Voltage treatment device supporting remote automatic adjustment and treatment method

By integrating multi-parameter sensing modules, edge computing units, and dual-mode communication modules, combined with the Q-learning model, the problems of slow adjustment speed and insufficient remote adjustment capabilities of traditional voltage regulators are solved, and fast and reliable voltage regulation and communication switching are achieved to adapt to grid fluctuations and emergencies.

CN120638358APending Publication Date: 2025-09-12SHANDONG ELECTRICAL ENG & EQUIP GRP XINNENG TECH CO LTD
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Patent Information

Application Number
CN202510761602.7
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2025-06-09
Publication Date
2025-09-12

AI Technical Summary

Technical Problem

Traditional voltage regulators have slow adjustment speeds, no remote adjustment capabilities, and are unable to cope with sudden problems. Cloud-based remote adjustment systems have long communication links, high latency, and high signal loss rates, and their adjustment strategies have no learning capabilities, making it impossible to optimize strategies based on historical data.

Method used

By adopting a multi-parameter sensing module, an edge computing unit, a dual-mode communication module and an adjustment execution module, combined with the Q-learning model reinforcement learning strategy, the integration of edge computing and dual-mode communication is realized, dynamic adjustment instructions are generated, and highly reliable communication is carried out through the dual-mode communication module.

Benefits of technology

It achieves fast-response voltage regulation, reduces communication delay and packet loss rate, supports network disconnection autonomy, improves system robustness and decision reliability, and adapts to power grid fluctuations and emergencies.

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Abstract

The invention provides a voltage treatment device and method supporting remote automatic adjustment, and the device comprises a multi-parameter sensing module, an edge calculation unit, a dual-mode communication module, and an adjustment execution module. The method comprises the steps of multi-parameter synchronous acquisition, data preprocessing and noise suppression, dynamic weight fusion calculation, reinforcement learning decision generation and adjustment instruction execution and feedback. Dynamic fusion calculation is carried out on multiple parameters through the edge calculation unit, the algorithm reasoning time is shortened, a precise adjustment instruction is generated, the real-time response capability is remarkably improved, the response delay is reduced, edge calculation is supported, the edge decision reliability is improved, high-precision multi-parameter cooperative adjustment is achieved, and the communication reliability and the system robustness are enhanced. The communication packet loss rate is reduced, and seamless switching of power-on lines is realized.
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