Techno-economic analysis of a small-scale Modified Plant Oil (MPO) production plant that has an annual production capacity of 15,072,741 kg of MPO (batch process) was carried out to estimate the capital and operating costs of a plant. The analysis was done by using a computer model that was designed and simulated with an aid of SuperPro Designer (Version 4.32) software. The specified feedstock was crude Jatropha oil (JO) and the main product was MPO. The major processes involved were degumming, neutralisation and blending. Degumming involved the removal of gums or phospholipids, and two methods were used: water degumming and acid degumming, whereas blending involved mixing of degummed or purified JO with natural gas condensate (NGC) modifier to lower the viscosity of JO. From techno-economic analysis of the process, it was found that the total capital investment of a plant was about US $ 10,222,000 and the predicted unit production cost of MPO was US $ 1.315/kg at a value of US $ 1.0/kg of JO. The economic feasibility of MPO production was found to be highly influenced by the price of feedstock, which contributed about 95% of the total annual production cost. The relationship between plant throughput and unit cost of producing MPO showed that unit production cost was very sensitive to production rate at low annual throughputs. The MPO cost showed a direct linear relationship with the cost of JO, with a change of US $ 0.50/kg of MPO in MPO cost in every change of US $ 0.50/kg of JO in JO price. The process technology simulated was found to be economically viable and can be implemented in rural setting, taking into consideration Tanzania’s rural situation.
The rural community still lacks access to clean, cost effective and sustainable form of energy that is needed to power their socio-economic activities, particularly for agriculture, water supply and food processing. Bioenergy is the main form of energy to rural residents particularly wood-fuel, which is mainly used for cooking. On one hand, use of wood-fuel for energy contributes negatively to deforestation and hence loss of CO2 sink, the quality of life due to inherent indoor air pollution and overburdening women and children as a result of walking long distances to collect wood fuel [
However, POs cannot be used directly in diesel engines because of high viscosity and low volatility as well as presence of gums and free fatty acids (FFAs), which affects engine operation and durability [
Some of the techniques used in modifying POs are such as transesterification, pyrolysis, blending and micro- emulsion [
In most cases, rural economy is characterised by low per capita economy and therefore the main challenge is an appropriate process that can meet low capital investment and yet ensure financial return to the investor. Moreover, some methods and technologies used, still display low performance in reduction of viscosity and removal of gums and FFAs. So the main questions to answer are what reasonable quality of PO is needed for rural setting utilisation; what measures are required to improve oil quality for use as fuel in diesel engines commonly found in remote rural environment, by analysing on which methods exist can reduce the unwanted components in the PO to an acceptable level, both small-scale, simple, low cost and applicable for the rural setting.
Quite a number of PO research publications and reports, analyses and reviews are more concerned with the technical analysis and the economic feasibility (techno-economic analysis) of biodiesel production by using transesterification reaction method [
Although techno-economic analysis on biodiesel industry has been performed by several studies to date in determining its economic prospective and profitability, in all the studies it has been found that even though biodiesel is more renewable and cleaner than fossil diesel, it has relatively high production costs which makes it not economic viable due to its price. Another major observation is that costs of feedstock comprise a very substantial part of overall biodiesel cost (about 75% - 80% of the total operating costs) [
This highlighted the need for a flexible model to be developed, which could aid in the comparison of alternative production routes for their abilities in reducing production costs to desirable levels and making the conversion of POs into liquid biofuel which be economically viable. The developed model could assist in determining the overall economic feasibility of a proposed operation and its flexibility could guide choices regarding feedstock, plant capacity, chemical process or conversion process and design as a whole [
This paper focuses on the modification of plant oil as a way of improving the fuel properties of jatropha (Jatropha Curcas) seed oil so that it can be used as a potential ready-to-use fuel in low- and medium-speed diesel engines for rural community without modifying an engine. These engines are commonly used in rural areas for many social economic activities. Lister engines are a good example of these engines. The main objective of this study is to evaluate techno-economic viability of a non-transesterification method or process developed to modify PO into a suitable liquid biofuel for rural setting. This involves modeling a non-existing industry based on the country’s technology capacity.
