Energy Prediction System with Environmental Correction
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Solution Overview
Problem
Existing energy prediction systems do not effectively determine whether current energy consumption status will meet a target value by the end of a predetermined period, lacking the ability to assess the sufficiency of power saving efforts.
Innovation Solution
An energy prediction system comprising an estimated information acquisition unit, consumption information acquisition unit, first prediction unit, environmental information acquisition unit, and output unit, which predicts energy consumption based on correlations between environmental states and consumption data, correcting predictions with real-time environmental information to provide both a target and actual consumption forecasts.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If the system only displays past energy consumption data and target values, then the user can check historical performance, but the user cannot determine whether current consumption status will meet the target by the end of the period
Solution Approach 1:
The system performs preliminary prediction of future energy consumption based on current consumption patterns and environmental factors before the target period ends. This allows users to know in advance whether they will meet their energy targets, enabling proactive adjustments to consumption behavior.
Solution Approach 2:
The system provides continuous feedback to users by comparing predicted future consumption with target values and displaying real-time consumption status. This feedback loop enables users to understand their current trajectory and make informed decisions about energy usage adjustments.
2Measurement precision
If the system uses multiple prediction methods with environmental data correction, then the prediction accuracy improves, but the system complexity increases
Solution Approach 1:
The prediction system is divided into separate functional modules: a base prediction unit that generates initial predictions from consumption patterns, and a correction unit that adjusts predictions based on environmental factors. This segmentation allows each module to be optimized independently while working together to improve overall accuracy.
Solution Approach 2:
The system dynamically adjusts prediction parameters based on environmental conditions such as temperature, humidity, and seasonal variations. By changing the prediction model's parameters according to these environmental factors, the system maintains high accuracy without requiring an entirely complex redesign of the prediction architecture.
3Productivity
If the system provides detailed real-time prediction data, then users can make timely adjustments to meet energy targets, but the amount of information processing and display complexity increases
Solution Approach 1:
The system extracts and highlights only the most critical information needed for energy management, such as predicted total consumption, comparison with target values, and key environmental factors affecting consumption. By extracting only essential data rather than presenting all available real-time data, the system maintains user-friendly complexity while enabling effective energy-saving decisions.
Data Source
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AI summary
Provided are an energy prediction system, an energy prediction method, a program, a storage medium, and a management system, all of which are configured or designed to allow the user to determine whether the current energy consumption status will enable reducing energy consumption to a target value or less at the end of a predetermined period. An energy prediction system (1) includes an estimated information acquisition unit (102), a consumption information acquisition unit (103), a first prediction unit (105), a second prediction unit (106), and an output unit (107). The first prediction unit (105) predicts, based on a correlation between estimated information acquired by the estimated information acquisition unit (102) and energy consumption, a quantity of energy defining a target value of a quantity of energy that needs to be consumed over a first predetermined period, as a first predicted value. The second prediction unit (106) predicts, in accordance with energy consumption information about respective quantities of energy consumed in a predetermined number of second predetermined periods acquired by the consumption information acquisition unit (103), a quantity of energy that is going to be consumed over the first predetermined period, as a second predicted value. The output unit (107) outputs prediction result information about the first predicted value and the second predicted value.