Energy Investment Modeling And Its Applications Under The Background Of Energy Security And Climate Change

China has tremendous energy consumption and still with rapid growth rate. Energy resource limits and large proportion of fossil fuel consumption have made China to face serious energy security and greenhouse gas emission problems. The complexity of energy security and climate change will cause large uncertainties in China's future energy development. As pre-actvities of energy development, current NPV based energy investment evaluation or resource allocation methods can not take such uncertainties into account and manage the flexibility and strategy in energy investment. A reasonable and effective energy investment is also an important way for China to address energy and climate change issues. This dissertation based on modern financial theory, proposed a comprehensive energy investment evaluation method EIRP (Energy Investment evaluation with Real options and Portfolio theory). And based on EIRP method, several energy investment evaluation models have been established to study China's energy investment issues (overseas oil investment and low-carbon energy technology evaluation). The outline is as follows:(1) According to 'problem-oriented ideas' in management science, we start with energy investment, applying 'Real options' and 'Portfolio theory' to 'Energy Investment evaluation', and propose an uncertain energy investment evaluation method EIRP. As a methodological basis of this study, several energy investment evaluation models have been established under the framework of EIRP.(2) From the perspective of oil investment value, we establish an overseas resource countries'oil investment evaluation model based on EIRP method. With the application of real options theory we take different countries's investment factors such as tax, interest rate, oil development cost, production decline rate, and uncertainty factors like oil prices, exchange rate into a unified analytical framework. And tne investment-environment factor is also been quantified and added to oil-resource valuation. In this model an option value index (OVI) has been defiend for comparing different countries'oil-investment situation. China's overseas oil investment is taken as an example for anaysis. The results show that the model developed here can provide useful advice for China's overseas oil investment program.(3) For specific overseas oil investment projects, according to EIRP framework, we establish an overseas oil investment evaluation model. With the consideration of the complexity and dynamics in overseas oil investment, the model incorporates real options and Monte Carlo method and the model is solved by Least Squares Monte-Carlo (LSM) method. With an investee country chosen as case study, the project values of three typical sized oil fields have been calculated. And the simulations of different oil resource tax system are also presented in discussions.(4) After modeling overseas oil investment, for domestic oil supply, based on EIRP method, we apply dynamic asset allocation with stochastic programming to establish a multi-stage oil resource allocation model for oil supply resources optimization. Three kinds of oil resource (domestic production, oil trade and overseas oil investment) have been taking account into the model with the consideration of oil prices and demand uncertainties. With the model calculation we can get the optimal proportions of the three kinds of oil resources in the period from 2011 to 2030 in cost-minimize strategy for China's mid-long term oil supply.(5) According to EIRP method, with the application of portfolio theory we establish China's generating mix optimization model. Take different generating technologies as asset, with reference to the risk of relevant generating-cost streams and carbon emission cost. Based on mean-variance method we have calculated the efficient-frontier for generating technologies and generating portfolio and discussed the optimal generating portfolios that enhance energy security in different future scenarios, including CO2-emission-constrained scenarios. Some policy implications have been presented based on scenario analysis results.(6) According to EIRP framework, we establish a carbon capture and storage (CCS) investment evaluation model based on real options theory and Monte Carlo method. In this chapter we focus on the cost saving cash flows between CCS technology and existing thermal power. The model aims to evaluate the value of the cost saving effect and amount of CO2 emission reduction through investing in newly-built thermal power with CCS technology. Since the model could be used as a policy analysis tool, China is taken as a case study to evaluate the effects of regulations on CCS investment through scenario analysis. The research presented would be useful for CCS technology evaluation and related policy making.(7) For wind power concession mechanism, based on EIRP method, we apply option games to establish a model to analyze the wind power concession projects under incomplete information and preemption. With carbon trading mechanism introduced into existing concession mechanism, the model aims to analyze the behavior of investors in wind power bid auction mechanism under carbon price uncertainty, how should investors determine their own optimal bidding price, the impact of other bidders' strategy on the of investors' behavior. And we also calculated the optimal bidding price under Bayesian Nash equilibrium.(8) For third generation nuclear power technology, according to EIRP framework, we establish a nuclear power investment evaluation model by employing real options theory with Monte Carlo method to evaluate the value of third generation nuclear power plant. Nuclear accident is modeled as probabilistic unexpected events with three levels of losses. The model is used to evaluate Sanmen nuclear power plant in Zhejiang province. The impacts of three electricity price mechanisms, two carbon price mechanism, and nuclear power investment cost reduction are investigated and discussed.