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A systematic review of building electricity use profile models
The building sector contributes significantly to overall energy consumption and carbon
emissions. Improving renewable energy utilization in buildings is of considerable …
emissions. Improving renewable energy utilization in buildings is of considerable …
From consumer to prosumer: A model-based analysis of costs and benefits of grid-connected residential PV-battery systems
The development of the European PV market has shown the strong potential for using grid-
connected solar PV systems operated simultaneously with battery storage. Since 2018, an …
connected solar PV systems operated simultaneously with battery storage. Since 2018, an …
Mid-term electricity demand forecasting using improved multi-mode reconstruction and particle swarm-enhanced support vector regression
L Wang, X Wang, Z Zhao - Energy, 2024 - Elsevier
Balancing electricity supply and demand is crucial for China's energy transition and the
stability of its electricity market. Accurate prediction of mid-term electricity demand plays a …
stability of its electricity market. Accurate prediction of mid-term electricity demand plays a …
Mismatch analysis of rooftop photovoltaics supply and farmhouse load: Data dimensionality reduction and explicable load pattern mining via hybrid deep learning
D Gao, Y Zhi, X Rong, X Yang - Applied Energy, 2025 - Elsevier
Establishing a new type of electricity system based on rooftop photovoltaics (PV) can
facilitate the energy transition in rural China. Research on the mismatch between the PV …
facilitate the energy transition in rural China. Research on the mismatch between the PV …
Building electricity load forecasting based on spatiotemporal correlation and electricity consumption behavior information
Accurate prediction of building electricity load is essential for grid management and building
optimization operations. This paper proposes a novel approach based on spatiotemporal …
optimization operations. This paper proposes a novel approach based on spatiotemporal …
A deep clustering framework for load pattern segmentation
In recent years, the widespread use of smart meters in power networks has generated a
wealth of data from electricity customers. However, much of this real-world smart meter …
wealth of data from electricity customers. However, much of this real-world smart meter …
Time-series data clustering with load-shape preservation for identifying residential energy consumption behaviors
Categorizing residential energy demand patterns is a principal task for demand-side
management (DSM) and energy-saving strategies. While deep learning (DL)-based …
management (DSM) and energy-saving strategies. While deep learning (DL)-based …
[HTML][HTML] Classification model of electricity consumption behavior based on sparse denoising autoencoder feature dimensionality reduction and spectral clustering
Y Huang, Z Yao, Q Xu - International Journal of Electrical Power & Energy …, 2024 - Elsevier
The development of electrical measurement technology has brought high latitude residential
electricity consumption data to power companies, which contains the characteristics of users' …
electricity consumption data to power companies, which contains the characteristics of users' …
Enhancing electrical load profile segmentation for smart campus energy management
Efficient electrical load profile segmentation is essential for optimizing energy management,
facilitating data-driven decision-making and operational efficiency. This paper addresses a …
facilitating data-driven decision-making and operational efficiency. This paper addresses a …
A new binary encoding method for energy consumption patterns quantification
H Fang, JW **ao, YW Wang… - IEEE Transactions on …, 2024 - ieeexplore.ieee.org
Extracting users' energy consumption patterns (ECPs) from smart meter data is an important
work for retailers. The existing literature usually describe these patterns by clustering the …
work for retailers. The existing literature usually describe these patterns by clustering the …