A systematic review of building electricity use profile models

X Kang, J An, D Yan - Energy and Buildings, 2023 - Elsevier
The building sector contributes significantly to overall energy consumption and carbon
emissions. Improving renewable energy utilization in buildings is of considerable …

A review of electricity tariffs and enabling solutions for optimal energy management

DA Zaki, M Hamdy - Energies, 2022 - mdpi.com
Today, electricity tariffs play an essential role in the electricity retail market as they are the
key factor for the decision-making of end-users. Additionally, tariffs are necessary for …

[HTML][HTML] DA-LSTM: A dynamic drift-adaptive learning framework for interval load forecasting with LSTM networks

F Bayram, P Aupke, BS Ahmed, A Kassler… - … Applications of Artificial …, 2023 - Elsevier
Load forecasting is a crucial topic in energy management systems (EMS) due to its vital role
in optimizing energy scheduling and enabling more flexible and intelligent power grid …

A machine learning-based framework for clustering residential electricity load profiles to enhance demand response programs

V Michalakopoulos, E Sarmas, I Papias… - Applied Energy, 2024 - Elsevier
Load shapes derived from smart meter data are frequently employed to analyze daily energy
consumption patterns, particularly in the context of applications like Demand Response …

[HTML][HTML] Electricity scenarios for Hungary: Possible role of wind and solar resources in the energy transition

J Campos, C Csontos, B Munkácsy - Energy, 2023 - Elsevier
The paper examines the compatibility of wind and solar energy resources with projections of
future electricity demand in Hungary. For such, we model the national electricity system and …

Gaussian Mixture Model based pattern recognition for understanding the long-term impact of COVID-19 on energy consumption of public buildings

Z Huang, Z Gou - Journal of Building Engineering, 2023 - Elsevier
At present, the structural transformation of energy demand of public buildings in the post-
pandemic era is not well known, and there is also a lack of fine-grained research on energy …

[HTML][HTML] Uncovering the financial impact of energy-efficient building characteristics with eXplainable artificial intelligence

K Konhäuser, T Werner - Applied Energy, 2024 - Elsevier
The urgency to combat climate change through decarbonization efforts is more crucial than
ever. The global building sector is one of the primary contributors to carbon emissions, yet …

A machine learning framework to estimate residential electricity demand based on smart meter electricity, climate, building characteristics, and socioeconomic …

MK Peplinski, B Dilkina, M Chen, SJ Silva… - Applied Energy, 2024 - Elsevier
Due to the substantial portion of total electricity use attributed to the residential sector and
projected rises in demand, anticipating future energy needs in the context of a warming …

Customer segmentation based on smart meter data analytics: Behavioral similarities with manual categorization for building types

H Komatsu, O Kimura - Energy and Buildings, 2023 - Elsevier
Among the techniques supporting information services that promote energy conservation,
clustering has been widely used for customer segmentation. However, the potential of smart …

Clustering and analysis of air source heat pump air heater usage patterns of inhabitants in Qinghai-Tibet Plateau areas

J Li, M Deng, X Wang, X Wang, R Ma - Journal of Building Engineering, 2023 - Elsevier
Occupant behavior is one of the most important factors influencing the level of energy
consumption in the operational phase of buildings. The unique climatic conditions of the …