Title

Multistage Energy System Planning under Uncertainties;Optimal Design of Biofuel Production System and Resource Allocation: A California Case Study

Abstract

Multistage Energy System Planning under Uncertainties

This talk focuses on multistage energy systems modeling, especially addressing issues of uncertainties through stochastic and dynamic modeling approaches. The annual feedstock seasonality issue will be first discussed under an uncertain decision making environment. For long-term strategic plans (e.g., fuel cell vehicle market penetration over decades), the question is how to reach those goals in a smooth and reliable manner. This requires transitional system planning strategies. Some major issues involved in this transition including evolving technology and dynamic societal needs are addressed in a dynamic programming framework.

Optimal Design of Biofuel Production System and Resource Allocation: A California Case Study

A well designed biofuel production system may alleviate greenhouse gas emission and energy security issues. An important question is how to maintain a low-cost and low-risk biofuel supply system under future uncertainties such as demand, supply, and technologies. A two-stage stochastic programming model is developed for an entire biofuel pathway with the goal of minimizing the total expected system cost. To overcome the computational challenges encountered in solving the large-scale problem, an effective decomposition method based on progressive hedge (PH) method is implemented.