Multi-stage co-planning framework for electricity and natural gas under high renewable energy penetration

This study develops a new multi-stage (dynamic) approach for the co-planning of power and gas systems to deal with variable renewable energy resources (VREs). The model is formulated using a stochastic programming framework to accurately capture the unfolding of both short and long-term uncertainties faced by power and gas systems. The effects of high renewable energy penetration and renewable energy uncertainty in both systems are assessed while determining the optimal investment and operation decisions in several stages of the planning horizon. To prove the benefits of the proposed approach, the authors compare the results of the authors' framework with other methods used in the literature. The effectiveness of the framework is validated on a realistic case of Queensland, Australia, in which both networks are driven to capture the link between these systems and to accommodate the state's unique features of renewable availability. The results demonstrate that their dynamic approach provides more robust outcomes compared to other methods as it allows adapting the expansion plans to unexpected changes in the future. The analysis also shows that a transition towards renewable energy presents a higher cost, different investment strategies, and lower gas-fired consumption compared to the terminal renewable target.