Jatropha curcas oil is one of the most promising renewable energy sources for rural areas due to its ease of production, which can be used as an alternative to diesel and fuel oil. The development of sustainable energy has been the issue of the discussion about biofuel production given the considerable consumption amount of fossil fuel during the transformation process. And any production process that consumes a lot of energy records a significant destruction of useful energy, which leads to thermodynamic inefficiencies of the process. Besides, the focus on environmental safety is gradually shifting towards energy efficiency in industrial processing. Exergetic analysis is an effective tool for measuring the performance of a production process since exergy is a quantity that measures energy quality. This study assesses the scale of resource degradation in Jatropha oil mechanical extraction processes and finds improving possible pretreatments options for more efficient production. Data from experiments combined with existing databases have permitted to establish the exergy flow balance at each stage of production. The process exergetic yield varies from 29.85% to 35.41% according to the chosen pretreatment process. Mass exergy accounts for 67% of incoming flows and, for outgoing flows, more than 60% is associated with the mass exergy generated by the process waste. The uncertainties analysis on the results was used to validate model results, and to visualize the minimum values for the most unfavorable cases and the maximum values when all the parameters are at their optimum values.
Several research works on biodiesel production have recently focused on optimizing the transformation process [
Growing consumption of fossil fuel products leads to the search for alternative fuels limiting global warming and environmental pollution to meet energy demand. Biodiesel is one of the most prominent renewable fuels nowadays. Biodiesel has similar properties with diesel fuel. It can be mixed with diesel fuel or can be used directly in most diesel engines without major engine modifications. The other advantage is that biodiesel has lower sulfur content, with an upper limit of 10 mg/kg biodiesel, in accordance with European biodiesel standard (EN 14214).
Biodiesel from jatropha oil is a reliable source of energy that is efficient and conducive to sustainable economic development [
Jatropha curcas plantation can produce 2 to 5 tons of dry seed/ha/year. The yield varies according to the type of culture, by seeds or by cuttings; the climatic conditions as well as the management technologies used [
As this kind of oil is inedible, its production should not affect the food security problem [
While being converted to biodiesel, jatropha oil has a high potential of produced biofuel from vegetable oil as its properties are well improved and subsequently suitable for replacing fossil fuels [
Most people in rural areas do not have access to energy sources in developing countries. An approach to provide the required energy is to enable the generation of energy from local resources. Jatropha oil is one of the most promising renewable and independent energy sources in rural areas due to the ease of its production [
There are commonly 4 kinds of oil extraction from seeds according to the used method, namely: solvent extraction, mechanical extraction, enzymatic extraction and aqueous extraction. For rural areas, mechanical extraction with screw press or hydraulic press is considered as the best way. It is adopted because of its lower initial and operational cost as well as its ease of use by unskilled workforce. Besides, the produced oil is relatively good quality compared to that obtained from chemical extraction process. Additionally, residual cake may be used for other purposes [
Exergetic analysis goes further in the energy optimization of industrial processes than the purely thermal approach on which traditional energy analyses are based. Exergy combines the first and second law of thermodynamics to locate and quantify inefficiencies in an industrial process, taking into account not only the energy losses, but also the quality losses of this energy [
Screw presses and oil expellers have been used since the first century of our era. Previously, the Greeks developed it for pressing olives. This method is still widely used by small, medium and large scale companies for vegetable oil extraction. In most parts of the world, especially in remote areas without access to electricity, Jatropha curcas oil is generally extracted from screw presses operating on diesel engines. This is preceded by a heat treatment at about 60˚C - 70˚C and gives 47.2% oil yield [
So far, exergetic analyzes on jatropha oil extraction focused on the oil extraction steps and the improvement of the methods to be used. This is important, but not enough, because we must also integrate the effective use of natural resources.In order to use the most efficient technology for extracting oil for biodiesel production, an exergy analysis must be performed. Exergy analysis is an effective way to detect the true magnitude of thermodynamic imperfections in the performance of various unit operations within the process to be improved.
