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面向海上风电高效利用的水下抽水蓄能容量优化配置分析

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为应对以海上风电为代表的海洋新能源并网挑战,水下抽水蓄能(underwater pumped hydro storage,UPHS)受到日益广泛的关注.然而,现有UPHS研究聚焦点距能源电气领域较远,尚无对现实储能工程的容量配置和规划的深入分析.针对此问题,立足(准)稳态视角,围绕水下抽蓄的容量优化配置开展研究.首先,明确海上风电-UPHS系统结构,基于水下抽蓄原理与风电出力特性建立系统模型;之后,以最大化投资收益为目标,构建UPHS容量优化配置模型,求解目标算例风速条件下风电机组、水下储能的最佳容量与实时出力;最后,围绕UPHS关键参数对规划结果的影响开展对比分析.结果表明,水下储能的引入可以大幅提升远海风电场的建设规模与投资收益;同时建设尺寸、利用小时数等储能参数亦会对规划结果产生多角度影响.
Underwater Hydro Pumped Storage Optimized Capacity Configuration for Offshore Wind Power Utilization
Underwater energy storage is receiving increasing attention to address the challenges of integrating marine renewable energy,represented by offshore wind power,into the power grid.Underwater pumped hydro storage(UPHS)is typical of these energy storage methods.However,the focus of existing research on UPHS is far from the electrical and energy field,and there is no in-depth analysis of capacity allocation and planning of real energy storage projects yet.To solve this problem,this paper researches the UPHS optimization configuration problem from the(quasi-)steady state perspective.Firstly,the structure of the offshore wind farm(OWF)and UPHS combined system is clarified,and a system model is established based on the principle of UPHS and wind turbine characteristics.After that,a mathematical model to derive the optimal capacity allocation is built to maximize investment return.Optimal capacities and real-time outputs of OWF and UPHS are solved under certain wind speed conditions.Finally,a comparative analysis of some key parameters is carried out to show their impacts on energy storage planning.Results show that UPHS can significantly improve the construction scale and investment returns of OWFs;meanwhile,the size and utilization hours also have multi-dimensional influences on the planning decision.

underwater pumped hydro storage(UPHS)underwater energy storagecapacity configurationoffshore wind power

王晰、苏开元、谢小荣

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新型电力系统运行与控制全国重点实验室(清华大学电机系),北京市海淀区 100084

水下抽水蓄能 水下储能 容量配置 海上风电

国家自然科学基金国家自然科学基金清华大学-丰田联合研究基金

51925701U22B2010020223930081

2024

电网技术
国家电网公司

电网技术

CSTPCD北大核心
影响因子:2.821
ISSN:1000-3673
年,卷(期):2024.48(4)
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