs occurring at later points in time, the present value is calculated by discounting them to the base year of the case study. The sum of the discounted costs is used to find the optimal solution. Calculating total cost, MESSAGE can use assumptions on specific costs of hundreds of individual technologies as they develop over time. The actual number of technologies is determined by the degree of detail included in the Reference Energy System (RES) and specified in the MESSAGE input files. The RES is the conceptual core of the MESSAGE model. It is a formal description of energy supply and demand in a given economy and is thus the basis for energy modeling exercise. In its most comprehensive form, it represents a given real-world energy system including resource extraction, imports and exports, all conversion technologies, energy transport and distribution, as well as the energy demand. Detailed description of the objective function and constraints can be found in references (IAEA, 2007; J. Fr. Hake, et. al., 1994). 2.2 Energy model considering CO2 constraint for Vietnam The Reference Energy System for Vietnam in this study is shown in Fig. 1. It includes 9 subsectors and is divided into 2 main categories: - Energy supply and conversion sectors: Coal, Naturalgas, Oil, Central power generation sectors; - Energy consumption sectors: Industrial, Agricultural, Commercial, Residential, Transportation sectors. To analyze the effects of limitation of pollution emissions on energy system, we add some constraints to the MESSAGE model. The constraints are the limitations of the total amount of pollutant, such as CO2, SO2, NOx. These limitations can be introduced of each time step t in the time range. The constraints are expressed by the following set of equations: i n
ECO2 ¦ i
i, t
u Xi ,t d LCO2t
1
i n
ESO2 ¦ i 1
i, t
u Xi ,t d LSO 2t
i n
ENOx ¦ i
i, t
u Xi ,t d LNOxt
1
Where Xi,t : fuel consumption of technology i in time step t; ECO2i,t: emission factor for CO2 of technology i in time step t; ESO2i,t: emission factor for SO2 of technology i in time step t; ENOxi,t: emission factor for NOx of technology i in time step t; LCO2t: maximum value of total amount of CO2 in time step t; LSO2t: maximum value of total amount of SO2 in time step t; LNOxt: maximum value of total amount of NOx in time step t; In summary, the energy model developed in this paper to study Vietnam energy system includes the linear optimization model built in MESSAGE and 3 additional constraints on emission limitation. With this energy model, we can analyze the effects of single reduction (CO2) or combined reductions of CO2, SO2 and NOX at the same time. 2.3 Description of Cases and assumptions In this study, the planning horizon starts from 2005 to 2030. Emissions of CO2, SO2, NOx are calculated based on emission factors provided by the Intergovernmental Panel on Climate Change (IPCC). The energy demand data, technology data and other input data for optimization model are used based on the current references (Bui Huy Phung, et. al., 2006). The paper analyzed 3 cases: Base case , No_nuclear case and ENV1 case. The Base case: - Indigenous resources are exploited with maximum capacity (in the year 2030, coal about 60-70 MTon, crude oil about 20 MTon, natural gas about 20 Billion m3 and hydro power about 80 TWh); - Nuclear energy is used as fuel for electricity generation in the period 2020-2030 with capacity of 2000-6000 MW. No_nuclear case - Nuclear energy is not used as fuel for electricity generation in the study period 2005-2030. - All other things are the same as in the Base Case. CO2 limitation case (ENV1): 5% reduction of CO2 emission - In this case, a 5% CO2 emission reduction per year between 2025-2030 is introduced. The CO2 reduction is referred to the Base Case; - All other things are the same as in the Base Case.
― 298 ―
Fig. 1. Structure of Energy System for Vietnam
― 299 ―
3. RESULTS AND DISCUSSION Fig. 2 shows the structure of primary energy consumption in 2030 for 3 scenarios. The changes in total amount of primary energy consumptions are small. But there is a big difference in structure between 3 scenarios. The main changes are in coal and nuclear energy portions. 180
Fig. 4 illustrates the changes in electric power generation under the No_nuclear case. The quantities of gas combined cycle, hydro, renewable and oil power plant are the same those in Base case. The changes are mainly in coal-fired power plant. Coal-fired output increases about 22% compared with Base case. Vietnam has to import huge amount of coal for electricity generation. Coal import in 2030 will be 29.52 MTOE in No_nuclear case and 20.68 MTOE in Base case (Fig. 6).
160
35
140 MTOE
120
30
Electricity, MTOE
100 80 60 40 20 0 Base
No_nuclear
ENV1
25 20 15 10 5
Coal Hydro Biomass
Oil Nuclear
Natural_Gas New&Renew
0 2010
2020
2025
2030
Year
Fig. 2. Structure of Primary energy consumption in 2030 Fig. 3 shows the development of the electric power sector to the year 2030 under the Base case. In this case, the quantities of gas combined cycle and hydro power plant increase steady and get maximum level in the period 2025-2030. The quantities of renewable and oil power plant have small value. Nuclear power plant is introduced to the year 2020 with 2000 MW and the year 2030 with 6000 MW. The quantity of coal-fired power plant increases rapidly after the year 2020.
35
Coal_ppl Oil_ppl Nuclear_ppl
NaturalGas_ppl Hydro_ppl Renew_ppl
Fig. 4. Power generation mix for the No_nuclear case Fig. 5 shows the changes in electric power generation under the ENV1 case, in which 5% of CO2 emission reduction per year between 2025-2030 referred to Base case is introduced. In this case, the changes happen in coal-fired and nuclear power plant. One part of coal-fired power plant, the main CO2 emission source, is replaced by nuclear power plant. Output of nuclear power plant increases rapidly, especially in the year 2030 with 6.57 MTOE compared with 3.16 MTOE in Base case.
30
35
25
30
Electricity, MTOE
Electricity, MTOE
2015
20 15 10 5
25 20 15 10 5
0 2010
2015
2020
2025
2030
Year Coal_ppl Oil_ppl Nuclear_ppl
0 2010
2015
2020
2025
2030
Year NaturalGas_ppl Hydro_ppl Renew_ppl
Coal_ppl Oil_ppl Nuclear_ppl
Fig. 3. Power generation mix for the Base case
NaturalGas_ppl Hydro_ppl Renew_ppl
Fig. 5. Power generation mix for the ENV1 case
― 300 ―
35
Coal import, MTOE
30
4. CONCLUSION Base No_nuclear
25
ENV1
20 15 10 5 0 2010
2015
2020
2025
2030
Year Fig. 6. Coal import for electricity generation Fig. 7 shows the CO2 emissions and Fig. 8 shows the SO2 emissions for 3 scenarios. In Base case, CO2 emission increases rapidly in the whole time range 2010-2030. CO2 emission in 2030 is 431MTon compared with 109 MTon in 2010. Although SO2 emission is not limited, the trend of SO2 emission is the same as trend of CO2 emission. 550
CO2, MTon
450
Base No_nuclear ENV1
350 250 150 50 2010
2015
2020
2025
2030 Year
Fig. 7. Trend of CO2 emission 2400
SOx, kTon
REFERENCES
Base No_nuclear ENV1
2100 1800 1500 1200 900 600 300 2010
2015
2020
2025
2030 Year
Fig. 8. Trend of SO2 emission
The paper presents MESSAGE model, a linear programming model supported by IAEA. The model is used to analyze energy development strategy considering CO2 limitation. The results are summarized as follows: - After 2020, Vietnam will exploit energy resources at maximum level. But due to shortage of energy, Vietnam should import coal, oil, electricity to meet energy demand. Without nuclear power developing, Vietnam has to import a big amount of coal for electricity generating in 2025-2030. In No_nuclear Case, coal import is 2.49 MTOE in 2025 and 29.52 MTOE in 2030. It means Vietnam has many difficulties in ensuring energy security. Nuclear power plant will be good answer for this problem; As for CO2, despite Vietnam is not required to take on any obligation on greenhouse gas reduction in the Kyoto Protocol, Vietnam should pay great attention to decreasing CO2 emission. With ENV1 case (5% CO2 reduction referred to base case in the period 2025-2030), apart of coal-fired power plant will be replaced by nuclear power plant. The installed capacity of nuclear power plant increases rapidly with 6000MW in 2025 and 13000MW in 2030. Vietnam lacks of finance and human resource to build such big capacity of nuclear power plant. One of the best solution for this problem may be Clean Development Mechanism (CDM). CDM can not only assist Vietnam to achieve sustainable development, but also assist developed countries to achieve their obligation of emission reduction promised in the Kyoto Protocol, and at the same time, provide opportunities for those who invest and convey their technology for Vietnam. The implication of CDM on energy development of Vietnam will be presented in another paper.
