Power Demand Estimation Using Environmental Pattern Matching
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Solution Overview
Problem
In areas with limited or no historical power demand records, accurately estimating power demand is challenging due to the reliance on dummy data, which is difficult to correct and understand, leading to inaccuracies in demand estimation.
Innovation Solution
A power demand estimating apparatus that classifies power demand patterns by environmental conditions, allowing for the selection of matching patterns and the calculation of demand models based on temperature data, facilitating easy correction and display of the estimation model.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If dummy demand record data is used for areas with limited historical records, then demand estimation can be performed, but the accuracy of demand estimation deteriorates due to differences from actual power demand
Solution Approach 1:
The patent introduces a correction coefficient as an intermediary element between the dummy demand record data and the actual demand estimation. This coefficient adjusts the dummy data to better reflect actual demand patterns, thereby improving accuracy while maintaining the ability to perform estimation in areas with limited historical records
Solution Approach 2:
The patent modifies the dummy demand record data by applying correction coefficients that change key parameters of the data. These coefficients adjust the relationship between environmental conditions and demand patterns, transforming the dummy data into more accurate predictions without requiring extensive historical records
2Measurement precision
If correction is applied to demand estimating model, then demand estimation accuracy is improved, but it is difficult to reflect the correction on dummy demand record data that is absolute value
Solution Approach 1:
The patent transforms the correction process by changing the parameter representation from absolute demand values to relative correction coefficients. This allows corrections to be easily applied and reflected in the dummy demand record data, as coefficients can be multiplied with the absolute values to produce corrected estimates
3Productivity
If dummy demand record data is used, then demand estimation can be performed in areas without historical records, but user understanding of the relationship between model and base data deteriorates
Solution Approach 1:
The patent uses correction coefficients as intermediary elements that bridge the dummy demand record data and the actual demand patterns. These coefficients serve as explanatory factors that help users understand the relationship between the model and base data, as they quantify the adjustments needed to match actual demand
Data Source
AI summary
A power demand estimating apparatus includes a demand data memory, a demand estimator, and a display. The demand data memory stores plural power demand patterns and power demand amount data. The demand estimator selects, from the demand data memory, the demand pattern matching the environmental condition on an estimation day, obtains the maximum value of an power demand amount and the minimum value thereof at an expected temperature on the estimation day, calculates, using those pieces of information, the power demand amount per a unit time on the estimation day, and creates a demand estimating model. The display displays, together with the power demand pattern selected by the demand estimator, the demand estimating model.