风光水火储多能互补能源基地电源容量规划研究

李祥; 龚里; 陆峥; 周航; 李夏阳; 黄泽毅; 李佩杰

doi:10.19666/j.rlfd.202505117

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风光水火储多能互补能源基地电源容量规划研究

热力发电 2026年55卷第2期页码：139-146

多类型储能辅助调峰调频技术 | 更新时间：2026-08-07

- 风光水火储多能互补能源基地电源容量规划研究
- Power generation capacity planning for multi-energy complementary energy base including wind, solar, hydropower, thermal power and energy storage
- 作者机构：
  
  1. 中国能源建设集团广西电力设计研究院有限公司
  2. 广西电力系统最优化与节能技术重点实验室(广西大学)
- 作者简介：
- 基金信息：
  
  国家自然科学基金项目（52267006）~~
- DOI：10.19666/j.rlfd.202505117
  中图分类号： TM61
- 纸质出版：2026
- 稿件说明：
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[1]李祥,龚里,陆峥,等.风光水火储多能互补能源基地电源容量规划研究[J].热力发电,2026,55(02):139-146.
[1]李祥,龚里,陆峥,等.风光水火储多能互补能源基地电源容量规划研究[J].热力发电,2026,55(02):139-146. DOI： 10.19666/j.rlfd.202505117.

DOI：10.19666/j.rlfd.202505117.

摘要

随着电源结构逐步向多元化格局转变，区域性新能源消纳风险增大。为最大限度地利用现有的水电和火电调节能力，提升风电与光伏的消纳水平，构建了包含风电、光伏、水电、火电以及储能的多能互补能源基地，分析了风光水火储互补发电相比于其他发电模式的优势，并基于全年8 760个时序点，构建了兼顾系统可靠性、经济效益、环境效益、新能源消纳水平的多目标电源容量规划模型，通过目标函数单位标准化的线性加权法实现了多目标优化，最后选取某地的年历史风光数据进行了仿真实验。结果表明：相比于单目标优化，多目标优化能够有效权衡不同优化目标之间的平衡点，避免单一目标优化的局限性，并通过合理调节水电、火电和储能的出力，实现风光水火储在多时间尺度上的互补协同。

Abstract

As the power supply structure gradually shifts toward a diversified pattern

the risk of regional renewable energy consumption increases. In order to maximize the utilization of the existing adjustment capacity of hydropower and thermal power and improve the consumption level of wind power and photovoltaic power

a multienergy complementary energy base including wind power

photovoltaic power

hydropower

thermal power and energy storage is constructed

and the advantages of complementary power generation among wind power

photovoltaic power

hydropower

thermal power and energy storage compared to other power generation modes are analyzed. Based on 8 760 time series points throughout the year

a multi-objective power generation capacity planning model that takes into account system reliability

economic benefits

environmental benefits

and the consumption level of renewable energy is constructed

and multi-objective optimization is achieved through the linear weighting method of unit standardization of the objective function. Finally

the annual historical wind and solar data of a certain place are selected for simulation experiments. The results show that

compared with singleobjective optimization

multi-objective optimization can effectively balance the equilibrium points among different optimization objectives

avoid the limitations of single-objective optimization

and by rationally adjusting the output of hydropower

thermal power and energy storage

the complementary coordination of wind power

photovoltaic power

hydropower

thermal power and energy storage on multi-time scales can be achieved.

关键词

Keywords

references

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