A small-scale MPO production plant that has an annual production capacity of 15,072,741 kg of MPO (batch process) was designed and simulated in SuperPro Designer. MPO production involves modifying of PO to lower and/or remove the undesired materials from PO to produce PO with fuel properties that has similar specifications of diesel fuel grade 4-D (ASTM D975), for use in low- and medium speed diesel engines. The main problems to address were viscosity, FFAs and gums (Phospholipids). Thus, the major processes involved were degumming, neutralisation and blending.
Degumming materials were water and phosphoric acid. Sodium hydroxide (NaOH) was used for neutralisation of FFAs. The blending material used was Natural Gas Condensate (NGC), which is a by-product of natural gas extraction. The condensate is supplied by Tanzania Petroleum Development Corporation (TPDC) (Dar es Salaam, Tanzania) from Songosongo gas fields. The composition of the Songosongo natural gas condensate was as shown in
SuperPro Designer can help design better plants or process within existing plants to help increase profitability. Due to its flexibility, the software allowed interactively change of specifications such as operating conditions, flowsheet configuration and feed compositions to run new cases and analyse alternatives. SuperPro Designer is the only commercial process simulator that can handle equally well batch and continuous processes as well as combination of batch and continuous processes. More importantly, it has modelling capabilities which are suitable for this application [
The simulator includes mathematical models that perform cost analysis and project evaluation calculations. The project feasibility was assessed based on the Net Present Value (NPV) or Net Present Worth (NPW) profitability indicator. NPV can be defined as the difference amount between the sums of discounted: cash inflows and cash outflows; or the difference between total present value of annual cash flows and the total capital investment. It is a standard method for using the time value of money to appraise long-term projects [
Component | Chemical Formula | Molar Composition [%] | Concentration [g/l] |
---|---|---|---|
Propane | C3H8 | 0.126 | 0.113 |
Butane | C4H10 | 0.670 | 0.601 |
Pentane | C5H12 | 1.262 | 1.133 |
Hexane | C6H14 | 2.183 | 1.959 |
Heptane | C7H16 | 24.738 | 22.147 |
Octane | C8H18 | 33.883 | 30.368 |
Nonane | C9H20 | 37.264 | 33.361 |
The following assumptions and limitations were made in the process simulation:
1) JO is classified as a mixed TG: Oleic-Linoleic and therefore pure oil is an OOL molecule (or 1,2- OLEIN-3-LINOLEIN molecule), which is very rich in oleic acid [
2) FFA in JO is based on oleic acid (C18:1) since the major FA composition of JO is oleic acid (34.3% - 45.8%) [
3) Incoming crude JO may contain significant amount of solid material (light and heavy) that need to be removed and based on particle size or specific gravity, filtration or sedimentation can be applied respectively;
4) Phospholipids present in JO are of two forms: free hydratable phospholipids (HPL) and non-hydratable phospholipids (NHPL);
5) NHPL compounds are in the form of Ca2+ salts: Calcium phosphatidate (CaPA) complexes and phospha- tidic acid (PA). PA is formed after initial decomposition of CaPA by the phosphoric acid [
6) NHPL compounds are very rich in FA common in JO;
7) This simulation will not consider the treatment of waste streams;
8) The biofuel market has developed in Tanzania and so there is high supply of JO, that makes the price of JO low;
9) A new facility plant will be constructed and
10) The plant operates around the clock.
The main things which were taken into consideration for the techno-economic analysis were the raw material, pre-treatment, transformation and separation and are described in the following subsections.
In this case, the raw material is the extracted jatropha oil (crude virgin oil). The design was based on composition of crude JO as shown in
Component | Composition [% w/w] |
---|---|
Water | 0.04 |
FFA | 6.07 |
Gums | 0.1 |
LPM | 0.05 |
Pure Oil | 93.69 |
Sludge | 0.05 |
Total | 100 |
was needed to lower or remove these substances. The process components accounted for simulation were oil filters, blending tanks, a reactor, a decanter and an evaporator.
