Interval-Stochastic Programming for Integrated Generation, Transmission, and Energy Storage System (ESS) Planning Considering Uncertainty in Renewable Energy Sources

In recent years, renewable energy sources have been expanding worldwide to create sustainable power systems. While the transition to sustainable system provides benefits such as reducing greenhouse gas emissions, it creates many problems within the system. For example, due to the volatility and uncertainty of renewable energy, problems such as an imbalance in supply and demand and a lack of flexibility are appearing. This paper focuses on these problems encountered or to be encountered globally. This paper divides the uncertainty of renewables into uncertainty due to natural variability and uncertainty due to lack of information. To address these challenges, this paper presents a new integrated planning method for generators, transmission lines, and ESS, considering uncertainties of renewable energy. An interval-stochastic programming method is introduced, using Benders decomposition method for 2-stage optimization. This paper applies a bi-objective optimization technique for decision making, and a minimum regret cost criterion. Furthermore, this paper demonstrates the effectiveness of the proposed method through numerical results based on a model of simplified Korean power system. The conclusion emphasizes the importance of ESS in integrated expansion planning to effectively manage the uncertainties of renewable energy and ensure a sustainable power system.