Asian Development Bank. Energy Policy Experience of Asian Countries. Manila, Philippin, 1987. Behram N. Kursunoglu, Stephan L. Mintz, Arnold Perlmutter (Ed.). Global Warming and Energy Policy. Kluwer Academic/Plenum Publishers, 2001. Bui Huy Phung, Bui Thanh Hung, et. al. Research on building the best reasonable strategy for development of Vietnam energy system in the period 2005-2030. Final report. Institute of Energy Science, Vietnam Academy of Science and Technology, 2006. Derek W. Bunn, Erick R. Larsen (Ed.). Systems Modelling for Energy Policy. John Wiley & Sons. 1997. J. Fr. Hake (Ed.), et. al. Advances in Systems Analysis: Modelling Energy-Related Emissions on a National and Global Level. Forschungszentrum Juelich GmbH,1994.
― 301 ―
Hydrometeorological service (HMS). Vietnam National Strategy Study on Clean Development Mechanism. Hanoi April 2002. Ibrahim Kavrakoglu (Ed.). Mathematical Modelling of Energy System. Sijthoff & Noordhoff, 1981. International Atomic Energy Agency (IAEA). MESSAGE - Model for Energy Supply Strategy Alternatives and their General Environmental Impacts. Vienna, Austria, 2007. Jean-Baptiste Lesourd, Jacques Percebois, Fransois Valette. Models for Energy Policy. Routledge. London, 1996. S. Jebaraj, S. Iniyan. A review of energy models. Renewable and Sustainable Energy Reviews 2006; 10:281-311. Joel N. Swisher, Gilberto de Martino Jannuzzi, Robert Y. Redlinger. Tools and Methods for Integrated Resource Planning – Improving Energy Efficiency and Protecting the Environment. UNEP & RISO. Denmark, 1997. Marion Hersh. Mathematical Modelling for Sustainable Development. Springer. Germany, 2006. The Energy Data and Modelling Center, The Institute of Energy Economics. EDMC Handbook of Energy & Economic Statistics in Japan. Japan, 2007. Ulrich Bartsch, Benito Mueller, Asbjorn AAheim. Fossil Fuels in a Changing Climate: Impacts of the Kyoto Protocol and Developing Country Participation. Oxford University Press, 2000.
Bui Thanh Hungg received the B.E. (1995), M.E. (1997) degrees in energy engineering from Hanoi University of Technology. He is a lecturer at Department of Thermal Energy System, Institute of Heat Engineering and Refrigeration, Hanoi University of Technology. His current interests include energy system analysis and modelling, energy conservation and efficiency, thermal power plant. Hoang Ba Chuu received B.E (1971) degree in energy engineering from VUT – Brno (Czech Republic), D.E (1976) degree in energy engineering from CVUT (Czech Republic). He is a Professor, Department of Thermal Energy System, Institute of Heat Engineering and Refrigeration, Hanoi University of Technology. His current interests include turbomachinery, thermal power plant, energy conservation and efficiency.
― 302 ―
Bui Huy Phungg received B.E (1965) degree in thermal energy engineering from Hanoi University of Technology (Vietnam), D.E (1971) degree in energy planning in Romania. He is a Professor, Institute of Energy Science, Vietnam Academy of Science and Technology. His current interests include integrated resource planning, energy policy, clean development mechanism.
RESIDUAL TREND AND HALF-LIFE TIME OF DDT IN SURFACE SOILS FROM BACNINH, VIETNAM Vu Duc Thao 1* , Vu Duc Toan 2 1 2
Hanoi University of Technology, 1 Dai Co Viet Street, Hanoi, Vietnam Hanoi Water Resources University, 175 Tay Son Street, Hanoi, Vietnam
*Corresponding to: V.D. Thao
Abstract
Dichlorodiphenyltrichloroethane (p,p’-DDT) and its metabolites (p,p’-DDE, p,p’-DDD) were analyzed in the surface soils of Bacninh, Viet Nam. Forty representative soil samples were collected from Bacninh town and three surrounding districts. The sampling locations were chosen at random in February 2006, with an attempt to get them evenly distributed over Bacninh province. The levels of the DDT and its metabolites in the surface soils of Bacninh were investigated by means of gas chromatography coupled with mass spectrometry. In agricultural areas, ΣDDT concentrations ranged from
improving image on renewable energy. Therefore, this paper discusses the following power supply systems: reducing the electricity receiving power with the generation at a WG (wind generator) which is a new installation and existing PV (photovoltaic) power generation facilities. In addition, a battery can change output power and reduce contract electricity at the peak period, realized by charged power at night period, resulting in cost cut. These facilities are sown in Fig.1. This paper considers about the reduction of the electricity rate by reduction of the contract electricity and the reduction of the receiving power. In addition, this paper discusses the initial cost of a wind generator and the battery, evaluating loss of battery and the cost performance.
(a) NaS (sodium-sulfur) battery
(b) WG (wind generator)
(a) PV (photovoltaic) module
(d) PV indicator Fig. 1. Power facilities
― 287 ―
1. INTRODUCTION Now a day because of the deregulation of the electricity business, electricity business is open to any place, not just the electric power company. In addition, the generation with the distributed power supply attracts its attention from two aspects, many device having little carbon dioxide discharges generally and the possibility of the reduction of the electricity bill [1]. A simple model is constructed which evaluates the generator dynamics using software (MATLAB / SIMULINK). Fig.2 is the outline chart of this system. The storage battery is controlled with PC. The control aimed for “stabilization of the output”, “Decrease of the contract electric power”, and, “Effective use of the electric power at nighttime” is to be scheduled on the PC. Disclosing energy usage condition to the average student is also a target of this study for energy education. 2. ELECTRIC POWER SYSTEM MODEL Simulating model throughout theoretical studies is importance factor for success of the researches. The model consists of generators model and load model and control center model. The model output the signal which added the generators out put to P-tie (tin-line power flow on the feeder from utility) and a difference with the load. the model calculates a frequency deviation from a difference of the electricity then decides the output of P-tie based on it. The model feeds back the output of P-tie and decides output of a battery in the control center. And the model simulates its dynamics.
Generators
a WG
d
c
Utility grid
BT
PC PV
b University load
Fig. 2. University power facility model
Fig.3. shows the battery system, considering the electricity loss caused by battery itself and the corresponding power converter. Loss with a case of 10% and a case of 20% are calculated. Fig.3 is the former 10% loss model. When the amount of the electric power is ordered as a command from the control center, the loss is considered though this model as index SOC, which should be within limitation [2]. Fig.4. shows the load curve that the consumption electricity of the university, obtained from recorded value at a day of July. The reason of focusing July is it is the most electricity demand period during a year. Fig.5. and Fig.6 show assumed output of wind generator and photovoltaic power generation. Both of them are rating 20kW [3].
