Integration of storage and renewable energy into district heating systems: A review of modelling and optimization
The building and infrastructure sector is accountable for 46% of the total worldwide energy
consumption. Most traditional energy sources such as coal or petroleum are among the non …
consumption. Most traditional energy sources such as coal or petroleum are among the non …
Modeling energy demand—a systematic literature review
PA Verwiebe, S Seim, S Burges, L Schulz… - Energies, 2021 - mdpi.com
In this article, a systematic literature review of 419 articles on energy demand modeling,
published between 2015 and 2020, is presented. This provides researchers with an …
published between 2015 and 2020, is presented. This provides researchers with an …
Predicting hourly heating load in a district heating system based on a hybrid CNN-LSTM model
J Song, L Zhang, G Xue, YP Ma, S Gao, QL Jiang - Energy and Buildings, 2021 - Elsevier
Heat loads change dynamically with meteorological conditions and user demand, and the
related accurate prediction algorithms are conducive to the realization of optimized …
related accurate prediction algorithms are conducive to the realization of optimized …
An artificial neural network (ANN) expert system enhanced with the electromagnetism-based firefly algorithm (EFA) for predicting the energy consumption in buildings
In this study, a new hybrid model, namely the Electromagnetism-based Firefly Algorithm-
Artificial Neural Network (EFA-ANN), is proposed to forecast the energy consumption in …
Artificial Neural Network (EFA-ANN), is proposed to forecast the energy consumption in …
Multi-step ahead forecasting of heat load in district heating systems using machine learning algorithms
Predicting next-day heat load curves is essential to guarantee sufficient heat supply and
optimal operation of district heat systems (DHSs). Existing studies have mainly investigated …
optimal operation of district heat systems (DHSs). Existing studies have mainly investigated …
A firefly algorithm modified support vector machine for the credit risk assessment of supply chain finance
H Zhang, Y Shi, X Yang, R Zhou - Research in International Business and …, 2021 - Elsevier
Abstract Purpose Nowadays, Supply Chain Finance (SCF) has been develo** rapidly
since the emergence of credit risk. Therefore, this paper used SVM optimized by the firefly …
since the emergence of credit risk. Therefore, this paper used SVM optimized by the firefly …
Machine learning-based thermal response time ahead energy demand prediction for building heating systems
Y Guo, J Wang, H Chen, G Li, J Liu, C Xu, R Huang… - Applied energy, 2018 - Elsevier
Energy demand prediction of building heating is conducive to optimal control, fault detection
and diagnosis and building intelligentization. In this study, energy demand prediction …
and diagnosis and building intelligentization. In this study, energy demand prediction …
Comparative study of machine learning-based multi-objective prediction framework for multiple building energy loads
Buildings are one of the significant sources of energy consumption and greenhouse gas
emission in urban areas all over the world. Lighting control and building integrated …
emission in urban areas all over the world. Lighting control and building integrated …
Vibration fault diagnosis of wind turbines based on variational mode decomposition and energy entropy
X Chen, Y Yang, Z Cui, J Shen - Energy, 2019 - Elsevier
The bearing vibration of wind turbines is nonlinear and non-stationary. To effectively extract
bearing vibration signal features for fault diagnosis, a method of feature vector extraction …
bearing vibration signal features for fault diagnosis, a method of feature vector extraction …
Estimating the heating load of buildings for smart city planning using a novel artificial intelligence technique PSO-XGBoost
In this study, a novel technique to support smart city planning in estimating and controlling
the heating load (HL) of buildings, was proposed, namely PSO-XGBoost. Accordingly, the …
the heating load (HL) of buildings, was proposed, namely PSO-XGBoost. Accordingly, the …