| Summary: | 博士 === 國立成功大學 === 資源工程學系碩博士班 === 101 === Due to energy depletion and global warming, the development of green industry has become a major energy policy issue and seeks to achieve the goals of energy conservation and reduction of carbon emissions. But nowadays, new and renewable energy (RE) investment was still not to achieve the cost-benefit. Therefore, the government must assess the return on investment of its policies in order to determine the effectiveness of those policies. Thus, the development policy of new energy industry would not only yield economic and environmental benefits, but also positively impact new energy policy planning.
This study presents a value evaluation model that integrates learning curve model and grey forecasting model on new and renewable energy technologies into real option analysis (ROA) methods. The proposed model evaluates quantitatively the policy value provided by developing new and renewable energy in the face of uncertain fossil fuel prices and new and renewable energy policy-related factors. The economic intuition underlying the policy-making process is elucidated, while empirical analysis illustrates the option value embedded in the current development policy in Taiwan for new and renewable energy. In addition, the study employs learning curve to explore the learning effect of power generation, and examines whether firms can actually boost power generation cost efficiency through government subsidies and R＆D. Due to the difficulty of obtaining data, the grey system is used to ease data collection difficulties.
In summary, the proposed policy value evaluation model measures uncertainty and other factors affecting new and renewable energy industry development policy. The evaluation model can shed light on the value of policy implementation. Additionally, the proposed model can forecast cost efficiencies of new technologies when available data are limited, especially in the case of new and renewable energy technologies.
|
|---|
