This paper proposes a new power generating system that combines wind power (WP), photovoltaic (PV), trough concentrating solar power (CSP) with a supercritical carbon dioxide (S-CO₂) Brayton power cycle, a thermal energy storage (TES), and an electric heater (EH) subsystem. The wind power/photovoltaic/concentrating solar power (WP–PV–CSP) with the S-CO₂ Brayton cycle system is powered by renewable energy. Then, it constructs a bi-level capacity-operation collaborative optimization model and proposes a non-dominated sorting genetic algorithm-II (NSGA-II) nested linear programming (LP) algorithm to solve this optimization problem, aiming to obtain a set of optimal capacity configurations that balance carbon emissions, economics, and operation scheduling. Afterwards, using Zhangbei area, a place in China which has significant wind and solar energy resources as a practical application case, it utilizes a bi-level optimization model to improve the capacity and annual load scheduling of the system. Finally, it establishes three reference systems to compare the annual operating characteristics of the WP–PV–CSP (S-CO2) system, highlighting the benefits of adopting the S-CO₂ Brayton cycle and equipping the system with EH. After capacity-operation collaborative optimization, the levelized cost of energy (LCOE) and carbon emissions of the WP–PV–CSP (S-CO₂) system are decreased by 3.43% and 92.13%, respectively, compared to the reference system without optimization.

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