解决闪电和市场不确定性的自我调度:智能电网的模糊马尔科夫方法

Iman Sanjari Benistan¹, Mahdi Jafari Shahbazzadeh², Mahdiyeh Eslami³

¹Department of Electrical Engineering, Ke.C, Islamic Azad University, Kerman, Iran.

Scientific reports

|March 11, 2026

概括

这项研究集成了模糊逻辑和马尔科夫模型来管理智能电网的不确定性,这些不确定性来自市场波动和闪电. 费齐-马尔科夫框架增强了决策和预测,以提高电网稳定性.

科学领域:

* 智能电网技术的使用
* 能源系统中的人工智能
* 风险管理和预测分析

背景情况:

*智能电网面临着来自市场波动和闪电等环境事件的复杂不确定性.
*现有的模型难以处理概率性市场数据和不准确的环境影响评估.
* 需要采用统一的方法来全面管理智能电网自动调度中的不确定性.

研究的目的:

* 开发一个可靠的fuzzy-markov框架,以提高智能电网的可预测性和稳定性.
* 整合模糊逻辑和马尔科夫模型来管理自我调度中的混合不确定性.
* 在不可预见的市场和环境条件下改进决策过程.

主要方法:

*将模糊逻辑集成到模糊状态中,用于对市场数据 (价格,收入,销售) 的定性评估.
* 应用马尔科夫模型来分析这些模糊状态之间的过渡概率.
*为混合不确定性管理制定统一的Fuzzy-Markov框架.

主要成果:

*成功地将财务指标分类为定性模糊状态.
* 构建和分析马尔科夫过渡矩阵,提供对状态过渡的见解.
* 在预测未来状况方面取得了56.13%的准确性,证明了战略规划的基础.

结论:

* 迷糊马尔科夫方法有效地对复杂的数据进行分类,并分析状态过渡以进行主动决策.
* 该框架通过滚动统计数据为风险管理提供了关键的见解.
*这种新的集成提供了一种强大的方法来管理智能电网中的各种不确定性.

关键词:

模糊-马尔科夫方法的方法.市场的不确定性市场的不确定性自我安排时间表智能电网是一个智能电网.

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