Air-conditioning management device, air-conditioning management method, and program
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Solution Overview
Problem
Existing air conditioner control schedules struggle to effectively incorporate weather forecasts to achieve energy reduction targets, lacking a systematic approach to create a proper and achievable schedule.
Innovation Solution
An air-conditioning management device that sets energy targets, creates a standard operation schedule, acquires and updates schedules using multiple weather forecast data for different forecast periods, ensuring the schedule reflects weather conditions and adjusts operation conditions to meet energy usage targets.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Use of energy by moving object
If a standard operation schedule is created to achieve energy targets, then energy usage control is improved, but the schedule cannot adapt to changing weather conditions
Solution Approach 1:
The patent implements a dynamic schedule update mechanism that transforms the static standard operation schedule into a dynamic one that automatically adapts to changing weather conditions. The system acquires weather forecast data at different time points and updates the operation schedule accordingly, allowing the air conditioner to adjust its operation while still working toward the energy target.
Solution Approach 2:
The system establishes a feedback loop where weather forecast data is continuously acquired and used to update the operation schedule. This feedback mechanism allows the system to monitor weather changes and adjust the air conditioner's operation in response, ensuring both energy target achievement and adaptability to actual weather conditions.
2Measurement precision
If weather forecast data is incorporated into schedule creation, then schedule accuracy is improved, but the complexity of schedule management increases
Solution Approach 1:
The patent segments the weather forecast data into multiple time points (e.g., short-term, medium-term, long-term forecasts) and processes each segment separately to create updated schedules. This segmentation approach makes the complex task of incorporating weather data more manageable by breaking it down into discrete, handleable components.
Solution Approach 2:
The system performs preliminary actions by acquiring and analyzing weather forecast data before creating the updated operation schedule. By preparing the weather data in advance and using it to proactively adjust the schedule, the system improves accuracy while managing complexity through structured preliminary processing.
3Reliability
If multiple weather forecast data for different forecast periods are used, then the ability to create proper schedules is improved, but the data processing complexity increases
Solution Approach 1:
The patent employs dynamic schedule updates by processing multiple weather forecast data sets for different time periods (short-term, medium-term, long-term). Each forecast period generates an updated schedule that builds upon previous updates, creating a reliable multi-layered scheduling approach that adapts to varying forecast horizons.
Solution Approach 2:
The system processes weather forecast data partially by focusing on the most relevant forecast periods and updating the schedule incrementally rather than reprocessing all data simultaneously. This partial action approach maintains reliability by considering multiple forecast periods while reducing overall processing complexity through selective, incremental updates.
Data Source
AI summary
A standard schedule creator creates a standard schedule that makes it possible to achieve a target presented by target data. A seasonal schedule updater, monthly schedule updater, weekly schedule updater, and current day schedule updater update the created standard schedule using the corresponding weather forecast data to create an operation schedule of an air conditioner in which the weather forecast is properly reflected.