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Decomposition of air conditioning electricity consumption based on effective duration
Chao Xun1, Huan Zheng2, Zhaoyu Han3
1State Grid Fujian Electric Power Co., Ltd., Fuzhou, China.
This study introduces a novel method for decomposing air conditioning electricity consumption using apparent temperature and effective duration. The new approach and evaluation metrics improve accuracy in assessing electricity usage patterns and grid stability.
Area of Science:
- Energy Systems Engineering
- Building Energy Analysis
- Power Grid Management
Background:
- Growing air conditioning electricity consumption necessitates accurate usage breakdown for grid stability.
- Existing literature inadequately addresses the impact of apparent temperature on AC energy use.
- A lack of effective indices hinders the evaluation of AC electricity consumption decomposition accuracy.
Purpose of the Study:
- To develop a method for decomposing air conditioning electricity consumption based on effective duration.
- To integrate apparent temperature modeling into AC consumption decomposition.
- To propose novel evaluation metrics for assessing the efficacy of consumption breakdown.
Main Methods:
- Utilized effective duration as the basis for decomposing air conditioning electricity consumption.
- Employed an apparent temperature model as a constraint to identify effective air conditioning operating time.
- Constructed a constrained convex optimization problem to estimate air conditioning power usage.
Main Results:
- The proposed decomposition methodology demonstrates closer alignment with actual electricity consumption data.
- The novel evaluation index, including penalties for negative decomposed consumption, enhances assessment accuracy.
- Empirical results from Fujian Province validate the effectiveness of the new approach.
Conclusions:
- The developed method provides a more accurate decomposition of air conditioning electricity consumption.
- The proposed evaluation metrics effectively gauge the quality of AC electricity consumption data.
- This work contributes to improved electricity usage pattern assessment and power grid management strategies.
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