This study was undertaken to scale up a 30 litre per hour biodiesel plant, model the unit operations in the production of biodiesel, automate the plant using a microprocessor based digital program, and determine the performance of the constructed plant. The scaling-up of the plant capacity to 100 liters capacity was done by use of C# visual basic software, mathematical selection of tank capacities using appropriate equations, application of flow rate, heating capacity and pipe sizing equations. The mathematical modelling of the unit operations was done by using finite difference analysis, Allen’s simulation model, and the rate equation by Arrhenius in order to simulate the effect of varying pressure on yield of biodiesel. The plant was automated using a microprocessor based digital programme. The performance of the plant was evaluated by testing the properties of the fuel produced and comparing it with ASTM stamdards. The performance was also evaluated by determing the yield and time taken to produce the biodiesel. Biodiesel was produced by reacting 120 liters of vegetable oil with 20 liters of methanol and catalyzed with 0.42 kg of Sodium Hydroxide. The results were analyzed using ANOVA at P≤0.05.
The scalabity software developed, calculated the
design parameters for pump capacity for 100 liters per hour to 10,000 liters
per hour biodiesel plant. The pump capacity for the 100 liters per hour
bidiesel plant was 0.745kW. The heater capacity was determined to be within the
range of 1500W to 2000W that was able to raise the temperature of the vegetable
oil from 37oC to 50oC within a set time of 5 minutes. The
automated controller for the biodiesel plant was able to handle varing
temperature values of 40oC to 60oC. It was also able to handle
varying inputs of time for various solenoid valves to open and close ranging
from 1 minute to 60 minutes. The automated controller handles varying values
for reaction time necessary for processing different types of oil ranging from
1 digit minute to 3 digit minutes. The modified Arrhenuis equation gave an
optimized pressure value of 1.1652 bar. The conversion percentage of biodiesel
at 50oC, 3000 revolution per minute, 30 minutes of reaction time,
and at a molar ratio of oil of 1:6, was 89.76% as against 81.13% for the
unmodified. The results of the viscosity, cetane index, flash point, relative
density, caloric value, were 3.4mm2/s, 51.824, 143.5oC, -21.44oC,
-10.37oC, 0.894g/cm3, and 128244.27kJ/kg respectively which was in
line with values from ASTM. The system material handling efficiency was 90%, at
20 minutes of reaction time with 63 liters yield of methyl ester. ANOVA at p≤0.05
shows that there was a significant difference in the results obtained from the
modified and unmodified Arrehnieus equation, which was due to the addition of
pressure. The use of the methyl ester in a Toyota Hilux Van reduced its smoke
production and the quantity used to drive (76 kilometers) to Enugu Nigeria was
6 liters as against 10 liters used of fossil diesel fuel. This show a high
caloric value.These results show a notable positive effect of pressure factor
consideration in biodiesel production. Therefore it was concluded that the
scalability software assisted in plant scaling-up, the mathematical modelling
assisted in the addition of pressure as a parameter in the optimized production
of biodiesel, the automated plant helped in increased and précised production
control, and the performance analysis showed the actual development of an
optimized biodiesel plant.
Plant design is a collaborative effort to design, optimize the yield, mass balance and integration with existing or new feedstock facilities. In most cases, biodiesel plants are designed as part of larger oilseed processing operations. It is unlikely any new plants will be constructed as “stand alone” facilities. This allows optimization of feedstock and product storage and integration with transportation and utilities. The trend is towards large facilities instead of small. The major holdback facing the biodiesel industry against building larger plants similar to the sizes used for vegetable oil refining (an industry most can relate to considering the feed stocks used for making biodiesel) is consumer demand. As demand increases, there will be little to stop an increase in the size of the average biodiesel processing plant because current biodiesel plants are nowhere near what can be considered “large.” A modern transesterification plant is continuous instead of batch. A continuous plant leads to better heat economization, better product purity, better recovery of excess methanol, minimal operator interference, and lower capital costs per unit of biodiesel produced. One particular processor that has run both batch and continuous biodiesel plants has vowed never to run a batch plant again (Paul, 2006).
The biofuel industry is fast growing in the world. Countries like Brazil, United States, United Kingdom, Germany, France and many more are increasing the budget allocation to biofuel development. Global warming and the attendant climate change issues necessitate the drive towards the carbon cut measures. Global warming entails increase in the average temperature of the atmosphere, oceans and landmass of the earth (Schnepf, 2007). Scientific evidence revealed that global warming is human induced. Its chief cause is the burning of fossil fuels such as coal, oil and natural gas by automobiles which continually release carbon dioxide into the atmosphere. According to UNDP 2007/2008 Human Development Report, the world temperature has increased around 0.7ºC since the advent of industrialization and the rate is increasing yearly. It is argued that biofuel is environment friendly because carbon dioxide release from burning biofuels is balanced by carbon dioxide intake by growing plants from where biofuels are made (United States Department of Energy, 2007). The process reduces greenhouse gas emissions. The biofuel industry also raises domestic and international income, creates wealth, employment and accelerated rural infrastructural development. In Nigeria, biofuel industry would not only aid rural development but help in economic diversification, thus making the country less dependent on petroleum as the main source of economic growth. Again, the market size of biofuel in Nigeria is another justification for the need to develop the industry in the country. In 2007 alone, fuel ethanol demanded was 1.3 billion litres, with anticipated increase to 2.0 billion litres in 2020. Biodiesel demand in 2007 was 480 million liters, with a projected demand of 900 million liters in 2020 (Azih, 2007).
There are great potentials in rural areas that would support the production of biofuel in Nigeria. About 70 percent of the country’s labour force resides in rural areas. This labour can be trained and retrained to fit innovations in the biofuel industry. The total area of Nigeria as could be seen in fig 1.1 is distributed among different utilization sector. It shows that Nigeria’s total area is 92.4 million hectares out of which 79.4 million and 13.0 million hectares are occupied by land and water respectively. Agricultural land occupies 71.9 million hectares which indicates that there is a high potential for production of agricultural produce as a biofuel feedstock.