Network Energy Management Component Dynamic Scheduling
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Solution Overview
Problem
Current energy management systems lack an effective method to optimize energy usage in network systems, leading to inefficiencies in energy production, distribution, and consumption, particularly in recognizing and responding to price fluctuations and scheduling operations based on cost conditions.
Innovation Solution
A network system that includes an energy management component capable of recognizing low-price and high-price periods, adjusting scheduled operation times, and changing operation modes to minimize energy costs by operating during low-price periods and conserving energy during high-price periods.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of energy
If energy consumption devices are operated according to fixed schedules, then operational reliability is maintained, but energy costs increase due to inability to respond to price fluctuations
Solution Approach 1:
The patent implements dynamic scheduling by allowing energy consumption devices to adjust their operation times based on real-time energy price signals. The system transitions from fixed schedules to flexible, adaptive schedules that respond to price fluctuations, enabling devices to operate during low-price periods and defer operation during high-price periods while maintaining operational reliability through predictive algorithms.
Solution Approach 2:
The system incorporates feedback mechanisms by continuously monitoring energy price signals and using this information to adjust device schedules. The energy management unit receives price information, processes it through algorithms, and generates adjusted schedules that are fed back to the devices, creating a closed-loop control system that optimizes energy costs based on real-time conditions.
2Productivity
If energy storage systems are activated to sell energy during favorable cost conditions, then revenue generation improves, but system complexity increases
Solution Approach 1:
The patent applies multi-functionality by designing the energy management system to handle multiple functions within a unified framework. The same scheduling algorithms and control mechanisms used for managing energy consumption devices are also applied to energy storage systems, allowing the system to both purchase energy during low-price periods and sell energy during high-price periods through a single integrated management platform.
Solution Approach 2:
The system implements self-service by enabling energy storage units to automatically make decisions about when to charge and discharge based on price signals received from the utility company. The algorithms autonomously determine favorable cost conditions and execute trading decisions without requiring manual intervention, allowing the system to generate revenue while maintaining operational simplicity.
3Loss of energy
If devices are activated during cheapest energy usage periods, then energy costs are reduced, but operational flexibility is constrained
Solution Approach 1:
The patent applies preliminary action by using predictive algorithms to forecast future energy prices and pre-schedule device operations during anticipated low-price periods. The system looks ahead in time to identify optimal operation windows and prepares schedules in advance, allowing devices to be activated at the cheapest moments while maintaining operational flexibility through predictive rather than reactive scheduling.
Data Source
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AI summary
Provided is a method of controlling a component for a network system. The method of controlling the component for the network system includes recognizing low-price period or high-price period information, recognizing a scheduled operation time including a scheduled operation start time of the component, determining whether a change condition of the scheduled operation time is satisfied, and changing the scheduled operation time when the change condition is satisfied and operating the component at the changed scheduled operation time.