Identification of optimal strategies for sustainable energy management in Taiwan

Abstract

SUMMARY In this study, an optimization model was developed for identifying optimal strategies in adjusting the existing fossil fuel-based energy structure in Taiwan. In this model, minimization of the total system cost was adopted as the objective function, which was subject to a series of constraints related to energy demand, greenhouse gas (GHG) emission restriction, and energy balance. Feasibility of several potential energy structures was also evaluated through tradeoff analysis between energy system costs and GHG emission targets. Three scenarios were established under several GHG emission restriction targets and potential nuclear power expansion options. Under the three scenarios, optimal energy allocation patterns were generated. In terms of the total energy system cost, the scenario that restricted GHG emissions and nuclear power growth would result in the highest one, with an average annual increase of 4.2% over the planning horizon. Also, the results indicated that the energy supply structure would be directly influenced by energy cost and GHG emission reduction targets. Scenario 2 would lead to the greatest dependence on clean energy, which would take up 41.8% in 2025. In comparison, with no restriction on nuclear energy, it would replace several energy sources and contribute to 34.0% of the total energy consumption. Significant reduction in GHG emission could be identified under scenario 2 due to the replacement of conventional fossil fuels with clean energies. Under scenario 3, GHG emission would be significantly reduced due to the adoption of nuclear power. After 2015, energy structure in Taiwan would be slightly adjusted due to synthetic impacts of energy demand growth and GHG emission restriction. The results also indicated that further studies would be necessarily needed for evaluating impacts and feasibilities of clean energy and nuclear power utilization in Taiwan. Copyright © 2011 John Wiley & Sons, Ltd.