Screw presses are currently designed for a continuous extraction process [
Currently, focus on environmental safety is shifting towards energy efficiency in industrial processing [
General exergy balance involving a mass transfer linking entropy generation and exergy destruction is given by [
∑ E x i n − ∑ E x o u t = E x d e s t = T 0 S g e n = I (1)
where ∑ E x i n represents total incoming exergy, ∑ E x o u t total outgoing exergy, E x d e s t destruction of total exergy, T 0 S g e n entropy generation, and I irreversibility, respectively.
Equation (1) can be rewritten as Equation (2) involves exergy due to heat/work interactions [
∑ E x h e a t − ∑ E x w o r k + ∑ E x m a s s , i n − ∑ E x m a s s , o u t = E x d e s t = T 0 S g e n (2)
where
∑ E x w o r k = W
∑ E x h e a t = ∑ ( 1 − T 0 T ) Q (2b)
∑ E x m a s s , i n = ( ∑ i m i E x i ) i n (2c)
∑ E x m a s s , o u t = ( ∑ i m i E x i ) o u t (2d)
Equation (2a) defines exergy of the system due to work production. This can be calculated from heat capacities and standard chemical energies of flows entering or leaving the system.
Equation (2b) also defines quality of energy in the system. Q represents thermal load of the system with T0 the ambient temperature (298 K) while T denotes the system temperature (K).
Equations (2c) and (2d) define physical exergy of input and output resources, respectively.
Consideration of mass exergy is more important in this study as the scope of the study extends from the drying process to oil extraction.
For real processes, exergy at input always exceeds that at exit of a system. This imbalance is due to irreversibility, also called destruction of exergy, and is represented as a function of entropy generation. The exergy value of a steady stream of fluid entering or exiting a part of a process is the minimum amount of energy that can be obtained from flow to bring it into equilibrium with the environment [
E x p h = ( H − H 0 ) − T 0 ( S − S 0 ) (3)
With real irreversible processes, there is always increasing entropy resulting from the dissipative effects of energy within the production system. This loss of generated exergy is released into the environment or destroyed during the process [
In 1995, the International Organization for Standardization [
Schenck [
There is no perfect measure. All measures of a variable contain inaccuracies. Because it is important to understand these inaccuracies if we have to perform experiments or if we simply have to use values that have been determined experimentally, we need to carefully define the concepts involved.
Our approach is an appropriate scientific tool to evaluate the thermodynamic durability of a production process. This study assesses resource degradation extent in jatropha oil extraction processes and identifies possible improvement options for efficient production. A comparison of degree of resources degradation and yields at each level of the process will be analyzed.
Pretreatment and oil extraction with screw press are used as case studies. Exergy destruction and efficiency at each transformation stage are compared.
Exergetic analysis is also a thermodynamic sustainability tool that is used here to quantify the emission and waste streams of the studied process [
Uncertainty analyses will be conducted on results to better understand the distribution of probability densities of the process yields.
Jatropha curcas seeds used in the experimentation were collected from Mahabo, Menabe region, Madagascar. The ripe fruits were harvested and dehulled manually in February 2018. They were locally dried in sun, stored in woven polypropylene bags ventilated at temperature between 28˚C and 35˚C with a relative humidity ranging from 65% to 75% for three months. After being transported to Antananarivo, the seeds were stored at ambient temperature between 15˚C and 25˚C and a relative humidity between 70% and 80%. The seeds were shelled and analyzed for weight fraction, initial moisture, and total oil content (see
For each batch, seeds undergo different pretreatment levels in order to evaluate each step of the process (
Moisture content is a determining factor in Jatropha curcas seeds storage and pretreatment. Seeds are well dried before being bagged so that it does not degrade during storage period.
