Reduction of acidification from electricity — Generating industries in Taiwan by Life Cycle Assessment and Monte Carlo optimization

Abstract

Life Cycle Assessment (LCA) is a rather common tool for reducing environmental impacts while striving for cleaner processes. This method yields reliable information when input data is sufficient; however, in uncertain systems Monte Carlo (MC) simulation is used as a means to compensate for insufficient data. The MC optimization model was constructed from environmental emissions, process parameters and operation constraints. The results of MC optimization allow for the prediction of environmental performance and the opportunity for environmental improvement. The case study presented here focuses on the acidification improvement regarding uncertain emissions and on the available operation of Taiwan's power plants. The boundary definitions of LCA were established for generation, fuel refining and mining. The model was constructed according to objective functional minimization of acidification potential, base loading, fuel cost and generation mix constraints. Scenario simulations are given the different variation of fuel cost ratios for Taiwan. The simulation results indicate that fuel cost was the most important parameter influencing the acidification potential for seven types of fired power. Owing to the low operational loading, coal-fired power is the best alternative for improving acidification. The optimal scenario for acidification improvement occurred at 15% of the fuel cost. The impact decreased from 1.39 to 1.24 kg SO 2-eq./MWh. This reduction benefit was about 10.5% lower than the reference year. Regarding eco-efficiency at an optimum scenario level of 5%, the eco-efficiency value was − 12.4 $US/kg SO 2-eq. Considering the environmental and economical impacts, results indicated that the ratio of coal-fired steam turbine should be reduced.