Edge-Cloud Factory Power Coordination for Real-Time Demand Response
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Traditional factory power management and control methods face challenges such as insufficient timeliness, inability to jointly manage power supply and consumption, and security vulnerabilities due to centralized approaches, leading to increased costs and potential system failures.
Innovation Solution
A factory power management and control system based on edge-cloud coordination, which integrates cloud and edge computing to locally process data, prioritize tasks, and coordinate power supply and consumption, using edge nodes to compute electricity demands and generate real-time schemes, while storing data in the cloud for future reference.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If centralized management and control methods are used for factory power, then power management and control can be unified, but timeliness is insufficient due to huge power data transmission delays
Solution Approach 1:
The patent divides the centralized cloud computing architecture into distributed edge computing nodes deployed at different factory locations. Each edge node independently processes local power data and generates control instructions, eliminating the need to transmit all data to a central cloud server. This segmentation resolves the contradiction by maintaining unified power management through coordinated edge nodes while drastically reducing transmission delays through localized processing.
2Device complexity
If centralized management and control methods are used for factory power, then scheduling can be simplified, but power supply-power consumption cannot be jointly managed and controlled
Solution Approach 1:
The edge computing nodes are designed with multi-functional capabilities to handle both power supply management and power consumption management simultaneously. Each edge node can process generation data, storage data, and consumption data, and coordinate them locally. This universal design enables joint power supply-consumption management without significantly increasing overall system complexity, as the same edge infrastructure serves multiple functions.
3Ease of operation
If centralized computing center is used for factory power management, then coordination can be centralized, but security is insufficient due to single point of failure
Solution Approach 1:
The patent segments the centralized computing center into multiple distributed edge computing nodes. Each node operates independently to manage local power coordination, eliminating the single point of failure vulnerability. While coordination remains centralized in terms of overall strategy, the execution is distributed across multiple secure nodes, improving system security and reliability while maintaining ease of operation through automated local decision-making.
4Loss of information
If all power data is moved to cloud for centralized computation, then comprehensive analysis can be achieved, but power consumption costs increase
Solution Approach 1:
The patent extracts the core computational functions from the centralized cloud and places them at distributed edge nodes. Only essential coordination data and aggregated results need to be transmitted to the cloud, while local power data processing and analysis are performed at the edge. This extraction reduces the volume of data requiring cloud transmission and processing, thereby reducing power consumption costs while maintaining comprehensive analysis capability through distributed computation.
Data Source
AI summary
The present invention provides a factory power management and control method based on edge-cloud coordination, including: 1) forming an industrial field network by a field node, a routing node and a device executing production tasks; 2) parsing production task information data and sending; 3) issuing an STN model in production field to an edge node; 4) sending to the edge node; 5) computing, required to complete the production tasks; 6) computing values of comprehensive ranks; 7) executing, by the edge node, the higher rank, and executing, by the cloud power management center, the lower rank; 8) executing, by the edge node, a demand response algorithm; 9) executing, by the production device, the production tasks based on computing results; and executing, by a power generation station in factory, a power storage station in factory and a power supply station outside factory, corresponding schemes based on the results.