AI-based smart energy gateway intelligent scheduling and optimization control system

By introducing an AI decision-making system into the smart energy gateway, using a time-sequential convolutional network and a deep reinforcement learning network for load prediction and optimal power allocation, the problems of low load prediction accuracy and under-optimization of equipment collaborative decision-making in the existing technology are solved, and high-precision load prediction and intelligent collaborative decision-making capabilities are achieved.

CN119717526AActive Publication Date: 2025-03-28GUANGZHOU HUITONG GUOXIN TECH CO LTD
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Patent Information

Application Number
CN202411862167.9
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2024-12-17
Publication Date
2025-03-28
Estimated Expiration
2044-12-17

AI Technical Summary

Technical Problem

The existing smart energy gateways have shortcomings in load prediction accuracy and equipment collaborative decision-making, and cannot effectively capture the long-term dependence characteristics of load data, and the scheduling method is limited, so they fail to make full use of the dynamic matching relationship between power generation equipment and energy storage devices.

Method used

It adopts a smart energy gateway system based on AI, including energy access films, data processing films, AI decision-making films and control execution films. The energy access chip collects data from multiple protocol devices and converts it into standard formats. The data processing chip performs differential processing and abnormality verification. The AI ​​decision chip uses the timing convolution network and the deep reinforcement learning network for load prediction and optimal power allocation, and controls the execution chip execution decision results.

Benefits of technology

It significantly improves the accuracy of load prediction, can more accurately identify the seasonal fluctuations and mutation characteristics of load, realizes accurate modeling of system status and optimal power distribution, and overcomes the shortcomings of traditional methods that poor adaptability to environmental changes.

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Abstract

The invention discloses a smart energy gateway intelligent scheduling and optimization control system based on AI. The system comprises an energy access chip, a data processing chip, an AI decision chip and a control execution chip. The energy access chip collects and uniformly converts equipment operation data of different protocols, and the data processing chip carries out differential processing and abnormity detection; the AI decision-making piece adopts a time sequence convolutional network TCN to carry out load prediction and uses a deep reinforcement learning network DQN to calculate an optimal power distribution scheme; and the control execution sheet is responsible for executing the control instruction and monitoring the state. The technical problems of a traditional energy gateway in the aspects of multi-protocol equipment access, data processing, intelligent decision optimization and the like are solved, the load change is predicted through adaptive learning, power distribution is optimized based on the dynamic coupling relation between the equipment, and the energy utilization efficiency and the system operation stability are improved.
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