Before performing the experiment, an initial moisture content calculation of seeds is done. For that purpose, 100 g of seeds are placed in an oven at a temperature of 150˚C. They are weighed every 30 minutes until constant weight is obtained. The moisture content is calculated using the following formula:
Stream name | Unit | Quantity | Standard chemical exergy (MJ/kg) | Chemical exergy (MJ) | Combustion exergy efficiency (MJ) |
---|---|---|---|---|---|
Jatropha seeds before treatment | kg | 5.00 | 17.73 | 89 | |
Dried Jatropha seeds | kg | 4.42 | 20.30* | 90 | 31.17% |
Jatropha kernel | kg | 1.56 | 12.60* | 20 | 70.30% |
Jatropha Shell | kg | 2.86 | 16.93* | 48 | 3.40% |
Jatropha cake | kg | 0.75 | 20.25* | 15 | 66.70% |
Jatropha oil | kg | 0.97 | 37.00 | 36 |
*Obtained from [
M = m k i − m k f m k i × 100 (4)
where M is the moisture content (%), m mass in (g), and subscripts k, i, f are for kernel, initial and final, respectively.
Oil recovery increases from a low moisture content of 1% (wb) to a maximum value at moisture contents between 4% and 5% (wb) for all applied pressures [
In experiments to study the effect of shell removal, the mean weight of samples (shells and kernels) was approximately 7 g for each seeds. The indicated percentage of shell removal is the shell removed percentage from the original sample. 0% elimination means that experiment uses 100% seed which is corresponding to 35.5% (weight basis) of shell content; while 100% removal means that experiment uses 100% kernels which corresponds to 0% of shell content. Oil recovery was calculated on oil content and undehulled sample weight basis. Jatropha shell, not containing oil, was removed and evaluated in mass rejected with the cake. Experiments were performed with 0%, 20%, 40%, 60%, 80% and 100% of shell removal. Unless otherwise indicated, the process consists of complete separation of kernel and shell. Seeds cracking is carried out using mechanical cracking rollers manufactured for this purpose. The shell-kernel sorting for removing all the shells is done manually.
Heat treatment on Jatropha curcas seeds is necessary in order to deform their cell structures to agglomerate or flocculate oil droplets into the kernels. This process helps improve cells permeability in seeds by reducing seeds oil viscosity for more efficient extraction. Reducing seed size increases oil yield efficiency besides.
The various effects of heat treatment on the process are observed with different heating temperature levels.
Given the oil quality degradation, with heat treatments of the order of 80˚C (increase of acidity, main cause of metallic elements abrasion), temperature stage 0˚C, 40˚C, 60˚C, 80˚C were selected.
Experiment is carried out with a Cotter rotary screw press with a production capacity of 15 kg/h. It is powered by 2.2 kW electric motor. Shelled and heat treated Jatropha curcas seeds are introduced into the screw press, which consists of helical thread rotating in a fixed perforated cylinder called a cage or barrel [
The methods used for mechanical Jatropha curcas oil extraction in this study are those commonly used, as reported in the literature [
The expelled oil may contain residue that can be removed using a decanter and a filter. Then oil is pumped into filter to remove remaining solids and fines to produce clear oil prior storage. Cake is valued with the shell because they can be used for other uses.
In a biomass such as Jatropha curcas seeds, exergy is mainly stored in chemical exergy form [
ε f u e l 0 = β ∗ L H V (5)
where ε f u e l 0 represents standard chemical exergy of biomass, LHV the lower heating value of fuel, and β the weighting factor which takes into account information conveyed by biomass or fuel; their values are indicated in the literature [
The chemical exergy for each pure substance, organic and utilities was computed using their standard chemical energies E x c h , i taken [
E x c h , i = Δ G f o + ∑ i v i E x c h , i 0 (6)
where E x c h , i , E x c h , i 0 , Δ G f o and v i are the chemical exergy of specie i, standard chemical exergy of species i, Gibb’s free energy of formation of species i and the molar ratio of species i, respectively.
