GCV Computation for biomass

GCV Computation for biomass Arshi Mehta, Amit Seth, Ashok Kumar, B Ram Suresh 4, Amit Yadav 5, Abhishek Mahor 6 Department of Power plant& Energy Efficiency, Development Environergy Services Limited (Energy auditor BEE) Abstract the primary concern is to compute the co-relation between ultimate analysis of biomass and its GCV. Many formulas are there but they all show varying results. The entire methodology was to derive the empirical formula that best co-relates the percentage of elements present in the fuel and its GCV. This will increase the accuracy in the practical applications to the biomass power plants. In this particular, the chemical analysis is done& GCV is recorded at the plant. Trial for more than 00 hours was conducted to reconcile the GCV values by direct & indirect efficiencies. With the help of the Regression & Simulation process the empirical factors have been back derived Keywords GCV (Gross Calorific Value), Ultimate analysis, boiler efficiency, efficiency losses, reconciliation, ash, loss of ignition I. INTRODUCTION In this paper, the associates have tried to derive the empirical formula for the GCV of the biomass (Mustard Crop Residue [MCR]). In the past one decade, the price of biomass has risen by almost 0 folds. During the earlier era of biomass-power plants, the Dulong formula was used to derive the GCV& other technical data. Dulong was the formula that had been derived for the most established fuel (Coal). It is only in the recent years that the margin in revenue of the industry is diminishing due to soaring biomass prices. This has been initiated to factor in the same for the higher level of accuracy. Researchers have tried to establish a correlation between GCV & boiler efficiency so as to minimize error. Same has been computed using regression model. The error in the final simulation reconciles with the standard deviation in the practical study carried out at field. Bomb calorimete r GCV value as per Dulong formula GCV value as per previous GCV as per present Deviation in GCV value II. METHODOLOGY Prepared sample by quarter cone method GCV evaluation through bomb calorimeter Observe the value of GCV Use ultiimate analysis values in Dulong formula Calcualtion from a previous Use ultiimate analysis values in derrived formula Deviation among all GCV values Establish new formula for GCV Fig. Methodology developed During the study, the sampling of the fuel was done as per IS46 standards. s were tested for the ultimate analysis. GCV of the same was calculated by combusting the sample in the bomb-calorimeter. The same has been tabulated below: TABLE I GCV FROM BOMB CALORIMETER bomb calorimeter in,460,987,967 This difference in GCV is due to variation in the moisture present in the fuel. Also, the presence of the external inert in the form of sand degrades the value. Various samples in different time horizons were tested for the GCV. This also affects the efficiency of the boiler since it is the function of the fuel fired on as received basis that includes the inert (sand) & moisture in the fuel fired. GCV of the same was calculated by the Dulong formula and has been tabulated below []: ISSN: -58 http://www.ijettjournal.org Page 65

TABLEII GCV FROM DULONG FORMULA samples Dulong formula in Difference in GCV w.r.t. bomb calorimeter Deviation in Efficiency -,460 0.0 0.0 -,86.. -,595 9.4 0. *Note GCV on dry basis is,955 Difference could be observed for the same, which varies within the range of 0.0 to. This impacts the boiler efficiency (Direct method) which comes out in the range of to 0. GCV of the same is calculated as per previous paper []: GCV = 5.*C - 9*C - 674*H + 8.6*C*H + N +08 Where C is the Carbon in fuel H is the Hydrogen in fuel N is the Nitrogen in fuel TABLE III GCV FROM PREVIOUS RESEARCH - - - Previous in Difference in GCV w.r.t. bomb calorimeter Deviatio n in Efficienc y,89.5. 4,56 6.8 6.,954 0. 0. Difference has been observed for the same & the variation lies in the range of 0. to.5. This results in impacting the boiler efficiency (Direct method) in the range of 0. to.. The difference in GCV of different fuels is primarily due to different structural linkages of various atoms and percentage of various compounds present (Majorly-Cellulose, Hemi-Cellulose, Lignin) in each type of fuel. Fig. Cellulose, Hemicelluloses and Lignin present in biomass TABLE IV COMPOSITION OF DIFFERENT BIOMASSES [] Type of biomass Cellulose Hemi cellulose Lignin Hardwoods 40-55 4-40 8-5 Softwoods 45-50 5-5 5-5 Wheat 0 50 5 Straw Corn cobs 45 5 5 Grasses 5-40 5-50 0-0 Switch grass 45.4 The ultimate and proximate analysis of MCR is nearly similar to that of wheat straw. Exact composition of the mustard in terms of Lignin, Cellulose & Hemi-cellulose is not available, therefore it has been considered same as that of wheat straw. Thus, most established fuel wheat straw which is almost same in the ultimate analysis ISSN: -58 http://www.ijettjournal.org Page 66

