Which One Does Better Predict the Heating Value of Biomass?—Dry Based or As-Received Based Proximate Analysis Results?

2019 ◽  
Vol 141 (11) ◽  
Author(s):  
A. Ozyuguran ◽  
H. Haykiri-Acma ◽  
S. Yaman
Keyword(s):  
Least Squares Method ◽  
Calorific Value ◽  
Absolute Error ◽  
Proximate Analysis ◽  
Prediction Performance ◽  
Bias Error ◽  
Waste Biomass ◽  
Heating Value ◽  
Value Prediction ◽  
Predicted Values

Thirty-nine different species of waste biomass materials that include woody or herbaceous resources as well as nut shells and juice pulps were used to develop empirical equations to predict the calorific value based on the proximate analysis results. Ten different linear/nonlinear equations that contain proximate analysis ingredients including or excluding the moisture content were tested by means of least-squares method to predict the HHV (higher heating value). Prediction performance of each equation was evaluated considering the experimental and the predicted values of HHV and the criteria of MAE (mean absolute error), AAE (average absolute error), and ABE (average bias error). It was concluded that the presence of moisture as a parameter improves the prediction performance of these equations. Also, the samples were classified into two subsets according to their fixed carbon (FC)/ash values and then the correlations were repeated for each subset. Both the full set of samples and the subsets showed a similar trend that the presence of moisture in equations enhances the prediction performance. Also, the FC content may be disregarded from the equation of the calorific value prediction when the FC/ash ratio is lower than a given value.

Evaluasi Prediksi Higher Heating Value (HHV) Biomassa Berdasarkan Analisis Proksimat

2020 ◽  
Vol 4 (1) ◽  
pp. 1-7
Author(s):  
Made Dirgantara ◽  
Karelius Karelius ◽  
Marselin Devi Ariyanti, Sry Ayu K. Tamba
Keyword(s):  
Renewable Energy ◽  
Natural Gas ◽  
Key Words ◽  
Critical Analysis ◽  
Fossil Fuels ◽  
Calorific Value ◽  
Proximate Analysis ◽  
Heating Value ◽  
Bomb Calorimeter ◽  
Hhv Prediction

Abstrak – Biomassa merupakan salah satu energi terbarukan yang sangat mudah ditemui, ramah lingkungan dan cukup ekonomis. Keberadaan biomassa dapat dimaanfaatkan sebagai pengganti bahan bakar fosil, baik itu minyak bumi, gas alam maupun batu bara. Analisi diperlukan sebagai dasar biomassa sebagai energi seperti proksimat dan kalor. Analisis terpenting untuk menilai biomassa sebagai bahan bakar adalah nilai kalori atau higher heating value (HHV). HHV secara eksperimen diukur menggunakan bomb calorimeter, namun pengukuran ini kurang efektif, karena memerlukan waktu serta biaya yang tinggi. Penelitian mengenai prediksi HHV berdasarkan analisis proksimat telah dilakukan sehingga dapat mempermudah dan menghemat biaya yang diperlukan peneliti. Dalam makalah ini dibahas evaluasi persamaan untuk memprediksi HHV berdasarkan analisis proksimat pada biomassa berdasarkan data dari penelitian sebelumnya. Prediksi nilai HHV menggunakan lima persamaan yang dievaluasi dengan 25 data proksimat biomassa dari penelitian sebelumnya, kemudian dibandingkan berdasarkan nilai error untuk mendapatkan prediksi terbaik. Hasil analisis menunjukan, persamaan A terbaik di 7 biomassa, B di 6 biomassa, C di 6 biomassa, D di 5 biomassa dan E di 1 biomassa.Kata kunci: bahan bakar, biomassa, higher heating value, nilai error, proksimat  Abstract – Biomass is a renewable energy that is very easy to find, environmentally friendly, and quite economical. The existence of biomass can be used as a substitute for fossil fuels, both oil, natural gas, and coal. Analyzes are needed as a basis for biomass as energy such as proximate and heat. The most critical analysis to assess biomass as fuel is the calorific value or higher heating value (HHV). HHV is experimentally measured using a bomb calorimeter, but this measurement is less effective because it requires time and high costs. Research on the prediction of HHV based on proximate analysis has been carried out so that it can simplify and save costs needed by researchers. In this paper, the evaluation of equations is discussed to predict HHV based on proximate analysis on biomass-based on data from previous studies. HHV prediction values using five equations were evaluated with 25 proximate biomass data from previous studies, then compared based on error value to get the best predictions. The analysis shows that Equation A predicts best in 7 biomass, B in 6 biomass, C in 6 biomass, D in 5 biomass, and E in 1 biomass. Key words: fuel, biomass, higher heating value, error value, proximate 

scholarly journals Experimental and Theoretical Fuel Property Comparison of Four Different Waste Biomass with A Commercial Counterpart