Fig. 3. Battery system model
― 288 ―
reduction in the amount of the payment for metered electric power and the contract electric power is calculated. This university is contracting to IPP (Independent Power Producer). Table.1 shows the unit price used in the IPP. Table.1. Unit price of new IPP Unit price Contract electric power Preliminary line Receiving power(summer) Receiving power(other season) Amount of fuel adjustment Fig. 4. Load curve
(yen/kW) 1510 60 8.25 7.8 1.28
The contract electricity cost is decided depending on the amount of the receiving power at the peak. Because the introduced storage battery is 20kW, it is 20kW contract electric power decrease. And a basic charge and the preliminary line expense can be reduced by this. Moreover, a basic charge is the discount by moment of power factor, and when moment of power factor is improved on the demand ground, is discounted 15% or less. The value of power factor of university facility is 1.0. Therefore, if it is calculated as followings; Basic charge: 1,510×20×(185-1.0×100)=25,670 [yen] Preliminary line expense: 60×20=1,200 [yen] Total: 26,870 [yen] When the amount of the receiving power decreases, the cost that can be reduced.. Because the unit price of the amount of the receiving power assumes summer in this study, unit price in summer season is used. When the average output of wind power generation is assumed to be 5kW, electricity will be generated by 3600 kilowatt-hour in year. Receiving power reduction: 8.25×3600=29,700 [yen] Total: 26,870 29700 u 12 678,840 [yen/per year]
Fig. 5. WG output
B. Evaluation of initial cost The equipment newly established by this research is a storage battery and a wind generator. First of all, an initial cost of the storage battery is calculated. Peak period is about four hours.. Fig.7 is a power generation unit price for electrical discharge times. 㪠㫅㫀㫋㫀㪸㫃㩷㪺㫆㫊㫋
Fig. 6. PV output. Two cases of 10 % and 20 % an internal loss of the storage battery are evaluated. Considerable difference can not be identified but 20% loss discharge time is longer than 10% loss discharge time. Moreover, the frequency is within 50Hz±0.1Hz that is same to in East Japan, which means stability problem does not exist.
㪬㫅㫀㫋㩷㫇㫉㪺㪼 䋨㪈㪇㪇㪇㫐㪼㫅䋯㫂㪮䋩㪅
㪋㪇㪇 㪊㪇㪇
㪣㪼㪸㪻㩷㪸㪺㫀㪻 㪥㪸㪪 㪩㪝
㪉㪇㪇 㪈㪇㪇 㪇 㪇
3. COST EVALUATION
A. Evaluation of contract charge Next, how much cost can be reduced because of the
― 289 ―
㪌 㪈㪇 㪜㫃㪼㪺㫋㫉㫀㪺㪸㫃㩷㪻㫀㫊㪺㪿㪸㫉㪾㪼㩷㫋㫀㫄㪼䋨䌨䋩
Fig.7. Power generation unit price.
The lead-acid battery is the cheapest during four hours in the ratings output time. If the longevity of the storage battery is calculated as 15 years, the calculation result is as follows. Initial cost of battery system 230,000×20÷17=310,000[yen] Next, it is as for an initial cost of the wind generator. The unit price of a wind generator that is medium-scale or small-scale is about 240,000-370,000 [yen/kW]. Now two cases of 240,000 [yen/kW] and 370,000 [yen/kW] are assumed. An initial cost of the wind generator is as follows assuming lifetime is17 years. Initial cost of wind generator A: Case of 240,000[yen/kW] 240,000×20÷17=280,000[yen/per year] B: Case of 370,000[yen/kW] 370,000×20÷17=30,000[yen/per year] Finally, the result of the cost evaluation is as follows. A: Case of 240,000(yen/kW) 678,840Ƚ(310,000+280,000)=90,000[yen/per year] B: Case of 240,000(yen/kW) 678,840Ƚ(310,000+430,000)=60,000[yen/per year] Therefore, it becomes a cost reduction in about 90,000 yen a year in case A. However, about 60,000 yen cost increases during year in case B. No economical advantage is found in case B. 4. CONCLUSIONS Installation of PV and/or WG system is getting popular among small customers associated with increasing concern on environmental issues and countermeasures [4]-[7] . However, feasibility study should be conducted before sating planning, including initial and running costs, understanding electricity bill system. Contribution to the management section is also important factor to run this kind of planning. Further research will focus on critical conditions for the facility investment and appropriate operation of the generation systems.
[4] M. Matsubara, G. Fujita, T. Shinji, T. Sekine, A. Akisawa, T. Kashiwagi, R. Yokoyama, ‘Supply and Demand Control of Dispersed Type Power Sources in Micro Grid’, Intelligent System Appreciation to Power Systems 2005 (ISAP 2005), No.10 (2005-11, Washington, USA) [5] Y. Takemoto, G. Fujita, K. Hasegawa, K. Koyanagi, T. Funabashi, R. Yokoyama, ‘Experimental Study on Rotary Frequency Converter’, Intelligent System Appreciation to Power Systems 2005 (ISAP 2005), No.60 (2005-11, Washington, USA) [6] Y. Takemoto, G. Fujita, R. Yokoyama, K. Koyanagi, T. Funabashi, W. Chen, ‘Design Consideration and Verification by Experiment of Rotary Frequency Converter’, International Conference on Electrical Engineering (ICEE) 2006, MI1-9 (2006-7, YongPong Resort, Korea) [7] M. Matsubara, G. Fujita, T. Shinji, T. Yamakami, A. Akisawa, T. Kashiwagi, R. Yokoyama, ‘Suitable Control and Supply of Micro Grid by Installation of Battery’, International Conference on Electrical Engineering (ICEE) 2006, SE1-09 (2006-7, YongPong Resort, Korea) Goro Fujita was born in January 1970. He received the B.E., M.E. and Ph.D degrees in electrical engineering from Hosei University, Tokyo, Japan in 1992, 1994 and 1997 respectively. In 1997, He was a research student of Tokyo Metropolitan University. Since 1998, he is in Shibaura Institute of Technology, Tokyo, Japan. At present he is an associate professor. His interest is in power system control including dispersed power sources. He is a member of the IEE of Japan, the Society of Instrument and Control Engineers (SICE) of Japan, and IEEE. He is also a Professional Engineer in Japan (Electrical and Electronics field)
REFERENCES [1] S. Shiki, “Autonomous Decentralized Control of Supply and Demand by Inverter Based Distributed Generations in Isolated Microgrid”, The Transactions of The Institute of Electrical Engineering of Japan, Vol.127-B, No.1, 2007 (in Japanese) [2] Y.Ueda, “Advanced Analysis of Grid-connected PV System’s Performance and Effect of Battery”, The Transactions of The Institute of Electrical Engineering of Japan, Vol.127-B, No.1, 2007 (in Japanese) [3] Y.Hayashi, “Cooperated operation form in supply of electric power system corresponding to expansion of decentralized power supply introduction”, The Transactions of The Institute of Electrical Engineering of Japan, Vol.127-B, No.1, 2007 (in Japanese)
― 290 ―
3rd SEATUC Symposium, Feb. 2009 Johor Bahru, Malaysia
