Lighting Network Control for Proactive Energy Demand Management
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing lighting systems in smart grids are reactive and event-driven, managing load only when receiving demand response signals, failing to proactively manage electricity use and match electricity generation and transmission effectively.
Innovation Solution
A method for proactively adjusting energy demand in lighting networks by collecting energy supply and load demand information, receiving electricity prices, and adjusting light operation strategies based on these factors, including dimming and off-grid power usage, to optimize energy use and respond to demand response signals.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If lighting systems use reactive event-driven load management, then the system complexity is reduced, but the ability to proactively manage energy demand and match electricity generation is worsened
Solution Approach 1:
The system performs preliminary actions by proactively adjusting lighting load before demand response events occur. The controller predicts future energy demand and supply conditions, and adjusts lighting operations in advance to optimize energy usage and reduce peak demand, rather than reacting only when demand response signals are received.
2Ease of operation
If lighting systems operate without proactive energy management, then the ease of operation is improved, but the energy consumption and grid resilience are worsened
Solution Approach 1:
The lighting system performs self-service by autonomously monitoring energy supply and demand conditions, predicting future states, and adjusting its own operation without requiring manual intervention. The controller automatically optimizes lighting load based on predicted energy conditions, reducing energy consumption while maintaining appropriate illumination levels.
3Device complexity
If lighting systems use simple load management strategies, then the device complexity is reduced, but the integration of renewable energy sources is worsened
Solution Approach 1:
The system implements dynamic load management by continuously adapting lighting operations based on real-time and predicted energy supply and demand conditions. The controller dynamically adjusts lighting load to match renewable energy generation patterns and grid conditions, enabling effective integration of renewable sources while maintaining system simplicity through automated decision-making.
Data Source
Figure 1
Figure 2
Figure 3~4
AI summary
Methods and apparatus related to operation of a plurality of lighting units of a lighting network according to energy demand and/or energy supply.