The Chemical exergy of organic substances not listed by Ayres [
The physical exergy of each stream is thus calculated using Equation (7) [
E x m a s s , i = E x c h , i + E x p h , i (7)
As indicated above, each term is determined separately and systematically for each stage of the oil production. The overall efficiency of the exergy process is defined by [
η t o t a l = ∑ E x O u t ∑ E x i n (8)
where ∑ E x O u t is the total exergy of output resources or products and ∑ E x i n is the total exergy of input resources.
The uncertainty analysis is conducted with the @RISK software which enriches Microsoft Excel with an expert modeling and uncertainty analysis capability. The modeling represents the actual situation for its analysis. Entries values result from variable experiments; hence, the importance of uncertainty calculations on our research results.
Probability distributions provide a quantified uncertainty presentation method of a variable, @RISK uses it to describe the uncertain values of Excel spreadsheets and to present the results. There are several forms and types of distributions, each describing a range of possible values and probability. All distribution types use a set of arguments to specify a range of real values and probability distributions. The normal distribution, used in the present case, is defined by an average and a standard deviation resulting from the experimental data.
The model is calculated on an Excel spreadsheet based on experimental averages. The variable nature of the input data prompts us to perform a simulation to determine the range and probabilities of all possible result outcomes.
Measurements of variables are influenced by a number of elementary error sources such as calibration errors, errors caused by changes in ambient temperature, humidity, pressure, vibration, instability in the phenomenon of “balance” to measure. With each experimental measurement, we could draw a histogram, which shows the fraction of N total measurements which is shown in
When identifying uncertain values in Excel spreadsheet, we must determine whether the variables are correlated or not. Those considered here are indeed “correlated”. In @RISK, the Corrmat function is used to identify correlated variables. It is extremely important to correctly identify correlations between them.
Once uncertain values in spreadsheet cells entered and the outputs of the analysis identified, we have an Excel spreadsheet that can be processed with @RISK. It uses Monte Carlo simulation to execute the uncertainty analysis. In this sense, simulation refers to the method by which possible outcomes distribution results from the computer executing repeated calculations of the spreadsheet, based on a set of different values each time, randomly selected from the probability distributions introduced in the cells values and formulas. The computer basically tries all the valid combinations of the input variables to simulate all possible outcomes, as if we were analyzing hundreds or even thousands of hypothetical scenarios at the same time.
Like all other uncertainty analysis models, input values and output results are composed of large database. The @RISK uncertainty analysis produces its results on cells defined as inputs and outputs of the Excel worksheet. These results are the probability distributions of the values that may occur. At first glance, they correspond to the ordinary Excel analysis results carried out with the averages.
The chemical energies of the main material streams in the extraction process as well as the exergy efficiency in combustions are presented in
Seeds, kernels, shell, and cake are, in their unprocessed state, used for combustion. They are evaluated in the present study by taking into account their exergy yields in heat production processes.
In order to perform uncertainty analysis on the exergetic efficiency of the process, the results are transcribed according to distribution functions.
In
The drying heat treatments were carried out at calculated times of 8 h 35 min, 5 h 26 min and 3 h 05 min for drying at 30˚C, 65˚C and 80˚C, respectively, to obtain 5% of moisture content (
Dependent variables such as input for starting materials press feed, outgoing exergies for oil, cake, shell as well as inputs in mass, labor and heat exergy are shown in
The exergy destructions related to the incoming flows are functions of unit process parameters step. To achieve dehulling levels of 100%, 80% and 40%, required exergetic resources are 0.36, 0.29 and 0.14 MJ respectively. Compared to each other, his data relate a constant according to dehulling level. Quantitatively, it is very small and even negligible compared to the mass exergy of inputs.
The exergy used by the press for the mechanical oil extraction of the oil depends on the dehulling level. A small percentage of shelled seeds implies a larger mass of inputs. Both values are inversely proportional. It must be taken into consideration also that the kernels are softer than the seeds. Which is disadvantageous compared to electrical exergy consumed for the unitary pressing process. Exponential increase of the energy demanded by the press is noted with 0.33 MJ to process 1.56 kg of kernels while 1.96 MJ for 3.85 kg of mixture of seeds and kernels shelled at 20%. This increase in consumption is largely compensated by a higher oil yield due to greater pressure in the cage of the screw press. In the transformation process, this operation is the second least consuming of exergy while it greatly influences the overall efficiency.