CATALYZED LIQUEFACTION OF EMPTY PALM FRUIT BUNCH (EPFB) IN SUB-CRITICAL WATER Javaid Akhtar, Soo Kim Kuang, NorAishah Saidina Amin Chemical Reaction Engineering Group (CREG) Faculty of Chemical & Natural Resources Engineering, Universiti Teknologi Malaysia, 81310 UTM, Skudai, Johor, Malaysia Corresponding Author : Nor Aishah Saidina Amin Tel: 07-5535588, Fax: 07-5581463, E-mail: [email protected] ABSTRACT Effect of alkaline catalysts (NaOH, KOH & K2CO3) on EPFB biomass liquefaction is investigated under subcritical water conditions in a batch type reactor operating at 270oC and 20 bars for a period of 20 minutes. In this study catalyst performance and suitable biomass to water ratio in order to support higher EPFB conversion, liquefied hydrocarbon yields and lignin degradation were screened. According to the results through GC-MS, FTIR, and UV spectrometer, one typical run could achieve 68 % of liquid hydrocarbons with 72.4 % EPFB conversion and 65.6 % lignin degradation in 1.0 M and 2:10 biomass to water ratio operating at the above said conditions. Liquid output was only 36.4 % when subjected to the same operating conditions in the absence of catalyst. Furthermore, high biomass to water ratios beyond 2:10 decreased both solid mass conversion and liquid hydrocarbons. The order of the catalyst reactivity was in the following order: K2CO3 > KOH > NaOH. Phenols and esters were dominant in the liquid products and K2CO3 yielded the highest value of phenols. The alkaline catalyzed process assisted with hot water treatments seemed promising for production of phenolic-rich bio oils from EPFB. 1
INTRODUCTION
Biomass supplies 12-14 % of energy requirements worldwide and shares around 35-50 % in developing countries. Furthermore, fossil energy depletion and its uneconomical extraction have spurred the idea of utilizing biomass in various applications like bio-fuels and bio- chemicals. It is widely accepted that utilizing biomass as energy source would bring forth social and economical benefits in less developed regions of the world. Other benefits include i) sustainable energy through renewable biomass ii) CO2 neutral substitute of
fossil fuel iii) reduction in gases like NOx, SOx due to less sulfur and nitrogen contents present in biomass and iv) abundant availability in all regions of world (Demirbas et. al. 2000, Kucuk et. al. 1997 Mckendry et. al. 2002). Empty palm fruit bunch (EPFB)-biomass used in current study, is one of the major wastes of oil palm plantations. EPFB amounts to 4.4 tonnes per hector per year, approximately concedes 20.4 % of total oil palm biomass. Total 73.4 million tonnes of palm biomass, in Malaysia for example, supplies 14.89 million tonnes EFB and 37.65 million tonnes world wide on yearly basis (Tau et. al. 2007, Yang et. al. 2004). Converting cheap abundant amounts of renewable palm EFB into valuable commodities like bio-fuels would bring forth energy security and social benefits in countries like Malaysia, Indonesia, Thailand and tropical African countries. Liquefaction of biomass feedstock to liquids like bio-fuels and chemicals, is one of the major alternatives for biomass utilization (Chunbao et. al. 2008, Mohan et. al. 2006, Bridgewater et. al. 1995, 2001). Biomass is liquefied into fuels and chemical based commodities through thermal, thermochemical, biochemical and biological routes. Biological means are quite economical for such liquefactions yet very low conversion of solid mass makes these processes unfit for large scale applications. Conversely, liquid yield is quite high (5070 %) in thermal and thermochemical processes. However still issues like low product quality, high temperatures and pressures daunt industrial applications of such processes. In thermochemical methods, direct and indirect conversions are two viable options for biomass liquefaction. Bio fuels and chemicals can be obtained indirectly from biomass gasification via Fischer-Tropsch conversion (Mark et. al. 2004, Charlo et. al. 2004) while direct processes like pyrolysis, extractions, and hydrogenations convert biomass solid to liquids. Direct processes are suitable choices in recent times due to
― 291 ―
simpler processing steps permitted with post- processing of liquid oils in order to increase fuel value. However, selection of a suitable process depends on various factorsbiomass types, product utility, economic aspects, and environmental conditions etc (Chunbao et. al. 2008, Peter et. al. 2002). Fast pyrolysis, wherein biomass is heated rapidly within 400- 850oC at atmospheric pressure usually, has reputation of yielding high amounts of products. However, problems like high water contents in product liquids, chars and a well mixed amount of organic compounds lower product quality and its potential application. Sub and supercritical extraction of biomass in solvents like water, methanol, ethanol, ether and CO2 etc produces bio oil dominated by phenols and esters etc. Thus, super/sub critical liquefaction may be a suitable option for EPFB liquefaction for which current study is carried out. The effect of catalysts like NaOH, Na2CO3, KOH, and K2CO3 was studied on sub critical water liquefaction of woody biomass at 208oC (Selhan et. al. 2005). Uncatalyzed liquefaction of Cunninghamia Lancelolata in water medium yielded 24 % of liquid oils at 280-360oC and 8 gm biomass/100 mL water conditions (Yixin et. al. 2003). In another development, rice straw liquefaction in presence of various liquids like water and ethanol, 2propanol under low temperature and pressure was studied (Yuan et. al. 2007). Depolymerization of lignin by alkali at 290oC in supercritical methanol illustrated lignin decomposition was proportional to base strength (Miller et. al. 1999). Effect of temperature on liquefaction of woody biomass in presence of Na2CO3 catalyst within 280-420oC was studied and 380oC as the optimal temperature was recommended (Yejian et. al. 2007). Water-phenol solvent system to liquefy wood biomass at moderate 250oC in presence of catalysts like NaOH, CuSO4 and (NH4)2SO4 was studied to investigate the effect of catalyst concentration, biomass to solvent ratios, pH of mixture and biomass types on liquids and residues production (Maldas et. al. 1996). In this work, empty palm fruit bunch (EPFB) was liquefied in hot water at moderate operating conditions (200oC, 20-40 bars) and 20 minutes in presence of KOH, K2CO3, and NaOH catalysts to compare liquid yields and biomass conversions in catalytic and non-catalytic runs. Liquids and solids compositions as well as lignin decomposition were analyzed through GC-MS, FTIR and UV Spectrophotometer. The objectives of this work were to investigate effect of base catalysts and suitable EPFB/water ratio to produce bio-chemical rich bio oil. 2
EXPERIMENTAL
Materials Empty palm fruit bunch (EPFB) was collected from FELDA oil palm company in Bukit Besar Kulai, Malaysia. The feed biomass was grounded to particle size ranged from 0.5 mm to 1.0 mm. Sulphuric acid and alkaline catalysts were obtained from Mallinckrodt Chemical Inc., USA and Quality Reagent Chemicals (QREC)., NZ, respectively.
2.2
Hydro-liquefaction The experimental rig consisted of a stainless steel autoclave, an electrical furnace and a product recovery system supported by water cooled condenser as shown in figure 1. Catalyst and crushed EPFB were mixed with water in a specified biomass to water ratio in the autoclave. Temperature, 270oC and pressure, 20-45 bars were maintained for 20 minutes residence times in this base catalyzed hot water liquefaction of EPFB. During reaction small quantity of gas was purged in a sampling tube in order to control pressure and avoid vapors loss. After 20 minutes of heating at 270oC, the operation was halted and cooled in open atmosphere followed by water cooling. Collected product was separated as unconverted solid mass and liquid portions. Effective biomass to water ratio, effect of basic catalysts and its concentration, were parameters notified in the above said procedure.
