A review of strategies for building energy management system: Model predictive control, demand side management, optimization, and fault detect & diagnosis

D Mariano-Hernández, L Hernández-Callejo… - Journal of Building …, 2021 - Elsevier
Building energy use is expected to grow by more than 40% in the next 20 years. Electricity
remains the largest energy source consumed by buildings, and that demand is growing. To …

Data-driven prediction and optimization toward net-zero and positive-energy buildings: A systematic review

SN Mousavi, MG Villarreal-Marroquín… - Building and …, 2023 - Elsevier
Recent advances toward sustainable cities have promoted the concept of near-zero energy
consumption. A Positive Energy Building (PEB) model has been developed by the European …

[HTML][HTML] Review of urban building energy modeling (UBEM) approaches, methods and tools using qualitative and quantitative analysis

U Ali, MH Shamsi, C Hoare, E Mangina… - Energy and buildings, 2021 - Elsevier
The world has witnessed a significant population shift to urban areas over the past few
decades. Urban areas account for about two-thirds of the world's total primary energy …

Prediction of heating and cooling loads based on light gradient boosting machine algorithms

J Guo, S Yun, Y Meng, N He, D Ye, Z Zhao, L Jia… - Building and …, 2023 - Elsevier
Abstract Machine learning models have been widely used to study the prediction of heating
and cooling loads in residential buildings. However, most of these methods use the default …

Machine learning modelling for predicting non-domestic buildings energy performance: A model to support deep energy retrofit decision-making

S Seyedzadeh, FP Rahimian, S Oliver, S Rodriguez… - Applied Energy, 2020 - Elsevier
Non-domestic buildings contribute 20% of the UK's annual carbon emissions. A contribution
exacerbated by its ageing stock of which only 7% is considered new-build. Consequently …

Machine learning for energy performance prediction at the design stage of buildings

R Olu-Ajayi, H Alaka, I Sulaimon, F Sunmola… - Energy for Sustainable …, 2022 - Elsevier
The substantial amount of energy consumption in buildings and the associated adverse
effects prompts the importance of understanding building energy efficiency. Develo** an …

Prediction of residential district heating load based on machine learning: A case study

Z Wei, T Zhang, B Yue, Y Ding, R **ao, R Wang, X Zhai - Energy, 2021 - Elsevier
Heating load prediction plays an important role in supporting the operation of a residential
district energy station. To find out the most suitable prediction algorithm, seven popular …

Predicting energy consumption in residential buildings using advanced machine learning algorithms

F Dinmohammadi, Y Han, M Shafiee - Energies, 2023 - mdpi.com
The share of residential building energy consumption in global energy consumption has
rapidly increased after the COVID-19 crisis. The accurate prediction of energy consumption …

Improved Harris Hawks optimization with hybrid deep learning based heating and cooling load prediction on residential buildings

RJ Kavitha, C Thiagarajan, PI Priya, AV Anand… - Chemosphere, 2022 - Elsevier
In digital era, energy efficient building remains a hot research topic because of increasing
concern regarding their environmental impact and energy consumption. Designing a …

Automated machine learning-based framework of heating and cooling load prediction for quick residential building design

C Lu, S Li, SR Penaka, T Olofsson - Energy, 2023 - Elsevier
Reducing the heating and cooling load through energy-efficient building design can help
decarbonize the building sector. Heating and cooling load prediction using machine …