Comprehensive optimization framework for transmission expansion planning with fractional frequency transmission system

The Fractional Frequency Transmission System (FFTS) operates with low frequency to decrease the electrical length of AC transmission lines, consequently enhancing transmission capacity. The integration of renewable energy sources via FFTS will significantly impact power system planning. This paper presents a Fractional Frequency Transmission Expansion Planning (FF-TEP) model, which considers the interaction between FFTS and the industrial-frequency power grid. This model addresses the challenges posed by the integration of offshore wind power through FFTS, and takes several key factors into account, including the active power coupling of Modular Multilevel Matrix Converter (M3C), inverter capacity, and converter transformer capacity. To address the non-convexity caused by AC power flow, this paper introduces a Genetic-Particle Swarm Optimization algorithm (G-PSO) with dynamic penalties tailored to the M3C structure. This approach incorporates both crossover and mutation operators from Genetic Algorithms (GA) into Particle Swarm Optimization (PSO). The penalty function dynamically adapts according to the M3C structure, resulting in improved global optimization while maintaining computational efficiency. The results of two case studies demonstrate that FFTS can significantly enhance transmission capacity while reducing cable charging power. This reduces investment costs and decreases voltage offset issues. This paper presents a Fractional Frequency Transmission Expansion Planning model, which considers the interaction between Fractional Frequency Transmission System and the industrial-frequency power grid. To address the non-convexity caused by AC power flow, this paper introduces a Genetic-Particle Swarm Optimization algorithm with dynamic penalties tailored to the M3C structure.image