Sustainable energy hub design under uncertainty using Benders decomposition method

A sustainable framework for optimal design of an energy hub (EH), which aims to determine the optimal size of the candidate distributed energy resources (DERs), is proposed in this paper by providing a modeling framework to consider environmental (Env) and social (Soc) impacts of the EH. In order to determine the Env and Soc impacts, the life cycles of different components are analyzed. The external cost method is employed to model the Env and Soc impacts. Also, a two-stage stochastic programming method is utilized to address different uncertainties such as wind speed and solar radiations as well as electricity and heat demands. The problem is formulated as a mixed integer linear programming (MILP). In the optimal EH design problem, the optimal dispatch of DERs should be determined, which leads to a large optimization problem. Benders decomposition (BD) algorithm is used to decompose the original problem in order to address heavy computational burden of the problem, especially when a large number of scenarios is used to properly represent uncertainties. The simulation is performed on a case study which shows the effectiveness of using the BD. In addition, the impacts of taking external cost into consideration on the optimal configuration are investigated.