[1]王明东,周政宇,杨宏杰,等.考虑光伏预测误差和并网波动率的储能容量配置[J].郑州大学学报(工学版),2025,46(06):75-83.[doi:10.13705/j.issn.1671-6833.2025.06.005]
　WANG Mingdong,ZHOU Zhengyu,YANG Hongjie,et al.Consideration of Dual-layer Hybrid Energy Storage Capacity Configuration Accounting for Photovoltaic Forecasting Errors and Grid Fluctuation Rates[J].Journal of Zhengzhou University (Engineering Science),2025,46(06):75-83.[doi:10.13705/j.issn.1671-6833.2025.06.005]
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考虑光伏预测误差和并网波动率的储能容量配置()
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《郑州大学学报(工学版)》[ISSN:1671-6833/CN:41-1339/T]

卷:
46
期数:
2025年06期
页码:
75-83
栏目:
出版日期:
2025-10-22

文章信息/Info

Title:
Consideration of Dual-layer Hybrid Energy Storage Capacity Configuration Accounting for Photovoltaic Forecasting Errors and Grid Fluctuation Rates
文章编号:
1671-6833(2025)06-0075-09
作者:
王明东1;  周政宇1;  杨宏杰2;  李忠文1
1.郑州大学 电气与信息工程学院,河南 郑州 450001;2.黄河勘测规划设计研究院有限公司,河南 郑州 450003
Author(s):
WANG Mingdong1;  ZHOU Zhengyu1;  YANG Hongjie2;  LI Zhongwen1
1.School of Electrical and Information Engineering, Zhengzhou University, Zhengzhou 450001, China; 2.Yellow River Engineering Consulting Co., Ltd., Zhengzhou University, Zhengzhou 450003, China
关键词:
光伏发电;  混合储能;  等年值成本;  补偿预测误差;  平抑并网波动;  双层规划模型
Keywords:
photovoltaic power generation;  hybrid energy storage;  levelized annual cost;  compensation for prediction error;  grid fluctuation smoothing;  bilevel planning model
分类号:
TM73TM615TM711
DOI:
10.13705/j.issn.1671-6833.2025.06.005
文献标志码:
A
摘要:
为满足并网要求并保障电力系统的稳健运行,提出了一种以降低光伏预测误差、平抑并网功率波动以及最小化等年值成本为目标的双层优化模型。上层规划旨在实现等年值成本最小化,其成本构成包括系统的投资、设备更换、维护费用以及碳排放效益成本。为提升系统经济性,提出了一种模糊遗传粒子群算法对模型进行优化分析;在下层规划中,模型以最小化预测误差和并网波动率为目标。基于超级电容器和蓄电池的不同特性,构建了充放电功率分配策略,从而提升系统的响应速度和延长蓄电池循环寿命。采用求解器进行控制,以实现对光伏预测误差的补偿和平滑光伏输出波动。最后,基于上述模型构建模型评估指标函数,并以某光伏电站为例进行案例分析,结果表明:所提算法在此模型中拥有更快的收敛速度和更寻优能力,同时优化后模型相较于优化前,预测误差的RMSE、MAPE分别降低99.95%和99.97%;最大并网波动率降低96.08%,验证了所提策略的有效性和实用性。
Abstract:
To meet grid connection requirements and ensure robust operation of the power system, a two-layer optimization model was proposed with objectives of reducing PV prediction errors, smoothing grid-connected power fluctuations, and minimizing annual equivalent costs. The upper-layer planning aimed to minimize annual equivalent costs, which included system investment, equipment replacement, maintenance costs, and carbon emission benefit costs. To improve system economic efficiency, a fuzzy genetic particle swarm algorithm was developed to optimize and analyze the model. In the lower-layer planning, the model aimed to minimize prediction errors and grid connection volatility. Based on distinct characteristics of supercapacitors and batteries, a charging-discharging power allocation strategy was constructed to enhance system response speed and extend battery cycle life. A solver was employed for control implementation to achieve PV prediction error compensation and PV output fluctuation smoothing. Finally, a model evaluation index function was established based on the proposed framework, with a PV power plant serving as a case study. Results demonstrated that the proposed algorithm exhibited faster convergence speed and superior optimization capability in this model. The RMSE and MAPE of prediction errors were reduced by 99.95% and 99.97% respectively, while the maximum grid connection fluctuation rate decreased by 96.08% after optimization. These findings verified the effectiveness and practicality of the proposed strategy.

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　Xu Tian,Chen Xiaoqiang.Research and simulation of parallel branch photovoltaic power generation system[J].Journal of Zhengzhou University (Engineering Science),2016,37(06):25.[doi:10.3969/j.issn.1671-6833.201505023]

更新日期/Last Update: 2025-10-21