Crude JO with composition presented in
In the reactor, acid (or chemical) degumming and neutralisation takes place to remove NHPL and FFAs from the water-degummed oil before sending it to the third blending tank for blending to lower the viscosity. Phosphoric acid converts NHPL to HPL ones (acid degumming) (
Aqueous sodium hydroxide is charged in the same reactor, to convert FFA to soap (neutralisation) (
In the first filter, clear oil is separated from the light particulate matter (LPM), sludge (and some water) and any other impurities. During water degumming the HPL are hydrated with water, swells and form precipitates or gels, which are separated from clear oil by the second filter. The salts formed in the reactor as well as any other impurities are removed together with soaps and phosphatides in the third filter. In the second blending tank, water (water2) is added into the neutral oil which has been separated from soaps to wash remaining soaps or any other impurities and is removed by the liquid-liquid phase decanter before blending, to avoid phase separation problem. Water used for washing neutral oil (water2) is typical municipal quality water. The neutral oil may still contain some water after decantation. This must be lowered to a maximum of 0.5% (v/v) to meet diesel fuel (grade 4-D) specifications (ASTM D975), and is removed by evaporation.
In large scale production, the solids from water degumming and from the reactor can be separated by centrifugation. The co-product soaps (in the neutralisation step) can be sent to a storage tank for other uses instead of disposing them as waste. The other co-product(s) were sludge, LPM, wet gums, water vapour and wastewater from the washing unit. Water vapour can also be condensed and recovered; wastewater can be treated and all this water, that is, the recovered water vapour and treated wastewater can be recycled.
including engineering firms that provide liquid biofuel processing expertise, chemical or equipment suppliers, researchers and practitioners experienced with the topic under study were used to obtain the necessary parameters or operational data for each unit operation.
Name | Data Input (Amount/Value) | Operational Condition (Temperature) | Equipment/Stream |
---|---|---|---|
Crude JO: Base Total Flowrate | 5000 l/batch (or 4600 kg/batch) | 30 ±1˚C (Room Temp.) | Fed to PFF-101 |
Crude JO: Composition | Ref. | 30˚C ±1˚C | Fed to PFF-101 |
Water | 5% by volume of oil | 30˚C ±1˚C | Added to V-101 |
Pure oil | -- | 80˚C ±1˚C | In the V-102 |
Phosphoric Acid | 0.2% by volume of oil | -- | Charged to V-102 |
Sodium Hydroxide | 3.5 g/l of oil | -- | Charged to V-102 |
Water2 | 40% by volume of oil | 50˚C ±1˚C | Leaving HX-101; Added to V-103 |
Pure oil | -- | 140˚C ±1˚C | In the EV-101 |
Pure oil | -- | 30˚C ±1˚C | In the V-105 |
NGC | 10% by volume of oil | 30˚C ±1˚C | Added to V-105 |
Efficiency: Water degumming | 30% gums removal | -- | Pure oil Leaving V-101 |
Efficiency: Acid degumming | 98% gums removal | -- | Pure oil Leaving V-102 |
Efficiency: Neutralisation | 98% FFAs removal | -- | Pure oil Leaving V-102 |
Yield: pure oil (after acid degumming and neutralisation) | 97% | -- | Pure oil Leaving PFF-103 |
Yield-final: pure oil (after drying) | 97% | -- | Pure oil Leaving EV-101 |
Efficiency: Blending | 65% Viscosity Reduction | -- | MPO Leaving V-105 (Final Product) |
Name | Chemical Formula | Remarks |
---|---|---|
Jatropha oil (JO): 1,2-OLEIN -3-LINOLEIN molecule (OOL) | C57H102O6 | The major triglyceride (TG) molecule in JO [ |
Sodium Hydroxide | NaOH | Converting FFA into soap; Partial Neutralisation of Phosphatidic acid (PA)/Hydrating PA |
Oleic acid | C18H34O2 | The principal FA in the JO [ |