has been used for computation. The comparison is shown in the table below. TABLE V PROPERTIES OF MUSTARD CROP RESIDUE AND WHEAT STRAW Constituent s in fuels Ultimate and proximate analysis of MCR Ultimate and proximate analysis of Wheat straw [4] Carbon 45. 45.5 Hydrogen 4.89 5.0 Oxygen.96 4.0 Nitrogen 0.7.80 Sulphur 0.8 0.8 Calorific value 987 406 Therefore, the percent composition of Cellulose, Hemi-cellulose and Lignin in MCR is expected to be approximately equal to that of wheat straw. Thus, the percentage composition of wheat straw is used to calculate the tentative GCV of MCR as shown in the table below. TABLE VI GCV OF MCR AS PER CHEMICAL STRUCTURE [6] Chemical compoun d in MCR GCV Weightage of compound Cellulose,8 0 Hemicellu loses,8 50 Lignin 5,97 5 Weighte d GCV 954 The value of the GCV in table VI reconciles with the practically tested GCV of the MCR without moisture & sand (surface), thus emphasizing on the same composition of the fuel as per table VII. This shows greater level of correlation between both biomasses. (Heat liberated in combustion of biomass as per availability of cellulose, hemicelluloses and lignin [5]) The team carried out modeling of fuel using the fundamentals in the PROSIM software for chemical engineering. The GCV computed by the software is reconciled with the estimated GCV in the formula using the complex correlation. Model of the same in the software is shown in the figure below: Fig. 4Model for the simulation (basic model) Results from various iterations in PRO-SIMPLUS are tabulated below: TABLE VIIGCV MODELING IN PROSIMPLUS Method GCV Dulong Modified,94 Solid or Liquid Waste,84 Vandracek,955 Dulong,64 All type of fuel 4,050 Liquid Coal 4,8 Boie,996 The simulated model for the system is shown in the figure below: Now the chemical structure of coal is given below in the figure [5]: Fig. Structure of 4 types of coal Chemical structure of coal is given in the above figure. The amount of heat liberated by combustion of coal will be equal to GCV calculated using Dulong formula which was derived specifically for coal only. Fig. 5 GCV simulation for the GCV for the fuel The team of ers practically carried out trials for calculating boiler efficiency using the MCR fuel. ISSN: -58 http://www.ijettjournal.org Page 67

