Renewable Energy Supply Chain Optimization: A Challenge for Control Engineers?

Renewable energy supply chain optimization problems are characterized by a large number of options, significant amounts of uncertainty and multi-scale nature of decisions. This presentation examines these characteristics through practical examples and offers some promising research directions. The problem of large number of processing stages/options will be first introduced through a microalgae-based bio-refinery design problem. Superstructure based modeling and optimization will be presented as a tool to investigate the problem at a high level. Then, the presentation will move onto the issue of coupling between long-term planning decisions like capital investment and policy and shorter-term decisions like production capacity operation and logistics. This aspect manifests itself as a large number of decision variables and constraints complicating solution of the optimization. The optimization complexity gets greatly amplified when the issue of uncertainty is added to the problem. We will examine both two stage and multi-stage problems. Examples of biofuel processing supply chain and energy portfolio optimization for power generation will be used to bring out the essential features and complications. For solutions, stochastic programming and approximate dynamic programming will be introduced.