Phosphoric Acid | H3PO4 | Removing gums by converting NHPL to HPL |
Phosphatidic acid (PA) | C39H73O8P | Gums (NHPL): Intermediate product of acid degumming |
Calcium phosphatidate (CaPA) | C39H72O8PCa | Gums: NHPL compounds in the form of Ca2+ salts: Calcium salt of PA. Main reactant in acid degumming |
Calcium bi-phosphate salt (CBP) | CaH4P2O8 | By-product of acid degumming |
Sodium salt | C39H72O8PNa | Gums (HPL): Sodium salt of PA. Product of partial neutralisation reaction of PA |
Soap | C18H33O2Na | Product of neutralisation reaction of oleic acid (transformed FFAs) |
NGC | A mixture of hydrocarbons (C3-C9), mainly heptane, octane and nonane | Modifier: Lowers JO viscosity |
MPO | Blended oil: a mixture of PO and modifier | Modified Plant Oil: Main product: a mixture of JO and NGC |
Water | H2O | Secondary product of neutralisation reaction; hydrates (dissolves) HPL to facilitate gums removal; washing material |
The results of simulation were presented in the form of reports which were generated and saved in a temporary file in the SuperPro Designer. They were then exported to a Microsoft Excel 2007 for ease of access. There are several reports generated; each focusing on a different topic. However, only Economic Evaluation Report (EER)
and Throughput Analysis Report (THR) were presented in this paper, which provided mass balances, energy balances and economic evaluation results.
Scheduling and execution of batch operations were visualised by the equipment utilisation chart (
On one hand, Gantt chart provides access to all simulation data for every operation in every procedure provided that it is included in the scheduling. This enables easy modifications to some operating conditions and to re-compute the execution plan. Equipment utilisation chart on the other hand, displays the utilisation of the various equipment items as a function of time for a single or multiple batches (Intelligen, 2013).
The charts shows that the execution of the various process steps as a function of time for about thirty hours (30 h) produced seven (7) consecutive batches. This is well visualised in
Cost analysis and project evaluation calculations were extracted from the Excel version of the EER.
The cost of JO was set US $ 1.0/kg by assuming that the biofuel market has been developed in Tanzania and so there is high supply of JO. The average retail price of JO in an under developed biofuel market situation in Tanzania is about TShs. 4000/L (~US $ 2.5 up to 18th November 2013). The cost of NGC set was based on
Category | Value | Units |
---|---|---|
Annual Operating Time | 7919.3 | h |
Annual Throughput | 15072740.63 | kg MP |
Batch Throughput | 4639.19 | kg MP |
Plant Batch Time | 14.93 | h |
Effective Plant Batch Time | 2 | h |
Number of Batches Per Year | 3249 | |
Time Bottleneck Equipment | V-102 | |
MP = Main Product = Total Flow in MPO |
Raw Material | Unit Cost [$/kg] | Annual Amount [kg] | Cost [$/yr] | % |
---|---|---|---|---|
Phosphoric Acid | 1.000 | 2794.14 | 2794 | 0.02 |
Water | 0.375 | 877230 | 328961 | 2.1 |
Sodium Hydroxide | 0.700 | 129960 | 90972 | 0.58 |
JO | 1.000 | 14945400 | 14945400 | 95.19 |
Water2 | 0.001 | 5978160 | 2989 | 0.02 |
NGC | 0.220 | 1494540 | 328799 | 2.09 |
TOTAL | 23428084.14 | 15700000 | 100 |
Cost Item | $/Year | % |
---|---|---|
Raw Materials | 15700000 | 79.23 |
Labor-Dependent | 2242000 | 11.31 |
Equipment-Dependent | 1534000 | 7.74 |
Laboratory/QC/QA | 336000 | 1.7 |
Consumables | 0 | 0 |
Waste Treatment/Disposal | 0 | 0 |
Utilities | 2000 | 0.01 |
Transportation | 0 | 0 |
Miscellaneous | 0 | 0 |
Advertising and Selling | 0 | 0 |
Running Royalties | 0 | 0 |
Failed Product Disposal | 0 | 0 |
TOTAL | 19814000 | 100 |
Where: QC = Quality Control and QA = Quality Assurance.
