Capacity-operation collaborative optimization of the system integrated with wind power/photovoltaic/concentrating solar power with S-CO2 Brayton cycle

The integration of renewable energy sources such as wind power (WP) and photovoltaics (PV) is crucial for transitioning away from fossil fuels. However, the intermittent and unstable nature of WP and PV limits their grid compatibility. Concentrating solar power (CSP) with thermal energy storage (TES) offers a stable and dispatchable power supply, which can complement variable renewables. Previous studies have often focused on system performance or single-objective optimization, neglecting the synergistic optimization of system capacity and operational scheduling.

In an article published in Frontiers in Energy, Yangdi Hu, Rongrong Zhai, and Lintong Liu from North China Electric Power University proposed a novel WP–PV–CSP system integrated with a supercritical CO₂ (S-CO₂) Brayton cycle, TES, and an electric heater (EH). The study introduces a bi-level capacity-operation collaborative optimization model, solved using a nested NSGA-II and linear programming algorithm. Key innovations include the fully renewable-driven system design and a hybrid AHP-Entropy-TOPSIS method for selecting the optimal compromise solution from Pareto results.

The authors developed mathematical models for each subsystem—PV, WP, CSP with S-CO₂ Brayton cycle, TES, and EH—and formulated a bi-level optimization framework. The upper level minimizes levelized cost of energy (LCOE) and carbon emissions, while the lower level maximizes renewable energy utilization through operational scheduling. Using real meteorological and load data from Zhangbei, China, the model identified an optimal configuration: 167 MW CSP, 72 MW PV, 31.8 MW WP, 7-hour TES, and 45 MW EH. After optimization, LCOE and carbon emissions were reduced by 3.43% and 92.13%, respectively, compared to an unoptimized reference system.

This work demonstrates that collaborative capacity and operation optimization can significantly enhance the economic and environmental performance of hybrid renewable systems. The use of the S-CO₂ Brayton cycle and EH improves efficiency and reduces curtailment. Sensitivity analysis further reveals the interdependence among system components, providing practical insights for the design and dispatch of future integrated renewable energy systems.

Original source:

https://link.springer.com/article/10.1007/s11708-024-0922-z

https://journal.hep.com.cn/fie/EN/10.1007/s11708-024-0922-z

Shareable link：

https://rdcu.be/eRYUG