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Comparison of time-frequency-analysis techniques applied in building energy data noise cancellation for building load forecasting: A real-building case study

Journal Article · · Energy and Buildings
 [1];  [2];  [3]
  1. National Renewable Energy Lab. (NREL), Golden, CO (United States); Drexel Univ., Philadelphia, PA (United States)
  2. National Renewable Energy Lab. (NREL), Golden, CO (United States); Univ. of Nebraska, Lincoln, NE (United States)
  3. Drexel Univ., Philadelphia, PA (United States)
+ Show Author Affiliations
Time-frequency analysis that disaggregates a signal in both time and frequency domain is an important supporting technique for building energy analysis such as noise cancellation in data-driven building load forecasting. There is a gap in the literature related to comparing various time–frequency-analysis techniques, especially discrete wavelet transform (DWT) and empirical mode decomposition (EMD), to guide the selection and tuning of time–frequency-analysis techniques in data-driven building load forecasting. This article provides a framework to conduct a comprehensive comparison among thirteen DWT/EMD techniques with various parameters in a load forecasting modeling task. A real campus building is used as a case study for illustration. The DWT and EMD techniques are also compared under various data-driven modeling algorithms for building load forecasting. The results in the case study show that the load forecasting models trained with noise-cancelled energy data have increased their accuracy to 9.6% on average tested under unseen data. This study also shows that the effectiveness of DWT/EMD techniques depends on the data-driven algorithms used for load forecasting modeling and the training data. Hence, DWT/EMD-based noise cancellation needs customized selection and tuning to optimize their performance for data-driven building load forecasting modeling.
Research Organization:
National Renewable Energy Laboratory (NREL), Golden, CO (United States)
Sponsoring Organization:
USDOE Office of Energy Efficiency and Renewable Energy (EERE)
Grant/Contract Number:
AC36-08GO28308
OSTI ID:
1769874
Alternate ID(s):
OSTI ID: 1899791
Report Number(s):
NREL/JA--5500-79372; MainId:33598; UUID:07387a92-2f0e-49c5-8b1c-204ccb685110; MainAdminID:19861
Journal Information:
Energy and Buildings, Journal Name: Energy and Buildings Vol. 231; ISSN 0378-7788
Publisher:
ElsevierCopyright Statement
Country of Publication:
United States
Language:
English

References (35)

Small-Scale Building Load Forecast based on Hybrid Forecast Engine journal October 2017
A hybrid forecasting model with parameter optimization for short-term load forecasting of micro-grids journal September 2014
A hybrid application algorithm based on the support vector machine and artificial intelligence: An example of electric load forecasting journal May 2015
Robust optimization based optimal chiller loading under cooling demand uncertainty journal February 2019
Accurately predicting building energy performance using evolutionary multivariate adaptive regression splines journal September 2014
Conceptual complexity and the bias/variance tradeoff journal January 2011
Use of model predictive control and weather forecasts for energy efficient building climate control journal February 2012
Short-term electricity load forecasting of buildings in microgrids journal July 2015
Predicting future monthly residential energy consumption using building characteristics and climate data: A statistical learning approach journal September 2016
Trees vs Neurons: Comparison between random forest and ANN for high-resolution prediction of building energy consumption journal July 2017
A systematic feature selection procedure for short-term data-driven building energy forecasting model development journal January 2019
Forecasting of consumers heat load in district heating systems using the support vector machine with a discrete wavelet transform algorithm journal July 2015
Electricity load forecasting by an improved forecast engine for building level consumers journal November 2017
Deep belief network based ensemble approach for cooling load forecasting of air-conditioning system journal April 2018
Two stage forecast engine with feature selection technique and improved meta-heuristic algorithm for electricity load forecasting journal October 2018
Improving forecasting accuracy of daily enterprise electricity consumption using a random forest based on ensemble empirical mode decomposition journal December 2018
Techniques of applying wavelet transform into combined model for short-term load forecasting journal April 2006
A wavelet Elman neural network for short-term electrical load prediction under the influence of temperature journal December 2012
Hybrid Improved Differential Evolution and Wavelet Neural Network with load forecasting problem of air conditioning journal October 2014
Short term load forecasting using wavelet transform combined with Holt–Winters and weighted nearest neighbor models journal January 2015
Different states of multi-block based forecast engine for price and load prediction journal January 2019
Electric load forecasting by the SVR model with differential empirical mode decomposition and auto regression journal January 2016
Advanced control systems engineering for energy and comfort management in a building environment—A review journal August 2009
A review on applications of ANN and SVM for building electrical energy consumption forecasting journal May 2014
Review of building energy modeling for control and operation journal September 2014
Short-term electricity demand forecasting using double seasonal exponential smoothing journal August 2003
Daubechies wavelets as a basis set for density functional pseudopotential calculations journal July 2008
A hybrid method based on wavelet, ANN and ARIMA model for short-term load forecasting journal June 2013
Power-Spectrum-Based Wavelet Transform for Nonintrusive Demand Monitoring and Load Identification journal May 2014
An Adaptive Wavelet Neural Network-Based Energy Price Forecasting in Electricity Markets journal August 2008
Toward Non-Intrusive Load Monitoring via Multi-Label Classification journal January 2017
Modeling Hourly Energy Use in Commercial Buildings With Fourier Series Functional Forms journal August 1998
Short-Term Load Forecasting Using EMD-LSTM Neural Networks with a Xgboost Algorithm for Feature Importance Evaluation journal August 2017
Forecasting Monthly Electric Energy Consumption Using Feature Extraction journal September 2011
Design and Implementation of Cloud Analytics-Assisted Smart Power Meters Considering Advanced Artificial Intelligence as Edge Analytics in Demand-Side Management for Smart Homes journal May 2019

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Related Subjects

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATION
building load forecasting
data-driven modeling
discrete wavelet transform
empirical mode decomposition
noise cancellation
time-frequency analysis