Optimal Capacity Configuration of Renewable Energy for Multi-Type Clean Energy Sending System via VSC-HVDC Islanded Transmission

Abstract

Wind power, photovoltaic (PV), hydropower, and energy storage, along with other multi-type clean energy sources, transmitted via islanded voltage source converter based high voltage direct current (VSC-HVDC) systems, will become an important form of delivery for renewable energy bases. However, due to the volatility and uncertainty of renewable energy, its high-proportion integration significantly exacerbates system frequency fluctuations and voltage violation risks, posing severe challenges to the stable operation of the system. To strike a balance between maximizing clean energy integration and maintaining the stability of the islanded system, this paper presents a capacity optimization approach for multiple types of clean energy within an islanded VSC-HVDC transmission system. First, typical wind power and PV output scenarios are obtained via Monte Carlo simulation, and a virtual slack bus is introduced to establish a power flow calculation model for the islanded VSC-HVDC transmission system. Second, the active power is regulated through fast VSC-HVDC support and droop control mechanisms, while a quadratic programming model for voltage is established based on the relationship between reactive power and voltage, aiming to drive the virtual slack bus power to zero, thereby improving system frequency and voltage stability. Finally, a genetic algorithm (GA) is employed to achieve optimal capacity configuration for maximizing renewable energy integration, and the corresponding optimal energy storage capacity is determined accordingly. Simulation results demonstrate that, while satisfying operational constraints, the proposed method identifies the maximum installable capacities of wind power and PV while simultaneously reducing the required energy storage capacity.