Gas Release
Pressure Gauge Thermocouple
Nitrogen Furnace Water
Autoclave Reactor Fig. 1
Experimental setup
2.3 Analysis 2.3.1 Kappa Number Test In this experiment, the kappa number was derived from the ratio of the absorption spectral intensities at 546 nm wavelength measured at the beginning and end of the reaction of EPFB with permanganate through UV spectrophotometer analysis. Details of procedure can be followed elsewhere (Chai et al. 2000). Kappa number was calculated according to the following formula:
2.1
Where K = Kappa number, a = Volume of 0.02mol/L permanganate solution used in experiment, w = Mass in grams of the solid sample used, Ae = Spectral intensities of blank solution, Ao = Spectral intensities of solution with the solid product
― 292 ―
2.3.2
FTIR analysis The solid residue collected at each operating condition was analyzed by Spectrum One FT-IR spectrophotometer (Perkin-Elmer, Ltd). FTIR analysis determined the structure of the char after the subcritical water treatment. FTIR spectra of the samples were recorded on the FTIR-Spectrum One with the KBr pellet technique. EPFB residue is mixed with laboratory grade KBr, grounded and pelletized with a hydraulic press. Pellet was tested through infrared spectrum in a range of 4000 to 370cm-1.with a resolution of 4cm-1. 2.3.3
GC-MS Spectroscopy GC-MS spectroscopy equipped with capillary column and selective detector (MSD) analyzed liquid product obtained through experiments. A calibrated Agilent 6890 series GC-MS equipped with a flame ionization detector and a capillary column (SPBTM-5, 30m x 0.32mm x 0.25µm) with helium gas as the carrier was used to perform the analysis. Liquid product of 100 µl was pipetted out each from the bottom and upper layer and top up to 10 mL with methanol as diluents in a measuring cylinder. The mixture was shaken to ensure complete mixing. Next, it was filtered into a GC vial and was ready for testing. The GC oven would be kept at 1800C for 2 minutes, ramped at 40C/min up to 2000C for 10 minutes. 3
RESULTS AND DISCUSSION
3.1
Effect of catalyst types Basic cataysts significantly degraded EPFB compared to non-catalystic run in all three parameters discussed in figure 2. Solid conversion jumped from 36.4 %, without catalyst, to 72.4 % in K2CO3 solution. Similar trend was realized in liquid yield and lignin degradation. Results obtained from NaOH, KOH treatmetns were within the said extremes and pretty similar to each other. K2CO3 > KOH > NaOH was the catalyst reactivity order for EPFB degration proved through these experiments. This may inform about superiroty of carbonates in EPFB degration than to hydoxides which may be due to conversion of K2CO3 into bicarbonates as secondary catalyst.
K2CO3 presence in supercritical hydropyrolysis of glucose at 450-550oC increased liquid yield proving effectiness of such catalysts in gasification process (Sinag et. al. 2003). Low temperature base catalyzed liquefaction of wood at 280 oC for 15 minutes also confirmed the sequence of our present study: K2CO3 > KOH >Na2CO3> NaOH. This may also support potasium bases are effective than sodium (Selhan et. al. 2005).
Fig. 2 Effect of various catalysts on amount of liquids in EPFB liquefaction 3.2
Effect of K2CO3 concentration EPFB liquefaction was further analyzed with various concentration of K2CO3 solution at 270oC, 5gram/25 ml water ratio. K2CO3 1.0 M yielded maximum conversion, liquids and lignin degradation. Catalyst concentration supported EPFB breakdown prior to 1.0 M K2CO3 and discouraged liquid yield beyond 1.0 M. K2CO3 possibly promoted re-polymerization at high concentrations. Solid conversion and liquid yield were least affected by catalyst concentrations while lignin degradation varied comprehensively (figure 3). Almost 10 % increase in liquids yield was noticed with 40 % extra lignin degradations. This proved almost one fourth effect of lignin on liquid yield as can be seen by original composition of EPFB wherein lignin is about 20 % of total lignocelluloses (Luis et. al. 1999).
Fig. 3 Effect of K2CO3 concentraion on EPFB conversion and liquid yields Higher conversion with increasing K2CO3 concentrations after analyzing effects of various K2CO3 solutions (0.235 M, 0.47 M, and 0.94 M) on biomass up gradation at 280oC was reported (Selhan et. al. 2006). Furthermore, in our study K2CO3 solution discouraged conversion beyond 1.0 M K2CO3 concentrations.
― 293 ―
3.3
Effect of biomass to water ratio Higher concentrations of EPFB biomass decreased amount of liquids and lignin degradation. As from figure 4, 68% liquids were achieved with 2:10 EPFB to biomass ratio converting 72% of solid mass at experimental conditions of 270oC, 40 bars, 1.0 M K2CO3 solution. 8:10 EPFB to biomass ratio resulted in the lowest degradation, liquids and solid mass conversion. In a similar study, cunninghamia lanceolate was liquefied in water in presence of 280-360oC with different biomass to water ratios (8g, 10g, 12.5 g per 100 ml each) (Yixin et. al. 2003). Results proved high amount of biomass led to low conversion and liquid yield as said in our study.
Table 1 Percentages of organic groups obtain through GC-Mass analysis of liquid oil under various conditions Reaction Condition Temperature = 270 oC Pressure = 40bar Reaction time =20min
% Area Phenol
Methyl Ester
Benzoic acid
5g EPFB/25ml Water Without catalyst
-
26.44
-
K2CO3 1.0 M
60.08
39.92
-
KOH 1.0 M
18.40
81.6
-
NaOH 1.0 M
6.00
86.45
-
K2CO3 0.1 M
1..33
2.88
2.89
K2CO3 0.5 M
1.77
63.48
4.85
K2CO3 1.0 M
60.08
39.92
-
K2CO3 1.5 M
34.50
68.50
-
K2CO3 2.0 M
34.79
65.21
-
K2CO3 1.0 M
Fig. 4 Effect of EPFB/water ratio on EPFB conversion, lignin degradation and liquid yields Although smaller biomass to water ratio resulted in better conversion, the use of large amounts of water should be avoided as the high energy inputs incurred high cost. 3.4
Liquid oil composition Liquid products distribution depended strongly on catalyst types and biomass to water ratio as shown in table 1. For 5:25 EPFB to water ratio, maximum ester yield was 86.45 % in 1.0 M NaOH solution while 1.0 M K2CO3 produced 60.08 % phenols. Subcritical hot water system could produce fuel grade bio oil dominated by phenols and esters (see table 1). Similar results have been published in literature (Selhan et. al. 2006). EPFB and char characterization Fourier transform infrared (FT-IR) spectroscopy characterized raw EPFB and chars obtained in liquefaction process said above within wave number range 4000 – 370 cm-1 (figure 5). Various bands in spectrum were identified as O-H (3446.9 cm-1), methoxyl (2924.0 cm-1), methoxyl (2924.0 cm-1), aliphatic C-H bonds (3000-2860 cm-1), stretching of aromatic C=C groups (1680-1570 cm-1), stretching and bending modes of saturated aliphatic hydrocarbon (2980-2850 and 14001300 cm-1, respectively) and bending of aromatic C-H groups (900-700 cm-1).
2.5gEPFB/25ml Water
0.61
94.29
1.72
5gEPFB/25ml Water
60.08
39.92
-
10gEPFB/25ml Water
0.44
41.34
-
15gEPFB/25ml Water
7.63
-
24.28
From figure 5, it is accessed for no catalyst runs chars showed sharp peaks within 1680-1570 cm-1 band region indicating presence of C=C bonds wherein no such bonds were found in case of catalyzed chars (K2CO3, KOH, NaOH). This proved the reactive nature of catalyzed chars under said process conditions. However, peaks of O-H bonds (at wave number of 3440-3450cm-1) which were still present in catalyzed char residues reflected stability of phenols and alcohols.
