Niigata University and TERI collaborated in developing a biomass gas turbine system with an enhanced fuel applicability for rural villages in south Asia. This paper describes a mixed and standard type gas turbine system for this purpose. The mixed type gas turbine employs a regenerated Brayton cycle with a secondary combustor to burn various fuels. The thermodynamic analysis revealed that the mixed type gas turbine system has a capability to achieve the thermal efficiency between a regenerated Brayton cycle and a complete external fired system. An experimental test was done using mixtures of bio diesel fuel and kerosene. It demonstrated that the engine performance changed only slightly with regard to the mixture ratio. In the experiment, a prototype biomass gas turbine was able to achieve the 600 W power generation. The mixed fuel with the mixture ratio of bio fuel up to 60 % was confirmed to be applicable to the current gas turbine system.
The purpose of this study is to investigate conventional photovoltaic (PV) and concentrator photovoltaic (CPV) system performance. The CPV system is operational in Okayama, Japan. The impact of different climates conditions on the system is studied. The system has been collecting data since 2011. The relationship between CPV performance and the environment is more complex than that of the conventional flat-plate PV. It is important to define the primary factors leading to these differences and accelerate installation as a clean energy generation. One of the factors is spectral distribution. Furthermore, the relationship between the I-V characteristics of the system and the environment parameter is discussed.
Effect of addition of CaO and ZrO2 to MgO/SiO2 catalyst, which is effective for synthesis of High Quality BioDiesel (HiBD) was investigated using atmospheric agitated reactor at 430°C and LHSV = 0.3 h-1. Binary MgOCaO/SiO2 and MgO-ZrO2/SiO2 catalysts and ternary MgO-CaO-ZrO2/SiO2 catalyst were prepared by the incipient wetness impregnation method. Physical properties of these catalysts were characterized by XRD and BET methods. Both the fatty acids and the triglycerides in waste cooking oil were converted into hydrocarbon gases, CO, CO2, water and hydrocarbon oil. CaO- and/or ZrO2-added catalysts gave higher CO2 yields than MgO/SiO2 alone, and showed lower acid values. These observation indicates that the added oxides promote the decarboxylation reactions. Iodine values also decreased to some extent by the addition of these oxides.
Studies on palm oil cogeneration systems, and design and analysis to further improve the energy efficiency have been done based on process integration technology. The products during cogeneration are crude palm oil (CPO) and solid wastes which come from empty fruit bunches, fibers and nutshells. However, factors affecting the production of biomass and biofuel from solid wastes and crude palm oil from oil palm fruit bunches for the boiler-based and combustion-based cogeneration can be further explored. This study hence aims to determine these factors, and then expound further in forecasting the production volume of biomass fuel and biofuel produced during cogeneration. For this purpose, the multiple regression (MR) technique is employed, and the results based on the mathematical modelling concept are thus compared. Mathematical models on the production of oil palm fruit bunches are developed via the model-building processes. Data variables are transformed using the ladder-power transformation method from a data set of 31 observations. Two models are developed, namely, Model I is for the production volume on biomass fuel from fresh oil palm fruit bunches, while Model II is the production volume on liquid biofuel from crude palm oil (CPO). There are five independent variables in Model I, and four independent variables in Model II. The four-phase in multiple regression model-building are carried out to change the non-normal data to normality. The best model obtained by the model transformation method in Model I is M72.2.5 where the main factor is the total workers employed during last pay period, and interaction factors up to the second order are: harvested area interact with yield per hectare, harvested area interact with local delivery average price, harvested area interact with total workers employed during last pay period, yield per hectare interact with local delivery average price, harvested area interact with local delivery average price interact with total workers employed during last pay period and yield per hectare interact with local delivery average price interact with total workers employed during last pay period. The significant factors on the biomass production are the yield per hectare and the harvested area of the oil palm fruit bunches. The mean absolute prediction error (MAPE) value for the best model on model transformation Model II is 2.62 %. Thus, the best model using the model transformation method is said to be excellent and acceptable to forecast for the production volume of biomass fuel and biofuel during cogeneration.