Distributed Load Control Switches for Demand-Reserve Prediction
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Solution Overview
Problem
Current demand-response systems in electrical utilities face challenges in accurately predicting available electricity demand-reserve, relying on rule-of-thumb methods or centralized data collection, which are inefficient and require extensive infrastructure and computational resources.
Innovation Solution
Implementing a distributed demand-reserve prediction system where load-control switches on high-energy-demand devices locally predict future load demand using historical data and transmit this data to a master control station, allowing for optimal load-shedding strategies and reducing the burden on centralized systems.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If centralized data collection from all energy-consuming devices is implemented, then accurate real-time demand reserve information is obtained, but extensive and complex infrastructure including significant transmission bandwidth is required
Solution Approach 1:
The patent divides the centralized data collection system into distributed prediction units at each load-control switch. Each unit independently predicts demand reserve for its controlled load using local historical data, eliminating the need for centralized real-time data collection from all devices. This segmentation reduces transmission bandwidth requirements and infrastructure complexity while maintaining prediction accuracy.
Solution Approach 2:
Each load-control switch performs self-service by locally predicting its own demand reserve characteristics using stored historical data. The devices autonomously generate prediction information without requiring centralized data gathering, processing, and transmission infrastructure, thereby reducing system complexity while providing accurate prediction data.
2Ease of operation
If rule-of-thumb guessing is used to determine load shedding proportion, then simple decision making is achieved, but accurate demand reserve prediction is not obtained
Solution Approach 1:
The system performs preliminary action by pre-calculating and storing historical load data and prediction algorithms at each load-control switch. This allows the system to quickly retrieve and use accurate prediction information during demand-response events, maintaining simple decision-making processes while eliminating the need for rule-of-thumb guessing through pre-prepared accurate data.
3Measurement precision
If weather information and historical data are considered in prediction algorithms, then demand reserve estimation is improved, but master station software is burdened with large databases and complex computational requirements
Solution Approach 1:
The patent extracts the complex computational requirements and large database storage needs from the master station and places them at the distributed load-control switches. Each switch locally stores and processes its own historical load data and weather information, performing predictions independently. This extraction eliminates the master station's computational burden while maintaining accurate demand reserve estimation using comprehensive local data.
Data Source
AI summary
A load control receiver (LCS) for controlling an electrical load. The LCS includes a power sensing arrangement that monitors power usage of the load; a processor that predicts future power usage based on prior power usage; a transceiver that receives load shedding commands; and a controllable switch that can interrupt power supplied to the attached loads, based on load shedding commands.