3.5
Fig. 5 FTIR analysis of raw EPFB, and residue char on concentration
― 294 ―
CONCLUSION Among various base catalyst NaOH, K2CO3 and KOH screened in this study, K2CO3 produced maximum liquids being 68.0 % and degraded 65.62 % lignin under the same operating conditions. Catalysts reactivity order is confirmed as K2CO3 > KOH > NaOH based on liquid yields and solid mass conversion. Furthermore, 1.0 M K2CO3 produced the maximum value of solid mass conversion, lignin degradation and liquids when compared with other concentrations of same catalyst. Possibly at high K2CO3 concentrations beyond 1.0 M, repolymerization of fragmented components reduced liquid yield. Higher amounts of EPFB mass also decreased liquid yields and the optimum value obtained through experiments was 2 g/25 ml water. Liquid bio oil thus produced dominantly consisted of phenols and esters according to GC-MS analysis. This confirms superiority of sub critical technique compared to pyrolysis for example wherein a large number of liquid product components daunt oil quality and increase post processing costs. REFERENCES Carlo, N.H., Andre´, P.C.F., Herman, D.U., and Harold, B., Production of FT transportation fuels from biomass; Technical options, process analysis and optimization, and development potential, Energy, vol. 29 pp 1743–1771, 2004 Chai, X.S., Luo, Q. and Zhu, J.Y., A Simple and Pratical Pulp Kappa Test Method for Process Control in Pulp Production, Institute of Paper Science and Technology, Atlanta, Georgia, 2002 Chunbao, X., and Timothy, E., Hydro-liquefaction of woody biomass in sub and supercritical ethanol with iron based catalysts, Fuel, vol. 87, pp 335-345, 2008 Malsdas, D., and Shiraishi, N., Liquefaction of biomass in the presence of phenol and H2O using alkalis and salts as catalysts, Pregamon, pp 74-8, 1996 Miller, J.E., Evans, L., Littlewolf, A., and Trudell, D.E., Batch micro-reactor studies of lignin and lignin model compound depolymerization by bases in alcohol solvents, Fuel, vol. 78, pp 1363–1366, 1999 Tau, L.K.Y., Keat, T.L., Abdul, R.M., and Subhash, B., Potential of hydrogen from oil palm biomass as a source of renewable energy worldwide, Energy Policy, vol. 35, pp 5692-5701, 2007 Kukuk, M., and Demirbas, A., Biomass conversion processes, Energy Conversion Management, vol. 38, pp 151-165, 1997 Luis, F.G., Óscar, J. S., and Carlos, A. C., Process integration possibilities for biodiesel production from palm oil using ethanol obtained from lignocellulosic residues of oil palm industry, Bioresource Technology, Vol. 100, no. 3, pp 1227-1237, 1999 Mark, J.P., Krzysztof, J.P., and Frans, J.J.G.J., Exergetic optimisation of a production process of Fischer–Tropsch fuels from biomass, Fuel Processing Technology, vol. 86, pp. 375– 389, 2004
Minowa, T., Fang, Z., and Tomoko, O., Cellulose decomposition in hot compressed water with alkali or nickel catalyst, J. Supercritical Fluids vol. 13, pp. 253259, 1998 Peter, M., Energy production from biomass (part 1): Overview of biomass, Bioresource Technology, vol. 83 pp. 37-46, 2002 Peter, M., Energy production from biomass (part 2): conversion technologies, ‘Bioresource Technology, vol. 83, pp. 47-54, 2002 Selhan, K., Thallada, B., Akinori, M., Yusaku, S., Toshiyuki, O., and Tamiya, K., Low temperature treatment of wood biomass analysis of liquid products, Chemical Engineering Journal, vol. 108, pp. 127-137, 2005 Selhan, K., Thallada, B., Akinori M., and Yusaku S., Hydrothermal upgrading of biomass: Effect of K2CO3 concentration and biomass/water ratio on products distribution, Bioresource Technology, vol. 97, pp 90–98, 2006 Sinag, A., Kruse, A., and Schwarzkopf, V., Key compounds of the hydropyrolysis of glucose in supercritical water in the presence of K2CO3, Ind. Eng. Chem. Res., Vol. 42, pp. 3516-3521, 2003 Yuan, X.Z., Li H., Tong, G.M., Tong, J.Y., and Xie, W., Sub and supercritical liquefaction of rice straw in the presence of ethanol-water and 2-propanol-water mixture, Energy, vol. 32, pp. 2081-2088, 2007 Yang, H.P, Yan, R., Chen, H.P, Lee, D.H, Liang, D.T, and Zheng, C.G, Pyrolysis of palm oil wastes for enhanced production of hydrogen rich gases, Fuel Processing Technology, vol. 18, pp. 1814-1821, 2004 Yejian, Q., Chengji, Z., Jian, T., and Jianhui, H.,Structural analysis of bio-oils from sub and supercritical water liquefaction of woody biomass, Energy vol. 32, pp. 196-202, 2007 Yixin, Q., Xiaomin, W., and Chongli, Z., Experimental study on the direct liquefaction of Cunninghamia lanceolata in water,Energy, vol. 28, pp. 597-606, 2003
― 295 ―
Prof. Dr. Nor Aishah Saidina Amin is the deputy dean for research and post graduate studies at the Faculty of Chemical and Natural Resources Engineering UTM, Malaysia. She also heads the Chemical Reaction Engineering Group (CREG). She received her PhD degree (1996) in chemical Engineering from Illinois Institute of Technology (IIT), Chicago, USA. Her research interests include bio-fuels, plasma chemical technologies, and methane reforming.
Javaid Akhtar is a PhD Chemical Engineering student at CREG UTM. He completed his Masters in chemical engineering (2005) from KAIST, South Korea and B.Sc (2002) from Punjab University, Pakistan.
