Grid Topology Optimization for Congestion Management Under High Renewable Penetrations and Discrete Load Growth
Transmission grids are increasingly stressed by the fluctuating nature of renewable energy sources and by increasing electricity demand. Such grids were mainly built for a different generation fleet and load conditions. Grid topology optimization offers the possibility to redistribute power flows by modifying the busbar topology of substations in the grid. However, the combinatorial explosion of feasible busbar configurations makes topology optimization impractical for system operators. This paper proposes a methodology to identify a small subset of high-value busbar topologies to capture the economic benefit of topology optimization across a range of renewable-demand patterns. The optimization model is based on a LPAC approximation of the optimal power flow formulation, and AC-feasibility checks of the optimal topology applied to the IEEE 118-bus test case. In the test case, we select two distinct pairs of substations (46-49 and 24-69) and we optimize their topology separately over 365 clustered timesteps with different wind and load conditions. For each pair, we identify the four most recurrent optimal topologies and evaluate their performance under standard, and congested conditions, with and without a discrete load growth. Results show that selecting from this reduced set of topologies reduces total generation costs by up to 0.147% compared to a plain AC-OPF. In addition, we show the influence of topology optimization on the hosting capacity of selected busbars under discrete load growth. Our findings provide a practical methodology for system operators to select a subset of optimal busbar topologies to be used in their grid for different wind-load conditions, resulting in decreasing generation costs without the computational and operational risks of real-time switching decisions.