TPDC selling price, which is about TShs. 350/L (~US $ 0.22 up to 18th November 2013) at commercial scale. The cost of phosphoric acid was set US $ 1.0/kg with aid from chemical suppliers and contributed only 0.02% of the total raw material cost.
The equipment-dependent costs for this process were based on depreciation, maintenance, and miscellaneous equipment expenses. Labour costs were based on the sum of the labour requirements for each unit procedure multiplied by a fixed labour rate (which was based on a basic labour rate, plus adjustments for fringe benefits, administration, and others). Utility costs were based on the type of heat transfer agent used, and the heating/ cooling requirements.
However, the essential results of cost analysis for the entire flow sheet of a plant with annual production capacity of 15,072,741 kg of MPO are shown in
Sensitivity analysis results showed the impact of changing specifications such as operating conditions, flowsheet configuration and feed compositions. The two new cases or scenarios were analysed as alternatives: First scenario: the impact of feedstock price fluctuations on MPO predicted price using the process model simulated pro-
Category | Value | Units |
---|---|---|
Total Capital Investment | 10,222,000 | $ |
Capital inv. Charged to This Project | 10,222,000 | $ |
Operating Cost | 19,814,000 | $/year |
Production Rate | 15,072,741 | kg/year of MPO |
Unit Production Cost | 1.315 | $/kg of MPO |
Total Revenues | 27,131,000 | $/year |
Gross Margin | 26.97 | % |
Return on Investment (ROI) | 57.71 | % |
Payback Time (PBP) | 1.73 | years |
Internal Rate of Return (IRR) after Taxes | 47.27 | % |
Net Present Value (NPV) (at 7.0% interest) | 28,659,000 | $ |
ducing 15,072,741 kg of MPO annually. Second scenario: the predicted unit cost of producing MPO of the adjusted annual production. This scenario simulated the impact of plant capacity to economic feasibility of MPO production.
The MPO cost showed a direct linear relationship with the cost of JO (
From Techno-economic analysis performed, the total capital investment of a plant with annual production capa- city of 15,072,741 kg of MPO is about US $ 10,222,000 (or US $ 10.2 M) with a PBP of 1.7 years and the pre- dicted unit production cost of MPO is US $ 1.315/kg at a value of US $ 1.0/kg of JO. The economic feasibility of MPO production is found to be influenced mainly by the price of feedstock, which contributes about 95% of the total annual production cost. Others are plant capacity, price of the product (MPO) and the conversion route used. These results are consistent with the results presented from other analyses on liquid biofuel production. The analysis indicates that the process technology simulated is economically viable and can be implemented in rural setting, taking into consideration Tanzania’s rural situation. The simulated model is flexible in terms of scale and process. Alternative scale or process pathways can be easily introduced to modify and assess the impacts for example that changes can have on capital and production costs. The multiple results available can then be used to find those scenarios or production systems that exhibit better performance. It also serves as the basis for future work with different POs or feedstocks. SuperPro Designer analytical tool enables a wide range of pro- cess configurations that are adapted to meet Tanzania’s conditions to be simulated within a short time.
The Authors acknowledge the financial support provided by the Policy Innovation Systems for Clean Energy
Security (PISCES) research project, which was a five-year initiative project funded by the UK’s Department for International Development (DFID). PISCES which had partners in Kenya, India, Sri Lanka, United Kingdom and Tanzania was intended to provide policymakers with information and approaches that they can apply to unlock the potential of bioenergy to improve energy access and livelihoods in poor communities. The Authors also acknowledge the Department of Chemical and Mining Engineering, University of Dar es Salaam for their co-support in this work as well as Tanzania Petroleum Development Corporation (TPDC) for supplying the natural gas condensate (NGC).