2021 ◽  
Author(s):  
Mustafa Kaan Baltacıoğlu ◽  
Mustafa Tunahan Başar ◽  
Hüseyin Turan Arat ◽  
Yasin Erdoğan
Keyword(s):  
Calorific Value ◽  
Orange Peel ◽  
Volatile Matter ◽  
Waste Biomass ◽  
Heating Value ◽  
Moisture Contents ◽  
Accredited Laboratory ◽  
Pomegranate Seed ◽  
Pomegranate Seeds ◽  
Pellet Form

Abstract This study focuses on determining the fuel properties of apple pulp, pomegranate seeds, pomegranate peel and orange peel wastes and converting them into pellet fuel. Within the scope of the study, the organic wastes were dried, ruined into small pieces and then pressed to take the pellet form. Moisture content, ash content, volatile matter determination, fixed carbon content, total sulfur content, hydrogen content, lower heating value and higher heating value were analyzed as solid fuel characterization process. Experiments were carried out in an internationally accredited laboratory in accordance with ASTM and TS EN ISO/IEC 17025 Standards. Considering the results, it was determined that the pellet obtained from fully dry state pomegranate seed had a calorific value of 4244 kcal/kg, whereas the commercial pellet was 4759 kcal/kg under the same conditions. On the other hand, the moisture contents of the commercial pellet and pomegranate seed sample were 5.42% and 1.83%, respectively. The drying process was one of the costliest stages of pellet production. The low moisture contents can reduce the production cost and shorten the time.

The Prediction Model and Application for Net Calorific Value of Biomass Power Plant Fuel

2013 ◽  
Vol 781-784 ◽  
pp. 2420-2424
Author(s):  
Hong Liang Zhang ◽  
Dian Zhen Fu ◽  
Pan Zhang ◽  
Wei Li
Keyword(s):  
Linear Regression ◽  
Regression Model ◽  
Multiple Linear Regression Model ◽  
Calorific Value ◽  
Woody Biomass ◽  
Proximate Analysis ◽  
Analysis Method ◽  
Value Prediction ◽  
Independent Variables ◽  
Biomass Power Plant

A quantitative multivariate linear regression equation is established with the net calorific value of woody biomass fuel as the dependent variable and proximate analysis indexes as the independent variables. The prediction effect of the regression model is evaluated by the error analysis method. Results show that within the variable application ranges, the prediction error of the multiple linear regression model developed is small, and it could provide basis and reference for the calorific value prediction of woody biomass.

scholarly journals PROXIMATE ANALYSIS AND CALORIFIC VALUE OF PELLETS IN BIOSOLID COMBINED WITH WOOD WASTE BIOMASS

2018 ◽  
Vol 19 (3) ◽  
pp. 185-190
Author(s):  
I Nyoman Sukarta ◽  
I Dewa Sastrawidana ◽  
Ni Putu Ayuni ◽  
Sudiana I
Keyword(s):  
Calorific Value ◽  
Proximate Analysis ◽  
Wood Waste ◽  
Waste Biomass

scholarly journals Properties of briquettes and pellets of pine needles from Hattiban Community Forest, Kathmandu, Nepal

2018 ◽  
Vol 6 ◽  
pp. 1-8
Author(s):  
Anu Radha Baral ◽  
Krishna Raj Shrestha
Keyword(s):  
High Pressure ◽  
Thermal Efficiency ◽  
Research Work ◽  
Calorific Value ◽  
Proximate Analysis ◽  
Pine Needles ◽  
Average Weight ◽  
Community Forest ◽  
Heating Value ◽  
Combustion Properties

