The economic costs of three biodiesel plants with capacities of 8000, 30 000, and 100 000 tons year -1 were analyzed and assessed. The plants employ continuous processes using an alkali catalyst and the raw material of soybean oil. Six major economic cost factors were computed and examined. These include the fixed capital cost (FCC), total capital investment cost (TCC), total manufacturing cost (TMC), net annual profit after taxes (NNP), after-tax rate of return (ARR), and biodiesel break-even price (BBP). The NNP and ARR of plants with capacities of 8000, 30 000, and 100 000 tons year -1 are -24 × 10 3 , 1975 × 10 3 , and 8879 × 10 3 U.S. dollars (USD), and -10.44, 40.23, and 67.38%, respectively. The values of BBP of the three plants are 862, 724, and 678 USD ton -1 (price in July 2007). The plant with a capacity of 100 000 tons year -1 is economically feasible, providing a higher NNP and more attractive ARR with a lower BBP. Among the system variables of the plants examined, plant capacity, price of feedstock oil and diesel, and yields of glycerine and biodiesel were found to be the most significant variables affecting the economic viability of biodiesel manufacture. In summary, this study aims at the need to obtain useful information for economic cost analysis and assessment of the production process of biodiesel using soybean oil. It provides an appropriate indication for the promotion of biodiesel in the future, targeting the reduction of the cost of feedstock oil with the increase of the yields of valuable products with a reasonable plant capacity.

No abstract

A new approach based on linear quadratic regulation (LQR) method is applied in this study to evaluate control strategies being decided by the optimal load reduction rates of influent nutrient for eutrophication management in a reservoir. Due to dynamic fluctuations occurring in the reservoir, proper adjustment of control strategies to the variations in water quality becomes necessary. Hence, to yield optimum results, a dynamic control strategy for the reservoir is needed. Feitsui Reservoir in northern Taiwan is used as a case study for the the models developed. Monitoring data obtained from Feitsui Reservoir is employed to verify the proposed method.A time invariant state-space eutrophication model is adopted in this study to predict the trophic state in the reservoir. The eutrophication model includes five water quality constituents (chlorophyll-a, NHrN, NOrN, N0 3 -N and P0 4 -P) and the LQR method is extended to the multi-variable system. Water quality in the reservoir is found to be mainly influenced by pollutants from nonpoint sources, particularly from agricultural activities. Moreover, hydrologic condition is also found to signifiicantly affect the trophic state. The trophic state in the reservoir is predicted by using the eutrophication model in combination with an ARMA (autoregressive/moving average) inflow model. Results of this study show that the state-space eutrophication model can predict water qualities well with limited data. Also, optimal dynamic control enables the reservoir operator to maintain the trophic level below a certain trophic state. The advantages of the proposed approach include: 1) the versatility of dealing with the multi-variable system, and 2) an efficient and economic management through dynamic optimization scheme for the control of reservoir eutrophication.

No abstract