Optimal Splitting Sections Searching Method for Power Systems with Grid-Forming Wind Turbines Based on Branch Transient Potential Energy

Controlled islanding is the last line of defense to prevent blackouts in power systems. This paper proposes a novel optimal splitting sections searching method for power systems with grid-forming (GFM) wind turbines, based on branch transient potential energy. First, an improved generator internal node potential energy is defined to uniformly characterize the transient energy accumulation of both synchronous generators and GFM wind turbines; coherent generator groups are then identified using K-means clustering. Second, a splitting sections searching model is formulated with the objective of minimizing the sum of branch stability indices (BSIs) on the splitting sections. An island inertia constraint is introduced as a penalty term to address the reduced system inertia caused by grid-following (GFL) wind turbines. An improved biogeography-based optimization (BBO) algorithm integrated with tabu search (TS) is employed for the solution. Finally, simulations are conducted on a modified New England 39-bus system. The results demonstrate that, compared to traditional models focusing on power imbalance or power flow disruption, the proposed method achieves better frequency and voltage stability in the formed islands, although this improvement comes at the cost of increased load shedding in certain scenarios. In power systems with GFM wind turbines, both frequency and voltage deviations are reduced, thereby validating the effectiveness of the proposed method in enhancing island stability.