Biomass is the most utilized primary energy source in context of Nepal. Briquetting of pine needles can be an option for natural resource management. This research work was carried out to quantify the amount of pine needles during the fall season and to study the combustion properties, performance and emission of the briquette produced. The study was carried out in Hattiban Community Forest of Kathmandu district. In order to quantify the pine needle, simple random sampling was used. The average weight of needles in field was observed to be 751g m-2. Altogether, four types of briquettes and two types of pellets were produced using different binders and various briquetting technologies. Proximate analysis was carried out following the Japanese Industrial Standards (JIS 8812) and the calorific value test was done using Toshniwal Digital Bomb Calorimeter. The result from the proximate analysis showed higher (32.93%) amount of ash content of beehive briquette. Calorific value test of the fuel showed that high pressure pellets had the higher heating value (5555.1 kcal kg-1) and beehive had the lower heating value (3801.4076 kcal kg-1). The water boiling test reveals that thermal efficiency of the stove was highest (39.1%) when operated with high pressure pellet and low (24.76%) for charcoal pellets. Except high pressure pellets, other briquettes and pellets exceeded the safe limit of carbon monoxide and particulate matter emission given by National Indoor Air Quality Standard. Fuel characteristics like high thermal efficiency, high calorific value and proximate value obtained from present analysis shows pine needles can be used as appropriate and sustainable source of energy.

Lower Heating Value Estimation of Coal Gangue through Proximate Analysis Data Based on GB/T 212-2008

2013 ◽  
Vol 726-731 ◽  
pp. 2699-2703
Author(s):  
Xiu Teng Wang ◽  
Bin Lu ◽  
Ling Xu ◽  
Chen Yi Li ◽  
Ling Lin ◽  
...  
Keyword(s):  
Thermal Power ◽  
Calorific Value ◽  
Analysis Data ◽  
Proximate Analysis ◽  
Coal Gangue ◽  
Important Indicator ◽  
Heating Value ◽  
Lower Heating Value ◽  
Value Estimation ◽  
Lower Heating

The calorific value of coal gangue is an important indicator to assess its quality for comprehensive utilizations. Although the heating values can be measured experimentally with a Bomb calorimeter, an easier and faster approach within an acceptable tolerance is in great demand. Herein, we use an alternative approach to estimate the heating value based on proximate analysis data, which are measured under the instruction of GB/T 212-2008. The lower heating values of coal gangue samples we collected range from 2307 to 8309 kJ/kg, which are key information for the use of coal gangue in principle. We conclude that the sample with calorific value of 8309 kJ/kg can be used as formal fossil fuel; another sample of 5799 kJ/kg can be used for thermal power generation, while the other four are not worth for fuel.

scholarly journals LOW HEATING VALUE PREDICTION FROM PROXIMATE ANALYSIS FOR SEWAGE SLUDGE SAMPLES

2018 ◽  
Author(s):  
Agnes Serbanescu ◽  
◽  
Mona Barbu ◽  
Ileana Nicolescu ◽  
Georgeta Madalina Arama
Keyword(s):  
Sewage Sludge ◽  
Proximate Analysis ◽  
Heating Value ◽  
Value Prediction

scholarly journals Effect of heating temperature on quality of bio-briquette empty fruit bunch fiber

2020 ◽  
Vol 9 (3) ◽  
pp. 192
Author(s):  
Nofriady Handra ◽  
Anwar Kasim ◽  
Gunawarman Gunawarman ◽  
Santosa Santosa
Keyword(s):  
Heating Temperature ◽  
Calorific Value ◽  
Mold Temperature ◽  
Waste Biomass ◽  
Renewable Energy Resources ◽  
Heating Value ◽  
Empty Fruit Bunches ◽  
A Value ◽  
Average Loss

<p><span>Empty Fruit Bunches (EFB) are one of the palm oil industry wastes, which are quite plentiful and currently unused optimally. Biomass is one of the renewable energy resources which has important roles in the world. The bio-briquettes are manufactured through densification of waste biomass by implementing certain processes. This research aimed to obtain variations in the mold temperature at 150 ºC, 200 ºC, and 250 ºC to the calorific value and toughness of the briquette material. The toughness was tested using ASTM D 440-86 R02 standard. Arduino program was used for setting the heating resistance time of the mold, which was 20 minutes and the thermal controller was used to adjust the temperature variation. The average mold pressure was 58 Psi. The highest heating value was obtained at a mold temperature of 250 ºC with a value of 5256 cal/g, and the lowest was resulted at a temperature of 150 ºC (4117 cal/g). Meanwhile, the briquette toughness test at 200 ºC mold temperature indicated good data results in which the average loss of fiber particles was only 4.17 %, this was because the adhesion between particles by lignin and cellulose in the fiber functions optimally at this temperature so that the resistance of briquettes went through minor damage.</span></p>

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