The islanded line-commutated-converter-based high-voltage direct-current (LCC-HVDC) transmission system is becoming a key solution for delivering multiple types of clean energy from large-scale renewable energy bases, including wind power, photovoltaic power, hydropower, and energy storage. However, the high penetration of renewable sources significantly increases the risks of frequency fluctuations and voltage violations due to their inherent volatility and uncertainty, posing serious challenges to system stability. To enhance the integration capacity of clean energy and ensure the stable operation of islanded systems, this paper proposes a maximum capacity optimization method tailored for islanded DC transmission involving multiple energy types. A K-medoids clustering algorithm is applied to historical data to extract typical wind and photovoltaic output scenarios, and a virtual balancing node is introduced. Subsequently, an active power droop control strategy and reactive power regulation are applied to enhance system frequency and voltage stability. Finally, the capacities of wind, photovoltaic, and energy storage systems are jointly optimized using particle swarm optimization. Simulation results demonstrate that the proposed approach can accurately determine the maximum allowable integration of wind and photovoltaic power while satisfying system operational constraints, and effectively reduce the required energy storage capacity.
Tao et al. (Sun,) studied this question.