Multi-Facility Power Control Using Equipment-Level Usage Prediction
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Solution Overview
Problem
Existing power control systems struggle to accurately predict and manage power usage across multiple facilities, leading to inefficiencies and potential overloads.
Innovation Solution
A power control system that includes an acquisition unit to gather power usage data from equipment devices, a prediction unit to forecast power usage based on historical data, and a control unit to manage total power usage across facilities, ensuring it meets predetermined conditions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If power control is performed based on simple aggregation of equipment data, then system complexity is reduced, but prediction accuracy of facility power usage deteriorates
Solution Approach 1:
The system segments the power usage prediction into two levels: equipment level and facility level. The acquisition unit collects data from individual equipment devices, the prediction unit forecasts equipment power usage, and the facility-level power usage is calculated by aggregating equipment predictions while incorporating facility-specific characteristics. This segmentation allows accurate predictions without requiring a single complex monolithic model.
2Measurement precision
If detailed equipment-level data is collected from all devices, then prediction accuracy improves, but data acquisition complexity and system resource requirements increase
Solution Approach 1:
The acquisition unit is designed with multi-functionality to collect diverse data types from multiple equipment devices through a unified interface. It can acquire operation states, environmental data, and power consumption information from various device types (air conditioners, refrigerators, washing machines, etc.) using the same data collection mechanism, reducing acquisition complexity while maintaining comprehensive data gathering.
3Manufacturing precision
If power usage is predicted for each equipment device individually, then allocation accuracy improves, but computational load and processing time increase
Solution Approach 1:
The prediction unit performs preliminary power usage prediction for each equipment device based on its operation state and historical data. These preliminary predictions are then aggregated to determine the total facility power usage and allocate power quotas to individual equipment. This preliminary action at the equipment level enables accurate allocation without requiring complex real-time calculations for the entire facility simultaneously.
Data Source
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AI summary
[Object] To control the power usage by plural facilities such that information related to the power usage is acquired from equipment devices and the power usage per equipment device is accurately predicted based on the acquired information. [Solution] A power control system for performing power control such that a total power usage of plural facilities satisfies a predetermined power usage condition, the power control system including an actual result information acquisition unit 360 that acquires information on power usages by equipment devices installed in the facilities; a first prediction unit 320 that predicts power usages of the facilities in which the equipment devices are installed, based on the information on the power usages by the equipment devices; and a control information generation unit 340 that controls the total power usage of the plural facilities, based on the power usages of the facilities predicted by the first prediction unit 320.