
1.成都城电电力工程设计有限公司,四川省 成都市 610000
2.西南交通大学唐山研究院,河北省 唐山市 063000
Received:29 October 2024,
Revised:2024-12-30,
Published:31 December 2025
移动端阅览
罗斌,白小龙,臧天磊等.风光水互补发电系统研究综述[J].发电技术,2025,46(06):1097-1111.
LUO Bin,BAI Xiaolong,ZANG Tianlei,et al.Review of Research on Wind-Solar-Hydro Complementary Power Generation Systems[J].Power Generation Technology,2025,46(06):1097-1111.
罗斌,白小龙,臧天磊等.风光水互补发电系统研究综述[J].发电技术,2025,46(06):1097-1111. DOI: 10.12096/j.2096-4528.pgt.24231.
LUO Bin,BAI Xiaolong,ZANG Tianlei,et al.Review of Research on Wind-Solar-Hydro Complementary Power Generation Systems[J].Power Generation Technology,2025,46(06):1097-1111. DOI: 10.12096/j.2096-4528.pgt.24231.
目的
2
以风光水为主的可再生能源发电是实现“双碳”目标的现实途径之一,因此有必要对日益成熟、渐成体系的风光水互补发电系统的研究进行综述。
方法
2
首先,概述了风光水互补发电系统的研究背景与工作原理。随后,回顾了风光水互补发电系统的研究进展,包括风光水多能源功率预测、配置比例评估、一体化调度、结合储能技术的风光水互补等研究。
结果
2
风光水预测在时间尺度上难以同步,且短期精度不如水电;容量配比主要采用比较优选法和直接求优法;一体化调度以不确定性建模为主流,智能优化算法在求解非线性问题上优于传统算法;储能技术中抽水蓄能与新型储能的混合配置最具发展前景。
结论
2
未来可从提升多尺度协同预测精度、增强水电及储能灵活调节能力、建设智能调度平台、优化建模求解算法4个方面寻求突破,以支撑我国“十四五”清洁能源体系建设。
Objectives
2
Renewable energy generation primarily using wind
solar
and hydro power is one of the practical approaches to achieving the dual carbon goals. Therefore
it is essential to review the research on the increasingly mature and gradually systematized wind-solar-hydro complementary power generation systems.
Methods
2
Firstly
the research background and working principle of the wind-solar-hydro complementary power generation systems are outlined. Subsequently
the research progress on the systems is reviewed
including wind-solar-hydro multi-energy power prediction
configuration ratio evaluation
integrated scheduling studies
and research on wind-solar-hydro complementarity combined with energy storage technologies.
Results
2
Wind-solar-hydro forecasting faces temporal scale synchronization challenges
with short-term accuracy inferior to hydropower forecasting. The comparison optimization method and the direct optimization method are mainly used to evaluate the capacity ratio. Integrated scheduling predominantly utilizes uncertainty modeling approaches
with intelligent optimization algorithms demonstrating superiority over conventional algorithms in solving nonlinear problems. Hybrid configurations of pumped storage and emerging energy storage technologies exhibit the most promising development prospects.
Conclusions
2
In the future
breakthroughs are required in four key areas: enhancing multi-scale coordinated forecasting accuracy
strengthening flexible regulation capabilities of hydropower and energy storage
constructing intelligent scheduling platforms
and optimizing modeling and solution algorithms
thereby supporting China’s 14th Five-Year Plan for clean energy system construction.
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