首页|期刊导航|电器与能效管理技术|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

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OA

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

中文摘要英文摘要

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.

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.

霍启敬;杨柯柯;蒋玉虎

国网河北省电力有限公司 邯郸供电分公司,河北邯郸 056000国网河北省电力有限公司 邯郸供电分公司,河北邯郸 056000国网河北省电力有限公司 邯郸供电分公司,河北邯郸 056000

信息技术与安全科学

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

integrated energy systemadaptive whale algorithmgrey clustering modelscheduling strategyexperimental comparison

《电器与能效管理技术》 2026 (5)

23-29,7

10.16628/j.cnki.2095-8188.2026.05.004

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