Unit operation: | Drying | |
---|---|---|
Masse unit | 5 kg | |
Temp (˚C) | Drying time | Exergy (MJ) |
30 | 8h35 | 42.49 |
65 | 5h26 | 58.27 |
80 | 3h05 | 40.70 |
Unit operation | Mass in press | Exergy efficiency | Exergy out | Exergy in | |||||||
---|---|---|---|---|---|---|---|---|---|---|---|
Exergy (oil) | Exergy (cake) | Exergy (shell) | Exergy (preheat) | Exergy (press) | Exergy (dehull) | Exergy (mass) | Drying (exergy) | ||||
Setup name | kg | % | MJ | MJ | MJ | MJ | MJ | MJ | MJ | MJ | MJ |
D100-Prt80 | 1.56 | 30.39% | 128.95 | 7.357 | 13.652 | 4.724 | 2.579 | 0.333 | 0.360 | 123.699 | 58.27 |
D100-Prt60 | 1.56 | 30.26% | 128.59 | 6.656 | 13.848 | 4.724 | 1.719 | 0.333 | 0.360 | 123.699 | 58.27 |
D100-Prt40 | 1.56 | 29.85% | 128.74 | 5.255 | 14.241 | 4.724 | 0.860 | 0.333 | 0.360 | 123.699 | 58.27 |
D80-Prt80 | 2.13 | 31.14% | 127.78 | 11.209 | 18.354 | 3.779 | 2.579 | 0.740 | 0.288 | 123.699 | 58.27 |
D80-Prt60 | 2.13 | 30.47% | 128.44 | 9.108 | 18.943 | 3.779 | 1.719 | 0.740 | 0.288 | 123.699 | 58.27 |
D80-Prt40 | 2.13 | 29.93% | 128.84 | 7.356 | 19.435 | 3.779 | 0.860 | 0.740 | 0.288 | 123.699 | 58.27 |
D60-Prt80 | 2.70 | 32.71% | 125.11 | 17.163 | 22.468 | 2.834 | 2.579 | 1.146 | 0.216 | 123.699 | 58.27 |
D60-Prt60 | 2.70 | 31.90% | 126.01 | 14.711 | 23.155 | 2.834 | 1.719 | 1.146 | 0.216 | 123.699 | 58.27 |
D60-Prt40 | 2.70 | 31.09% | 126.92 | 12.259 | 23.843 | 2.834 | 0.860 | 1.146 | 0.216 | 123.699 | 58.27 |
D40-Prt80 | 3.28 | 35.07% | 120.92 | 25.218 | 25.992 | 1.889 | 2.579 | 1.553 | 0.144 | 123.699 | 58.27 |
D40-Prt60 | 3.28 | 34.69% | 121.07 | 23.817 | 26.385 | 1.889 | 1.719 | 1.553 | 0.144 | 123.699 | 58.27 |
D40-Prt40 | 3.28 | 33.22% | 123.24 | 19.614 | 27.564 | 1.889 | 0.860 | 1.553 | 0.144 | 123.699 | 58.27 |
D20-Prt80 | 3.85 | 35.41% | 120.52 | 28.018 | 30.990 | 0.945 | 2.579 | 1.959 | 0.072 | 123.699 | 58.27 |
D20-Prt60 | 3.85 | 34.49% | 121.67 | 25.216 | 31.776 | 0.945 | 1.719 | 1.959 | 0.072 | 123.699 | 58.27 |
D20-Prt40 | 3.85 | 33.69% | 122.58 | 22.765 | 32.463 | 0.945 | 0.860 | 1.959 | 0.072 | 123.699 | 58.27 |
D0-Prt80 | 4.42 | 35.07% | 121.37 | 29.067 | 36.479 | - | 2.579 | 2.365 | 0.000 | 123.699 | 58.27 |
D0-Prt60 | 4.42 | 34.55% | 121.77 | 27.316 | 36.970 | - | 1.719 | 2.365 | 0.000 | 123.699 | 58.27 |
D0-Prt40 | 4.42 | 33.49% | 123.18 | 24.164 | 37.853 | - | 0.860 | 2.365 | 0.000 | 123.699 | 58.27 |
Preheating requires less time but remains one of the most penalizing factors in assessing the exergetic efficiency of the process. It was evaluated with the greatest quantity of materials, that is, 0% dehulling, to retain the most unfavorable case possible. A maximum exergy quantity of 2.58 MJ is recorded for the treatment of 4.42 kg of grain at 80˚C and 1.72 and 0.86 MJ respectively for 60˚C and 40˚C.
