首页|Capacity-operation collaborative optimization of the system integrated with wind power/photovoltaic/concentrating solar power with S-CO2 Brayton cycle
Capacity-operation collaborative optimization of the system integrated with wind power/photovoltaic/concentrating solar power with S-CO2 Brayton cycle
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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.
wind power/photovoltaic/concentrating solar power(WP-PV-CSP)supercritical carbon dioxide(S-CO2)Brayton cyclecapacity-operation collaborative optimizationsensitive analysis
Yangdi Hu、Rongrong Zhai、Lintong Liu
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School of Energy,Power and Mechanical Engineering,North China Electric Power University,Beijing 102206,China
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