Impacts of Uncertainty and Increasing Returns on Sustainable Energy Development and Climate Change: A Stochastic Optimization Approach

Abstract

In this article we discuss a stochastic optimization model used for evaluation of long-term energy development. The model includes the following features:

• 1. Increasing returns to scale for the costs of new technologies with uncertain learning rates;

• 2. Uncertain costs of all technologies and cost/quantities for energy sources, both renewable and depletable;

• 3. Uncertainties in future energy demands and their volatilities;

• 4. Uncertain environmental constrains;

• 5. Clusters of linked technologies that induced technological advances.

In particular, this allows us to identify robust dynamic technology portfolios, which supply (in a sense) potential energy demand, while minimizing adjusted to risks expected costs together with investment and environmental risks. Formally, the discussed problem involves a non-convex, large-scale stochastic optimization model requiring special global optimization technique which takes advantage of the specific structure of the problem.

This article primarily concentrated with main motivations, critical importance of non-convexity (increasing returns) and explicit treatment of uncertainty by using stochastic optimization approach.