Papers
Topics
Authors
Recent
Gemini 2.5 Flash
Gemini 2.5 Flash
169 tokens/sec
GPT-4o
7 tokens/sec
Gemini 2.5 Pro Pro
45 tokens/sec
o3 Pro
4 tokens/sec
GPT-4.1 Pro
38 tokens/sec
DeepSeek R1 via Azure Pro
28 tokens/sec
2000 character limit reached

A hybrid-model approach for reducing the performance gap in building energy forecasting (2206.00460v1)

Published 30 May 2022 in cs.CE

Abstract: The performance gap between predicted and actual energy consumption in the building domain remains an unsolved problem in practice. The gap exists differently in both current mainstream methods: the first-principles model and the ML model. Inspired by the concept of time-series decomposition to identify different uncertainties, we proposed a hybrid-model approach by combining both methods to minimize this gap: 1. Use the first-principles method as an encoding tool to convert the building static features and predictable patterns in time-series simulation results; 2. The ML method combines the results as extra inputs with historical records simultaneously, trains the model to capture the implicit performance difference, and aligns to calibrate the output. To extend this approach in practice, a new concept in the modeling process: Level-of-Information (LOI), is introduced to leverage the balance between the investment of simulation modeling detail and the accuracy boost. The approach is tested over a three-year period, with hourly measured energy load from an operating commercial building in Shanghai. The result presents a dominant accuracy enhancement: The hybrid-model shows higher accuracy in prediction with better interpretability; More important, it releases the practitioners from modeling workload and computational resources in refining simulation. In summary, the approach provides a nexus for integrating domain knowledge via building simulation with data-driven methods. This mindset applies to solving general engineering problems and leads to improved prediction accuracy. The result and source data are available at https://github.com/ResearchGroup-G/PerformanceGap-Hybrid-Approach.

Citations (14)

Summary

We haven't generated a summary for this paper yet.