电器与能效管理技术 ›› 2026, Vol. 0 ›› Issue (5): 23-29.doi: 10.16628/j.cnki.2095-8188.2026.05.004

• 研究与分析 • 上一篇    下一篇

基于自适应鲸鱼算法和灰色聚类模型的综合能源系统调度策略设计

霍启敬, 杨柯柯, 蒋玉虎   

  1. 国网河北省电力有限公司 邯郸供电分公司, 河北 邯郸 056000
  • 收稿日期:2025-12-23 出版日期:2026-05-30 发布日期:2026-06-09
  • 作者简介:霍启敬(1994—),女,硕士,工程师,主要从事电力系统分析研究。|杨柯柯(1993—),女,硕士,工程师,研究方向为电力系统分析。|蒋玉虎(1993—),男,硕士,工程师,研究方向为电力系统分析。

Scheduling Strategy Design of Integrated Energy System Based on Adaptive Whale Algorithm and Grey Clustering Model

HUO Qijing, YANG Keke, JIANG Yuhu   

  1. Handan Power Supply Branch of State Grid Hebei Electric Power Co., Ltd., Handan 056000, China
  • Received:2025-12-23 Online:2026-05-30 Published:2026-06-09

摘要:

针对传统综合能源系统调度策略在复杂电网环境下存在调度准确率低、效率不足的问题,提出一种结合自适应鲸鱼算法与灰色聚类模型的智能化调度策略。通过动态调整惯性权重与收敛因子改进鲸鱼算法,提升其全局与局部搜索能力,并运用灰色聚类模型对设备状态进行评估分级,为调度提供精确信息支撑。试验结果表明,该策略调度准确率与效率均超过99%,在降低系统运行成本与能源损耗的同时,显著提升了系统性能与可靠性。该方法为电力系统智能优化调度提供了有效基础。

关键词: 综合能源系统, 自适应鲸鱼算法, 灰色聚类模型, 调度策略, 实验对比

Abstract:

To address the issues of low scheduling accuracy and low efficiency in traditional integrated energy system scheduling strategies under complex grid conditions,an intelligent dispatch strategy combining the adaptive whale algorithm with a grey clustering model is proposed.The whale algorithm is improved by dynamically adjusting inertia weight and convergence factors to enhance its global and local search capabilities.Additionally,a grey clustering model is employed to evaluate and classify equipment status,providing precise information support for dispatching.Experimental results show that the strategy achieves scheduling accuracy and efficiency of more than 99%,effectively reducing system operational costs and energy losses while significantly improving system performance and reliability.The research concludes that this method provides an effective foundation for intelligent optimization dispatching in power systems.

Key words: integrated energy system, adaptive whale algorithm, grey clustering model, scheduling strategy, experimental comparison

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