Soo, Kim Kuang is a final year undergraduate chemical engineering student at the chemical reaction engineering laboratory (CREG), Universiti Teknologi Malaysia (UTM)
― 296 ―
APPLICATION OF OPTIMIZATION MODEL TO ANALYZE THE DEVELOPMENT OF VIETNAM ENERGY SYSTEM CONSIDERING CO2 EMISSION CONSTRAINT Bui Thanh Hung1, Hoang Ba Chu1, Bui Huy Phung2 1. Department of Thermal Energy System, Institute of Heat Engineering and Refrigeration, Hanoi University of Technology 2. Institute of Energy Science, Vietnam Academy of Science and Technology
ABSTRACT In Vietnam, energy consumption has been increasing because of rapid industrialization and economy development. At present, Vietnam is the energy producer and exporter, but as forecasting Vietnam need to import coal for electricity production after the year 2020. The paper presents the application of MESSAGE model, an optimization model developed by IAEA, to analyze the development of Vietnam energy system considering CO2 emission constraint. The analysis shows that using nuclear power plant and application of clean development mechanism (CDM) can be efficient measures for achieving energy security, decreasing CO2 emission and sustainable development for Vietnam. Keywor dss: Optimization model, energy system, CO2 emission 1. INTRODUCTION In Vietnam there are some applied projects and studies analyze the optimal development strategy for electric power system and the whole national energy system (Bui Huy Phung, et. al., 2006). Some optimization models are used such as MARKAL, EFOM-ENV, MESSAGE,... But in most of these studies, the impacts of environment factors on energy system were not examined. In recent years, with economy developing rapidly the energy consumption increases promptly. GDP increased from 20.21 mill. USD in 1995 to 53.66 mill. USD in 2005. Energy demand increased from 7.16 MTOE in 1995 to 20 MTOE in 2005. Electricity generation increased from 14.65 TWh in 1995 to 53.46 TWh in 2005. Vietnam now is an energy producer and exporter. In 2005, energy exportation of Vietnam is: 18 Mton of coal, 18 Mton of crude oil. This energy exportation can continue to the year 2020. But after 2020, as forecasting, Vietnam has to import coal for electricity generation. Many problems related to energy supply and use must
be addressed for Vietnam such as environment pollution, energy conservation and efficiency, energy security and sustainable development. In this study, we use MESSAGE model, an optimization model transferred by IAEA, to analyze and develop national, cost-effective strategies for CO2 emission reduction. Beside that, we also analyze to point the important role of nuclear power plant to ensure energy security for Vietnam in the future. 2. METHODOLOGY 2.1 Description of MESSAGE model (IAEA, 2007) MESSAGE (Model for Energy Supply Strategy Alternatives and their General Environmental Impacts) is a tool for medium- to long-term planning of the operation and extension of energy supply and use systems. The MESSAGE model is a multi-period linear optimization model. A predefined demand vector for the planning horizon is to be optimally covered (with respect to one or several target functions) using the resources and technologies available and observing exogenous constraints. MESSAGE was originally developed at International Institute for Applied Systems Analysis (IIASA). The IAEA acquired latest version of MESSAGE and several enhancements have been made in it, most importantly addition of a user-interface to facilitate its application. The most recent version of the model is MESSAGE V. MESSAGE identifies the flow of energy from primary-energy resources to useful-energy demands that (1) is feasible in a mathematical and an engineering sense, and at the same time (2) represents the investment choices that lead to the least cost of all feasible energy supply mixes to meet the given energy demand. Engineering feasibility is ensured by making energy flows consistent with model constraints on primary-energy availability and extraction, energy conversion and transportation as well as on end-use technologies and limits on the environmental impact of
― 297 ―
energy conversion. Energy flows are further determined by constraints on the rate of new capacity installation, the substitutability among energy forms, renewable-energy potentials and others. One important technical feature of MESSAGE is the so-called mixed-integer option. Expressed in less technical terms, this means the ability of the model to consider fixed sizes of technologies. Minimization of the total system cost is the criterion used for optimization of the model developed using the MESSAGE. The total system cost includes investment costs, operation cost and any additional penalty costs defined for the limits, bounds and constraints on relations. For all costs occurring at later points in time, the present value is calculated by discounting them to the base year of the case study. The sum of the discounted costs is used to find the optimal solution. Calculating total cost, MESSAGE can use assumptions on specific costs of hundreds of individual technologies as they develop over time. The actual number of technologies is determined by the degree of detail included in the Reference Energy System (RES) and specified in the MESSAGE input files. The RES is the conceptual core of the MESSAGE model. It is a formal description of energy supply and demand in a given economy and is thus the basis for energy modeling exercise. In its most comprehensive form, it represents a given real-world energy system including resource extraction, imports and exports, all conversion technologies, energy transport and distribution, as well as the energy demand. Detailed description of the objective function and constraints can be found in references (IAEA, 2007; J. Fr. Hake, et. al., 1994). 2.2 Energy model considering CO2 constraint for Vietnam The Reference Energy System for Vietnam in this study is shown in Fig. 1. It includes 9 subsectors and is divided into 2 main categories: - Energy supply and conversion sectors: Coal, Naturalgas, Oil, Central power generation sectors; - Energy consumption sectors: Industrial, Agricultural, Commercial, Residential, Transportation sectors. To analyze the effects of limitation of pollution emissions on energy system, we add some constraints to the MESSAGE model. The constraints are the limitations of the total amount of pollutant, such as CO2, SO2, NOx. These limitations can be introduced of each time step t in the time range. The constraints are expressed by the following set of equations: i n
ECO2 ¦ i
i, t
u Xi ,t d LCO2t
1
i n
ESO2 ¦ i 1
i, t
u Xi ,t d LSO 2t
i n
ENOx ¦ i
i, t
u Xi ,t d LNOxt
1
Where Xi,t : fuel consumption of technology i in time step t; ECO2i,t: emission factor for CO2 of technology i in time step t; ESO2i,t: emission factor for SO2 of technology i in time step t; ENOxi,t: emission factor for NOx of technology i in time step t; LCO2t: maximum value of total amount of CO2 in time step t; LSO2t: maximum value of total amount of SO2 in time step t; LNOxt: maximum value of total amount of NOx in time step t; In summary, the energy model developed in this paper to study Vietnam energy system includes the linear optimization model built in MESSAGE and 3 additional constraints on emission limitation. With this energy model, we can analyze the effects of single reduction (CO2) or combined reductions of CO2, SO2 and NOX at the same time. 2.3 Description of Cases and assumptions In this study, the planning horizon starts from 2005 to 2030. Emissions of CO2, SO2, NOx are calculated based on emission factors provided by the Intergovernmental Panel on Climate Change (IPCC). The energy demand data, technology data and other input data for optimization model are used based on the current references (Bui Huy Phung, et. al., 2006). The paper analyzed 3 cases: Base case , No_nuclear case and ENV1 case. The Base case: - Indigenous resources are exploited with maximum capacity (in the year 2030, coal about 60-70 MTon, crude oil about 20 MTon, natural gas about 20 Billion m3 and hydro power about 80 TWh); - Nuclear energy is used as fuel for electricity generation in the period 2020-2030 with capacity of 2000-6000 MW. No_nuclear case - Nuclear energy is not used as fuel for electricity generation in the study period 2005-2030. - All other things are the same as in the Base Case. CO2 limitation case (ENV1): 5% reduction of CO2 emission - In this case, a 5% CO2 emission reduction per year between 2025-2030 is introduced. The CO2 reduction is referred to the Base Case; - All other things are the same as in the Base Case.
― 298 ―
Fig. 1. Structure of Energy System for Vietnam
― 299 ―
3. RESULTS AND DISCUSSION Fig. 2 shows the structure of primary energy consumption in 2030 for 3 scenarios. The changes in total amount of primary energy consumptions are small. But there is a big difference in structure between 3 scenarios. The main changes are in coal and nuclear energy portions. 180
Fig. 4 illustrates the changes in electric power generation under the No_nuclear case. The quantities of gas combined cycle, hydro, renewable and oil power plant are the same those in Base case. The changes are mainly in coal-fired power plant. Coal-fired output increases about 22% compared with Base case. Vietnam has to import huge amount of coal for electricity generation. Coal import in 2030 will be 29.52 MTOE in No_nuclear case and 20.68 MTOE in Base case (Fig. 6).
160
35
140 MTOE
120
30
Electricity, MTOE
100 80 60 40 20 0 Base
No_nuclear
ENV1
25 20 15 10 5
Coal Hydro Biomass
Oil Nuclear
Natural_Gas New&Renew
0 2010
2020
2025
2030
Year
Fig. 2. Structure of Primary energy consumption in 2030 Fig. 3 shows the development of the electric power sector to the year 2030 under the Base case. In this case, the quantities of gas combined cycle and hydro power plant increase steady and get maximum level in the period 2025-2030. The quantities of renewable and oil power plant have small value. Nuclear power plant is introduced to the year 2020 with 2000 MW and the year 2030 with 6000 MW. The quantity of coal-fired power plant increases rapidly after the year 2020.
