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

IF 3.1 4区 工程技术 Q3 ENERGY & FUELS
Yangdi Hu, Rongrong Zhai, Lintong Liu
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Abstract

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.

风力发电/光伏发电/聚光太阳能发电与 S-CO2 布雷顿循环集成系统的能力运行协作优化
本文提出了一种新型发电系统,该系统将风力发电(WP)、光伏发电(PV)、槽式聚光太阳能发电(CSP)与超临界二氧化碳(S-CO2)布雷顿动力循环、热能储存(TES)和电加热器(EH)子系统结合在一起。带有 S-CO2 布莱顿循环系统的风力发电/光伏发电/聚光太阳能发电(WP-PV-CSP)以可再生能源为动力。首先,研究了风电/光伏/聚光太阳能发电(WP-PV-CSP)与 S-CO2 布赖顿循环系统的可再生能源驱动问题,构建了双级容量-运行协同优化模型,并提出了非支配排序遗传算法-II(NSGA-II)嵌套线性规划(LP)算法来解决该优化问题,旨在获得一组兼顾碳排放、经济性和运行调度的最优容量配置。然后,以中国风能和太阳能资源丰富的张北地区为实际应用案例,利用双级优化模型来改进系统的容量和年负荷调度。最后,它建立了三个参考系统来比较 WP-PV-CSP (S-CO2) 系统的年运行特性,突出了采用 S-CO2 布雷顿循环和配备 EH 系统的优势。经过容量-运行协同优化后,与未优化的参考系统相比,WP-PV-CSP(S-CO2)系统的平准化能源成本(LCOE)和碳排放量分别降低了 3.43% 和 92.13%。
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来源期刊
Frontiers in Energy
Frontiers in Energy Energy-Energy Engineering and Power Technology
CiteScore
5.90
自引率
6.90%
发文量
708
期刊介绍: Frontiers in Energy, an interdisciplinary and peer-reviewed international journal launched in January 2007, seeks to provide a rapid and unique platform for reporting the most advanced research on energy technology and strategic thinking in order to promote timely communication between researchers, scientists, engineers, and policy makers in the field of energy. Frontiers in Energy aims to be a leading peer-reviewed platform and an authoritative source of information for analyses, reviews and evaluations in energy engineering and research, with a strong focus on energy analysis, energy modelling and prediction, integrated energy systems, energy conversion and conservation, energy planning and energy on economic and policy issues. Frontiers in Energy publishes state-of-the-art review articles, original research papers and short communications by individual researchers or research groups. It is strictly peer-reviewed and accepts only original submissions in English. The scope of the journal is broad and covers all latest focus in current energy research. High-quality papers are solicited in, but are not limited to the following areas: -Fundamental energy science -Energy technology, including energy generation, conversion, storage, renewables, transport, urban design and building efficiency -Energy and the environment, including pollution control, energy efficiency and climate change -Energy economics, strategy and policy -Emerging energy issue
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