Integrated Generation–Transmission Expansion Planning With Uncertain Dynamic Line Ratings, Renewable Energy, and Electric Vehicles
Abstract
This paper examines the integrated generation and transmission expansion planning (IGTEP) problem in the presence of increasing power system demand, high penetration of renewable energy sources (RES), and growing electric vehicle (EV) charging loads. The proposed framework jointly optimizes investment and operational costs for new generation units and transmission lines, while considering the environmental benefits of RES integration and the impact of EV charging on grid operation. The inherent uncertainties in load demand, EV charging, and renewable generation are addressed through a hybrid stochastic-robust optimization approach. Dynamic thermal line rating (DTLR) is incorporated through a physics-based heat balance model to capture time-varying transmission limits driven by environmental conditions. The framework also tackles the uncertainty in DTLR, incorporating a heuristic linearization technique to reduce model complexity. Unlike conventional IGTEP approaches that rely on static line ratings or treat uncertainties independently, the proposed framework provides a unified and scalable formulation that jointly captures multi-source uncertainties, including renewable variability, EV demand, and weather-driven line ratings. The effectiveness of the proposed approach is demonstrated on the IEEE 6-bus and IEEE 118-bus systems.