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基于深度强化学习的可信变电站电力调度系统设计

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为有效应对快速变化的电网状态,提出了一种基于深度强化学习的变电站电力调度系统.该系统利用深度强化学习算法,通过与电网环境的实时交互,动态优化电力资源分配,实现智能调度决策.同时,结合区块链技术,利用智能合约自动化执行调度策略,并通过去中心化存储保障数据安全,增强了调度过程的可信性.结果表明,本系统能够增强电网的响应能力和灵活性,确保调度信息的真实性和完整性.
Design of Trustworthy Power Dispatch System for Substations Based on Deep Reinforcement Learning
To effectively respond to the rapidly changing conditions of power grids,this paper introduces a substation power dispatch system based on deep reinforcement learning.The system employs a deep reinforcement learning algorithm that dynamically optimizes the distribution of electrical resources through real-time interaction with the power grid environment,enabling intelligent dispatch decisions.Additionally,by integrating blockchain technology,smart contracts are used to automate the execution of dispatch strategies,and data security is ensured through decentralized storage,which enhances the trustworthiness of the dispatch process.The results show that the system can enhance the responsiveness and flexibility of the power grid and ensure the authenticity and integrity of dispatch information.

deep reinforcement learningsubstationpower dispatchblockchain

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山西华阳集团供电运维管理中心,山西 阳泉 045000

深度强化学习 变电站 电力调度 区块链

2024

自动化应用
重庆西南信息有限公司

自动化应用

影响因子:0.156
ISSN:1674-778X
年,卷(期):2024.65(13)