Identifying Best Candidates for Busbar Splitting

TL;DR

The paper tackles grid congestion driven by rising demand and renewables by proposing a screening framework for busbar splitting (BuS) that avoids exhaustive testing. It introduces three metrics, φ (sum of $|\Delta_{LMP}|$), ξ (count of congested branches), and ζ (binding voltage limits), derived from AC analysis to pre-select promising BuS candidates, then validates these candidates using a combined BuS model with LPAC-BuS and AC-OPF feasibility checks. Across test systems from 39 to 3374 buses, the metrics effectively identify buses whose topology optimization reduces total generation costs, while dramatically reducing computational effort compared with exhaustive testing. The work demonstrates practical potential for grid operators to efficiently target BuS actions, enabling scalable topology optimization and informing planning for future grid expansions and RES integration.

Abstract

Rising electricity demand and the growing integration of renewables are intensifying congestion in transmission grids. Grid topology optimization through busbar splitting (BuS) and optimal transmission switching can alleviate grid congestion and reduce the generation costs in a power system. However, BuS optimization requires a large number of binary variables, and analyzing all the substations for potential new topological actions is computationally intractable, particularly in large grids. To tackle this issue, we propose a set of metrics to identify and rank promising candidates for BuS, focusing on finding buses where topology optimization can reduce generation costs. To assess the effect of BuS on the identified buses, we use a combined mixed-integer convex-quadratic BuS model to compute the optimal topology and test it with the non-linear non-convex AC optimal power flow (OPF) simulation to show its AC feasibility. By testing and validating the proposed metrics on test cases of different sizes, we show that they are able to identify busbars that reduce the total generation costs when their topology is optimized. Thus, the metrics enable effective selection of busbars for BuS, with no need to test every busbar in the grid, one at a time.

Figures (5)

• Figure 1: Steps behind the topology optimization model proposed in BastianelBastianel_2025. The selected busbar $i$ (left) is split into two buses $i$ and $i'$, connected through a busbar coupler. The open/close position of this busbar coupler is represented by the binary variable $ZIL_{ii'}$. Each network element that was connected to busbar $i$ in the input topology is linked to an auxiliary bus (named $m,n,o$ and $p$ in the figure) and can be connected to either one ($i$) or the other part ($i'$) of the split busbar through a switch (center). After the optimization, the inactive switches are removed to yield the new topology (right).
• Figure 2: For each bus in 39-bus test case, the optimal topology from the LPAC-BuS model is tested for an ("AC"- and "LPAC"-) OPF feasibility check (FC). The differences in total costs of the FC compared to the original OPF are plotted on the x-axis, while the y-axis orders the busbar according to each bus' sum of the absolute differences in LMPs over the branches connected to it ($\phi$). The LPAC-FC and AC-FC see reductions in costs for the same buses.
• Figure 3: Topology optimization model applied to busbar 69 in the 118-bus test case. In the optimized topology, busbars 47 and 49 are decoupled from busbar 69 and the neighboring busbars, leading to a reduction in the total generation costs of 0.380% compared to the original AC-OPF.
• Figure 4: Cost decrease of the AC-OPF feasibility check for the optimized topology of the selected busbars compared to the results obtained by splitting one busbar at a time for case 793-bus. Most of the busbars selected with the identified metrics do lead to a reduction in generation costs. The busbars with the highest cost decrease tend to have a sum of the absolute differences in LMPs over the branches connected to it ($\phi$) higher than the mean $\phi$ value.
• Figure 5: Cost decrease of the AC-OPF feasibility check for the optimized topology of the selected busbars compared to the results obtained by splitting one busbar at a time for case 3374-bus. The proposed metrics identify several busbars leading to the highest reductions in generation costs.