Inputs mass exergy is 123.70 MJ. It was evaluated from Jatropha curcas dried seeds chemical exergy product taking into account its exergy yield during its use in combustion. Despite the change in mass flow rates at the press, the exergy at the beginning of the process remains unchanged, consisting of the whole seeds of dried jatropha. The shells, not passing through the pressing circuit, are evaluated with the other outputs. Taking into account the mass makes it possible to better apprehend the flow of exergy within the process. The only drying operation is responsible for the 41% degradation of seed exergy. Drying methods permitting moisture recovery could further increase the production process efficiency. On the other hand, a high moisture content of seeds to be processed would reduce the final exergy yield more. This calls for expanding the limits of process to the sun drying before storage.
The main output of the process is the exergy of the extracted oil. It depends on the production parameters. From
Changes of various parameters enable to identify the optimal operational parameters for jatropha oil production process. The settings are: preheating of the seeds with a level of dehulling of 20% at 80˚C to obtain a maximum exergetic yield of 35.41% and 35.04% to 40% of seeds shelled at the same temperature.
However, treatments at 80˚C are not recommended for reasons of increased acidity of the oil at the outlet, it is better to choose treatments at 60˚C with 34.69% and 34.49% respectively yield at 40% and 20% of kernel.
An uncertainty analysis is performed to validate all the results.
According to
the below-average results more important for the dehulling at 20%. By decreasing the percentage of interdependent elements in the calculation, the results for unfavorable cases combination regress. That result allows guiding the choice towards a dehulling rate of 40%.
The exergetic analysis of the production process of Jatropha curcas oil was conducted by widening the process boundaries and taking into account the mass exergy of inputs and outputs throughout the present study. It can be inferred from the results that the maximum oil yield is not significant for a production process with high exergetic efficiency. The only drying operation is responsible for the destruction of 46% of incoming exergies. The choice of the processing temperature makes it possible to reduce this rate considerably. This parameter is however dependent on the equipment used. In this case study, a long drying time at low temperatures destroys less exergy than the treatment in a medium time with a medium temperature. This is due to seeds drying curve which is not linear.
The mass effect generates 67% of incoming exergy and even, for outgoing flows, more than 60% is due to the exergy generated by the waste. The uncertainties analysis allows us directing treatments choice on processes with similar yields. It also enables to glimpse the minimum values of exergy efficiency for the most unfavorable cases that may occur as well as the maximum value when all the parameters are at their optimum values. On the other hand, it is a way to validate the results according to their probability of realization. The improvement to be done would be to use the cakes and shells during the drying operation with a considerable improvement in the means of their uses to affect the overall efficiency of the process. Looking for other uses for waste treatments also would be another alternative to having a more exergy efficient process.
The authors declare no conflicts of interest regarding the publication of this paper.
Harifidy, R.N.R. and Rakotondramiarana, H.T. (2019) Exergetic Efficiencies Evaluation of Flows and Operations on the Mechanical Extraction Process of Jatropha curcas Oil. Open Journal of Energy Efficiency, 8, 1-20. https://doi.org/10.4236/ojee.2019.81001