A Multi-Objective Optimization Framework for Anti-Galloping of UHV Transmission Lines Using MTTMD Based on Weighted Satisfaction

Conductor galloping is known to be a complicated phenomenon as different aerodynamic characteristics, galloping mechanisms are involved. To tackle the galloping problem of ultra-high-voltage transmission lines, this study designs a torsional tuned mass damper (TTMD) with eddy current mechanism. For a full-span iced conductor with multiple TTMDs (MTTMD), motion equations of galloping are derived and discretized using the Galerkin method. A multi-objective optimization framework using genetic algorithm for anti-galloping of conductors is proposed. The optimization objectives include critical wind speed at galloping initiation, galloping amplitude and damper stroke, which cover the wind conditions with frequent occurrence and large galloping amplitude. By using satisfaction function and weighting factor for each objective, the multi-objective optimization problem is transformed into a single objective optimization problem. For the weighting factors, the Analytic Hierarchy Process and random sampling method are employed to simulate the expert decision-making process with high efficiency, and reasonable ranges of the weighting factors are available for selection. The results of a numerical study show that the MTTMD with optimum design can achieve satisfying anti-galloping effectiveness on the bundled conductor, significantly increasing critical wind speed and suppressing the galloping amplitude. The robustness of the optimization method is also verified.