35
Coal_ppl Oil_ppl Nuclear_ppl
NaturalGas_ppl Hydro_ppl Renew_ppl
Fig. 4. Power generation mix for the No_nuclear case Fig. 5 shows the changes in electric power generation under the ENV1 case, in which 5% of CO2 emission reduction per year between 2025-2030 referred to Base case is introduced. In this case, the changes happen in coal-fired and nuclear power plant. One part of coal-fired power plant, the main CO2 emission source, is replaced by nuclear power plant. Output of nuclear power plant increases rapidly, especially in the year 2030 with 6.57 MTOE compared with 3.16 MTOE in Base case.
30
35
25
30
Electricity, MTOE
Electricity, MTOE
2015
20 15 10 5
25 20 15 10 5
0 2010
2015
2020
2025
2030
Year Coal_ppl Oil_ppl Nuclear_ppl
0 2010
2015
2020
2025
2030
Year NaturalGas_ppl Hydro_ppl Renew_ppl
Coal_ppl Oil_ppl Nuclear_ppl
Fig. 3. Power generation mix for the Base case
NaturalGas_ppl Hydro_ppl Renew_ppl
Fig. 5. Power generation mix for the ENV1 case
― 300 ―
35
Coal import, MTOE
30
4. CONCLUSION Base No_nuclear
25
ENV1
20 15 10 5 0 2010
2015
2020
2025
2030
Year Fig. 6. Coal import for electricity generation Fig. 7 shows the CO2 emissions and Fig. 8 shows the SO2 emissions for 3 scenarios. In Base case, CO2 emission increases rapidly in the whole time range 2010-2030. CO2 emission in 2030 is 431MTon compared with 109 MTon in 2010. Although SO2 emission is not limited, the trend of SO2 emission is the same as trend of CO2 emission. 550
CO2, MTon
450
Base No_nuclear ENV1
350 250 150 50 2010
2015
2020
2025
2030 Year
Fig. 7. Trend of CO2 emission 2400
SOx, kTon
REFERENCES
Base No_nuclear ENV1
2100 1800 1500 1200 900 600 300 2010
2015
2020
2025
2030 Year
Fig. 8. Trend of SO2 emission
The paper presents MESSAGE model, a linear programming model supported by IAEA. The model is used to analyze energy development strategy considering CO2 limitation. The results are summarized as follows: - After 2020, Vietnam will exploit energy resources at maximum level. But due to shortage of energy, Vietnam should import coal, oil, electricity to meet energy demand. Without nuclear power developing, Vietnam has to import a big amount of coal for electricity generating in 2025-2030. In No_nuclear Case, coal import is 2.49 MTOE in 2025 and 29.52 MTOE in 2030. It means Vietnam has many difficulties in ensuring energy security. Nuclear power plant will be good answer for this problem; As for CO2, despite Vietnam is not required to take on any obligation on greenhouse gas reduction in the Kyoto Protocol, Vietnam should pay great attention to decreasing CO2 emission. With ENV1 case (5% CO2 reduction referred to base case in the period 2025-2030), apart of coal-fired power plant will be replaced by nuclear power plant. The installed capacity of nuclear power plant increases rapidly with 6000MW in 2025 and 13000MW in 2030. Vietnam lacks of finance and human resource to build such big capacity of nuclear power plant. One of the best solution for this problem may be Clean Development Mechanism (CDM). CDM can not only assist Vietnam to achieve sustainable development, but also assist developed countries to achieve their obligation of emission reduction promised in the Kyoto Protocol, and at the same time, provide opportunities for those who invest and convey their technology for Vietnam. The implication of CDM on energy development of Vietnam will be presented in another paper.
Asian Development Bank. Energy Policy Experience of Asian Countries. Manila, Philippin, 1987. Behram N. Kursunoglu, Stephan L. Mintz, Arnold Perlmutter (Ed.). Global Warming and Energy Policy. Kluwer Academic/Plenum Publishers, 2001. Bui Huy Phung, Bui Thanh Hung, et. al. Research on building the best reasonable strategy for development of Vietnam energy system in the period 2005-2030. Final report. Institute of Energy Science, Vietnam Academy of Science and Technology, 2006. Derek W. Bunn, Erick R. Larsen (Ed.). Systems Modelling for Energy Policy. John Wiley & Sons. 1997. J. Fr. Hake (Ed.), et. al. Advances in Systems Analysis: Modelling Energy-Related Emissions on a National and Global Level. Forschungszentrum Juelich GmbH,1994.
― 301 ―
Hydrometeorological service (HMS). Vietnam National Strategy Study on Clean Development Mechanism. Hanoi April 2002. Ibrahim Kavrakoglu (Ed.). Mathematical Modelling of Energy System. Sijthoff & Noordhoff, 1981. International Atomic Energy Agency (IAEA). MESSAGE - Model for Energy Supply Strategy Alternatives and their General Environmental Impacts. Vienna, Austria, 2007. Jean-Baptiste Lesourd, Jacques Percebois, Fransois Valette. Models for Energy Policy. Routledge. London, 1996. S. Jebaraj, S. Iniyan. A review of energy models. Renewable and Sustainable Energy Reviews 2006; 10:281-311. Joel N. Swisher, Gilberto de Martino Jannuzzi, Robert Y. Redlinger. Tools and Methods for Integrated Resource Planning – Improving Energy Efficiency and Protecting the Environment. UNEP & RISO. Denmark, 1997. Marion Hersh. Mathematical Modelling for Sustainable Development. Springer. Germany, 2006. The Energy Data and Modelling Center, The Institute of Energy Economics. EDMC Handbook of Energy & Economic Statistics in Japan. Japan, 2007. Ulrich Bartsch, Benito Mueller, Asbjorn AAheim. Fossil Fuels in a Changing Climate: Impacts of the Kyoto Protocol and Developing Country Participation. Oxford University Press, 2000.
Bui Thanh Hungg received the B.E. (1995), M.E. (1997) degrees in energy engineering from Hanoi University of Technology. He is a lecturer at Department of Thermal Energy System, Institute of Heat Engineering and Refrigeration, Hanoi University of Technology. His current interests include energy system analysis and modelling, energy conservation and efficiency, thermal power plant. Hoang Ba Chuu received B.E (1971) degree in energy engineering from VUT – Brno (Czech Republic), D.E (1976) degree in energy engineering from CVUT (Czech Republic). He is a Professor, Department of Thermal Energy System, Institute of Heat Engineering and Refrigeration, Hanoi University of Technology. His current interests include turbomachinery, thermal power plant, energy conservation and efficiency.
― 302 ―
Bui Huy Phungg received B.E (1965) degree in thermal energy engineering from Hanoi University of Technology (Vietnam), D.E (1971) degree in energy planning in Romania. He is a Professor, Institute of Energy Science, Vietnam Academy of Science and Technology. His current interests include integrated resource planning, energy policy, clean development mechanism.
RESIDUAL TREND AND HALF-LIFE TIME OF DDT IN SURFACE SOILS FROM BACNINH, VIETNAM Vu Duc Thao 1* , Vu Duc Toan 2 1 2
Hanoi University of Technology, 1 Dai Co Viet Street, Hanoi, Vietnam Hanoi Water Resources University, 175 Tay Son Street, Hanoi, Vietnam
*Corresponding to: V.D. Thao
Abstract
Dichlorodiphenyltrichloroethane (p,p’-DDT) and its metabolites (p,p’-DDE, p,p’-DDD) were analyzed in the surface soils of Bacninh, Viet Nam. Forty representative soil samples were collected from Bacninh town and three surrounding districts. The sampling locations were chosen at random in February 2006, with an attempt to get them evenly distributed over Bacninh province. The levels of the DDT and its metabolites in the surface soils of Bacninh were investigated by means of gas chromatography coupled with mass spectrometry. In agricultural areas, ΣDDT concentrations ranged from
