综合智慧能源 ›› 2025, Vol. 47 ›› Issue (8): 68-76.doi: 10.3969/j.issn.2097-0706.2025.08.008

• 源网荷储优化调度 • 上一篇    下一篇

基于改进秃鹰搜索算法的风光火储综合能源系统优化调度策略研究

谭甲群(), 吕如轩(), 鞠洪晋(), 洪春雪*(), 肖海平(), 雷兢(), 韩振兴()   

  1. 华北电力大学 能源动力与机械工程学院,北京 102206
  • 收稿日期:2025-04-15 修回日期:2025-06-28 出版日期:2025-08-25
  • 通讯作者: *洪春雪(1999),女,硕士生,从事综合能源体系优化方面的研究,hongchunxue2022@163.com
  • 作者简介:谭甲群(2001),男,硕士生,从事综合能源系统厂级负荷分配方面的研究,tan200136@163.com
    吕如轩(2002),男,硕士生,从事综合能源系统净负荷优化方面的研究,ruxuanlv@foxmail.com
    鞠洪晋(2000),男,硕士生,从事火电系统安全性及安全生产管理方面的研究,juihongjin13@163.com
    肖海平(1978),男,副教授,硕士生导师,博士,从事锅炉、大数据等方面的研究,xiaohaiping@nuepu.edu.cn
    雷兢(1978),男,副教授,硕士生导师,博士,从事能源利用与转化过程正/反数学物理问题的解法、最优化方法与机器学习等方面的研究,leijing2002@126.com
    韩振兴(1973),男,副教授,硕士生导师,博士,从事蓄热技术、多相流检测等方面的研究,hzx@ncepu.edu.cn
  • 基金资助:
    国家自然科学基金项目(52276006)

Research on optimal scheduling strategy of wind-photovoltaic-thermal-storage integrated energy system based on IBES

TAN Jiaqun(), LYU Ruxuan(), JU Hongjin(), HONG Chunxue*(), XIAO Haiping(), LEI Jing(), HAN Zhenxing()   

  1. School of Energy Power and Mechanical Engineering, North China Electric Power University, Beijing 102206, China
  • Received:2025-04-15 Revised:2025-06-28 Published:2025-08-25
  • Supported by:
    National Natural Science Foundation of China(52276006)

摘要:

为准确高效地实现风光火储综合能源系统中新能源最经济消纳以及火电机组最优出力,同时探讨新能源消纳政策对燃煤电厂及系统整体的影响,基于模糊机会约束规划和改进秃鹰搜索(IBES)算法,构建了一种涉及火电机组厂级优化分配的风光火储体系分层优化调度模型。以某能源基地为例,模拟在不同风光消纳率约束下的调度情况,对比统一机组投运策略下的性能差异。结果显示:当风光弃能率放宽至10%时,火电机组净负荷平方差较5%约束时降低了24.04%,火电日总收益增加了2.48%,系统总收益增量为34.34万元,是风光弃能率为5%条件下的1.82倍,显著高于风光全额消纳模型;同时,火电机组深度调峰次数减少,调峰压力显著降低,运行安全性和经济性得到提升。所建模型能有效实现各发电主体出力的多目标优化分配,在新能源利用率不低于90%的政策指导下,适当放宽风光弃能率可显著提升能源基地的经济效益和系统运行灵活性,可为相关政策实施提供技术支撑和实证依据。

关键词: 风光火储综合能源系统, 新能源消纳, 模糊机会约束, 改进秃鹰搜索算法, 分层优化调度, 风光弃能率

Abstract:

The study aims to accurately and efficiently achieve the most cost-effective integration of renewable energy and the optimal output of thermal power units in the wind-photovoltaic-thermal-storage integrated energy system, while exploring the impact of renewable energy integration policies on coal-fired power plants and the overall system. Based on fuzzy chance-constrained programming and the improved bald eagle search (IBES) algorithm, a hierarchical optimal scheduling model for the wind-photovoltaic-thermal-storage system was constructed, incorporating plant-level optimal allocation of thermal power units. Taking a representative energy base as an example, the scheduling scenarios under constraints of different renewable energy curtailment rates were simulated, and performance differences under a unified unit operation strategy were compared. The results showed that when the wind and photovoltaic curtailment rate was extended to 10%, the net load square deviation of thermal power units decreased by 24.04% compared to the 5% constraint, the daily total revenue of thermal power increased by 2.48%, and the total system revenue increment reached 343 400 yuan-1.82 times that under the 5% renewable curtailment rate-significantly outperforming the full wind and photovoltaic integration model. Additionally, the number of deep peak-shaving operations of thermal power units was reduced, significantly alleviating operational stress and improving both operational safety and economic efficiency. The proposed model can effectively achieve multi-objective optimal allocation of output among power generation units. Under the policy guidance of maintaining renewable energy utilization rate of no less than 90%, appropriately relaxing the wind and photovoltaic curtailment rate can significantly improve the economic benefits of energy base and system operational flexibility, providing technical support and empirical evidence for the implementation of related policies.

Key words: wind-photovoltaic-thermal-storage integrated energy system, renewable energy consumption, fuzzy chance-constrained, improved bald eagle search algorithm, hierarchical optimal scheduling, wind and photovoltaic curtailment rate

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