Review and prospect of data-driven techniques for load forecasting in integrated energy systems
With synergies among multiple energy sectors, integrated energy systems (IESs) have been
recognized lately as an effective approach to accommodate large-scale renewables and …
recognized lately as an effective approach to accommodate large-scale renewables and …
A review of machine learning in building load prediction
The surge of machine learning and increasing data accessibility in buildings provide great
opportunities for applying machine learning to building energy system modeling and …
opportunities for applying machine learning to building energy system modeling and …
Thermal energy storage in district heating and cooling systems: A review
E Guelpa, V Verda - Applied Energy, 2019 - Elsevier
Thermal storage facilities ensure a heat reservoir for optimally tackling dynamic
characteristics of district heating systems: heat and electricity demand evolution, changes of …
characteristics of district heating systems: heat and electricity demand evolution, changes of …
A multi-energy load forecasting method based on parallel architecture CNN-GRU and transfer learning for data deficient integrated energy systems
C Li, G Li, K Wang, B Han - Energy, 2022 - Elsevier
In the integrated energy system with small samples, insufficient data limits the accuracy of
energy load forecasting and thereafter affects the system's economic operation and optimal …
energy load forecasting and thereafter affects the system's economic operation and optimal …
[HTML][HTML] Modeling and optimization of multi-energy systems in mixed-use districts: A review of existing methods and approaches
C Klemm, P Vennemann - Renewable and Sustainable Energy Reviews, 2021 - Elsevier
About 75% of the world's energy consumption takes place in cities. Although their large
energy consumption attracts a large number of research projects, only a small fraction of …
energy consumption attracts a large number of research projects, only a small fraction of …
Forecasting energy use in buildings using artificial neural networks: A review
J Runge, R Zmeureanu - Energies, 2019 - mdpi.com
During the past century, energy consumption and associated greenhouse gas emissions
have increased drastically due to a wide variety of factors including both technological and …
have increased drastically due to a wide variety of factors including both technological and …
A comprehensive overview on the data driven and large scale based approaches for forecasting of building energy demand: A review
Energy consumption models play an integral part in energy management and conservation,
as it pertains to buildings. It can assist in evaluating building energy efficiency, in carrying …
as it pertains to buildings. It can assist in evaluating building energy efficiency, in carrying …
Review of district heating and cooling systems for a sustainable future
A Lake, B Rezaie, S Beyerlein - Renewable and Sustainable Energy …, 2017 - Elsevier
The present study explores the implementation of district heating and cooling systems
across a broad set of case studies reported in the literature. Topics addressed include their …
across a broad set of case studies reported in the literature. Topics addressed include their …
Evaluation of a multiple linear regression model and SARIMA model in forecasting heat demand for district heating system
T Fang, R Lahdelma - Applied energy, 2016 - Elsevier
Forecasting heat demand is necessary for production and operation planning of district
heating (DH) systems. In this study we first propose a simple regression model where the …
heating (DH) systems. In this study we first propose a simple regression model where the …
Low-carbon robust economic dispatch of park-level integrated energy system considering price-based demand response and vehicle-to-grid
X Lyu, T Liu, X Liu, C He, L Nan, H Zeng - Energy, 2023 - Elsevier
With the aggravation of energy crisis and greenhouse effect, energy transformation is
imperative. The problems of renewable energy uncertainties and carbon emission need to …
imperative. The problems of renewable energy uncertainties and carbon emission need to …