A Stochastic Programming Approach for Energy Hubs Integrated with Renewable Energy Sources Based on Life Cycle Cost

Abstract

This study presents a stochastic programming approach to plan the energy hub integrated with renewable energy sources. Energy hub offers significant advantages in energy services such as enhancement of the efficiency, reduction of the emissions and costs, increase of the flexibility and reliability of the system but it has side effects due to the uncertainty of renewable energy sources, energy demands, and prices. Hence, the model with the objective function, which minimizes the expected life cycle cost, simultaneously considers many different technologies of renewable energy sources with the intermittent generation power and uncertainty of energy demands and prices. The uncertainty of parameters is modeled by probability density function then scenarios are generated by scenario matrix from all states of the parameters. The scenario reduction technique is applied to reduce the computational burden. Finally, the proposed model is simulated by GAMS/BONMIN for a test energy hub to illustrate the feasibility and effectiveness compared to the previous approaches.