The team had recorded, running parameters of the power plant to establish the co-relation of the GCV and its impact on the boiler efficiency. All relevant parameters were recorded from DCS (digital center) of the power plant. Known mass of fuel was used for trial and the same was entirely combusted in the boiler. Rigorous sampling methodology was adopted by the team at the field to obtain the required data for analysis. GCV samples for the fuel were collected from the belt weigher on an hourly basis and were recorded. To compute the indirect efficiency of combustor (boiler), measurements for the flue gas and ash were taken at intervals of 5 minutes to average out the deviations in the long duration of the trial for higher accuracy. Deviation in GCV is correlated with deviation in efficiency (direct and indirect method) that is given below: TABLE VIIDIFFERENCE BETWEEN DIRECT AND INDIRECT EFFICIENCY Direct efficien cy Indirect Efficienc y Differenc e in efficiency S-D valu e 65.4 68.8.4.7 68. 7.5 4.. 68.7 7.8 5..5 S.D. = Standard Deviation Minimum value of standard deviation is.7. Average is about. This is on account of the sampling error that had led to variation in the fuel parameters that vary continuously with time. The team had minimized this difference across several trails by rigorous sampling methodology adopted for the entire process. Factors used in empirical formula are given below in the table: TABLE VIIIFACTORS FOR EMPIRICAL EQUATION Power of factor C S H-O C*(H-O) C*S S*(H- O) 0 0 0 0 0 0 0 85 5.5 9 - - -5 0.0 5-0 -0.9745 0 0 0 0 0 0 0.00 0 4 0-0 - -0.00004-0.00 0 5 0 0 0 0 0.007 0 6 0 0 0.97e-07-0.0004 Using these factors, empirical formula comes out to be as follows: GCV = 85*C + 0.0(C ) + 5.5*S + 5*(S ) - 0*(S 4 ) +9*(H-O) 0*(H-O) *(H-O) 4 0 C*(H-O)-0.975*(C*(H-O)) +4e-5*(C*(H-O)) 4 + e-7*(c*(h-o)) 6 *(C*S) + 0.00*(C*S) 0.00*(C*S) 4 + 0.068*(C*S) 5 4e-4*(C*S) 6 5*(S*(H-0)) GCV obtained from the above empirical formula and deviation w.r.t. GCV from bomb calorimeter is shown in the table below: TABLE IXVARIATION IN GCV FROM EMPIRICAL FORMULA W.R.T. GCV FROM BOMB CALORIMETER bomb calorimeter in empirical formula Deviat ion in,460,89..05,987,905.4.05,967,95 0.05 GCV of the same was iterated with the addition of new relations b/w CH, CO, CHO, HS. Regression was carried out to derive the relation for the coefficients; higher degree of the empirical polynomial equation was carried out to establish the same. Research team was able to correlate the factors for fine tuning the error of. This factor almost equals the standard deviation during the trials. However, the impact of the same can be nullified by modification in the air to fuel data same had been tested and is under review & process optimization by the team. III. CONCLUSION This complicated empirical formula, tested on the mustard crop residue, was derived and error has been optimized to lower levels to around. Researchers used the algorithms for the regression method to minimize the error as low as possible. Same was also tested by the team with the practice fuel & steam scenario for over 00 hours to validate the same. This can be used for computation of the GCV more accurately. Also, the ultimate analysis of the fuel is used for calculation of the theoretical air which has impact on the efficiency too. Same is under review by the team to further curtail the error to a lower value. Research team is working on the algorithm to compute the proximate analysis of the fuel back from the GCV and relation in the proximate analysis of biomass & ultimate analysis of the biomass. Similar cases for the coal had been established. Thus, evaluation of these will help in defining the efficiency of power plants more ISSN: -58 http://www.ijettjournal.org Page 68

accurately and minimizing the losses. Once the accurate parameters are recorded, the further scope of saving can be figured out. This formula can be tested and the same can be integrated in the system DCS & excel models of the power plants using the Mustard fuel to compute the more accurate results. IV. REFERNCES [] http://nptel.ac.in/courses/04058/mme_pdf/lecture.pdf [] Giuseppe Toscano, Ester Foppa Pedretti.,Calorific Value determination of solid biomass, J. of Ag. Eng. - Riv. di Ing. Agr. (009),, -6 [] P. Bajpai, Pretreatment of Lignocelluloses Biomass for biofuel production, Springer Briefs in Green Chemistry for Sustainability, DOI 0..007/978-98-0-0687-6-, 06 [4] Vijay Krishna Moka, Estimation of Calorific value of biomass from its elementary components by regression analysis, department of mechanical engineering, NIT Rourkela, 0-0 [5] Richard C. Neavel, Coal Structure and Coal Scoence: Overview and recommendation Exxon and engineering Co. P.O. Box 455, Brayton, Texas, 7750 [6] http://bisyplan.bioenarea.eu/html-files-en/04-0.html [7] http://www.chem.tamu.edu/class/fyp/keeney/ch5.pdf [8] http://pslc.ws/fire/cellulos/combans.htm [9] http://chem.libretexts.org/core/physical_and_theoretical_c hemistry/chemical_bonding/general_principles_of_chemi cal_bonding/bond_energies [0] http://www.ausetute.com.au/heatform.html [] https://socratic.org/questions/upon-formation-of-5-0g-ofc0-from-carbon-and-oxygen-4-kj-of-heat-are-releas ISSN: -58 http://www.ijettjournal.org Page 69