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Data-driven optimization of multi-Source District heating systems based on load forecasting and coordinated control
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DOI：10.1016/j.applthermaleng.2026.129915.png)
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摘要
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• Delivers 0.989 fit and 2.0% error for short-term heat load prediction. • Cuts gas use by 5.41% and start–stop events by 25% via boiler scheduling. • Lifts average operating efficiency to 94.22% through coordinated dispatch. • Enables forecast-driven coordination of base-load and peak-shaving heat sources.
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IF:
6.9
论文数:
2.8W
被引数:
10.6W
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