Energy collaborative power transmission method and system based on source network load storage

By introducing innovative means such as intelligent prediction and scheduling modules, energy storage units, and multi-source power supply modes into energy collaborative power transmission technology, the problem of integration between conventional power supply and new energy is solved, and the efficient operation and low-carbon goals of energy systems are achieved.

CN119695883AActive Publication Date: 2025-03-25STATE GRID QINGHAI ELECTRIC POWER COMPANY +1
2 Cites 1 Cited by

Patent Information

Application Number
CN202411854291.0
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2024-12-17
Publication Date
2025-03-25
Estimated Expiration
2044-12-17

AI Technical Summary

Technical Problem

Existing energy collaborative power transmission technology is difficult to achieve seamless integration between conventional power supplies and new energy sources, resulting in weak power supply stability in specific areas and low energy utilization efficiency.

Method used

The energy collaborative transmission method based on source network load storage is adopted, and energy production, storage and transmission are optimized through intelligent prediction and scheduling modules, high-efficiency energy storage units, multi-source hybrid power supply modes, intelligent monitoring and management platforms, virtual power plant technology, blockchain technology and adaptive control and protection mechanisms.

Benefits of technology

It achieves efficient matching of power production and consumption, optimizes the operating efficiency of the energy system, improves the utilization rate of renewable energy, enhances the flexibility and stability of the power system, and reduces energy waste and carbon emissions.

✦ Generated by Eureka AI based on patent content.
Patent Text Reader

Abstract

The invention discloses an energy collaborative power transmission method and system based on source-grid load storage, and belongs to the technical field of source-grid load storage, and the method comprises the following steps: S1, predicting the generating capacity of a power supply side through employing an intelligent prediction and scheduling module in combination with a machine learning and deep learning algorithm; s2, deploying an efficient energy storage unit; s3, designing a multi-source hybrid power supply mode; s4, constructing an intelligent monitoring management platform; s5, the distributed energy resources are integrated, home photovoltaic and community wind power stations are connected to a main network through the micro-grid technology, and interaction between a large power grid and the distributed energy resources is promoted; and S6, applying a virtual power plant technology. According to the method, machine learning and deep learning algorithms are deployed, weather forecast and seasonal change factors are combined, the power supply side generating capacity is accurately predicted, dynamic scheduling and accurate prediction are realized according to a load side demand prediction result, so that power production can be more closely matched with actual demands, and excessive production and energy waste are avoided.
Need to check novelty before this filing date? Find Prior Art