The Application Of Radial Basis Collocation Method And Multi-grid Particle Swarm Algorithm In Investment Project Of Coal Bed Methane Pricing

With the rapidly developing of global economy, energy demand is increasing gradually and hazard of traditional energy is emerging apparently. Nowadays, new energy has been widely used in developed countries and forms mature markets. Since the lag in technology of developing country, the developments and implements of new energy are at initial stage and their markets are immature. This causes investors’hesitation when they are facing a new energy investment project and it also hinders the popularization in developing country to a large extent. Therefore, it is an important and difficult problem about harmonic sustainable development between economy and environment that pricing the new energy investment project fairly.Coal bed methane refers to the methane store in coal bed which is a kind of clean energy. It has been arousing public concern, since it only produces 5% of greenhouse gas of natural gas when it burnt out. This energy has been extensively used by Unite States at present and formed a strong market. China is the third country in the world that has rich reserve of coal bed methane. However, it is not popular in China partly because of the uncertainty of the investment project and its difficulty of pricing. Although traditional pricing methods of investment project are simple, the model errors are large.This thesis establishes pricing model of coal bed methane investment project as well as policy optimization model in the view of real options based on Chinese actual market conditions and policy background. We also discretize the multi-dimension partial differential equation by radial basis collocation method, solve the free boundary problem by moving boundary method, and optimize the complicated function by multi-grid particle swarm algorithm.This thesis has been divided into six chapters. Chapter one mainly talks about the background and significance of this paper. And it also analyzes the contents and determines technical roadmap of this thesis. Chapter two introduces some related notations and theories and describes traditional pricing method of real options. Chapter three analyzes market factors about coal bed methane investment project and then establishes its pricing equation based on stochastic process theories and real options model. Some properties about optimal exercise boundary have been elaborated. What is more, radial basis collocation method and moving boundary method have been also introduced there to solve this problem. Chapter four analyzes government expected objective in investment and establishes policy optimization model based on pricing model. And this model is solved by multi-grid particle swarm algorithm proposed in this thesis. Relevant computational results have been shown in Chapter five to verify our model. Chapter six summarizes our research and discuss the innovations and defects of our research. Our research provides new thinking for other investment project pricing problems and policy optimization problems. Also, it promotes applications of real options theories in R&D and investment projects.