[HTML][HTML] Big data analytics in smart grids: a review
Y Zhang, T Huang, EF Bompard - Energy informatics, 2018 - Springer
Data analytics are now playing a more important role in the modern industrial systems.
Driven by the development of information and communication technology, an information …
Driven by the development of information and communication technology, an information …
[HTML][HTML] Implementation of artificial intelligence techniques in microgrid control environment: Current progress and future scopes
Microgrids are gaining popularity by facilitating distributed energy resources (DERs) and
forming essential consumer/prosumer centric integrated energy systems. Integration …
forming essential consumer/prosumer centric integrated energy systems. Integration …
State-of-the-art techniques for modelling of uncertainties in active distribution network planning: A review
A Ehsan, Q Yang - Applied energy, 2019 - Elsevier
The intermittent generation of non-dispatchable renewable distributed generation, along
with the load variability, demand growth and electricity market prices impose operational …
with the load variability, demand growth and electricity market prices impose operational …
Clustering of electricity consumption behavior dynamics toward big data applications
In a competitive retail market, large volumes of smart meter data provide opportunities for
load serving entities to enhance their knowledge of customers' electricity consumption …
load serving entities to enhance their knowledge of customers' electricity consumption …
A comparative study of clustering techniques for electrical load pattern segmentation
Smart meters have been widely deployed in power networks since the last decade. This
trend has resulted in an enormous volume of data being collected from the electricity …
trend has resulted in an enormous volume of data being collected from the electricity …
Load profiling and its application to demand response: A review
The smart grid has been revolutionizing electrical generation and consumption through a
two-way flow of power and information. As an important information source from the demand …
two-way flow of power and information. As an important information source from the demand …
[HTML][HTML] Short-term electricity load forecasting—A systematic approach from system level to secondary substations
MG Pinheiro, SC Madeira, AP Francisco - Applied Energy, 2023 - Elsevier
Energy forecasting covers a wide range of prediction problems in the utility industry, such as
forecasting demand, generation, price, and power load over time horizons and different …
forecasting demand, generation, price, and power load over time horizons and different …
Hybrid ensemble deep learning for deterministic and probabilistic low-voltage load forecasting
Accurate and reliable low-voltage load forecasting is critical to optimal operation and control
of distribution network and smart grid. However, compared to traditional regional load …
of distribution network and smart grid. However, compared to traditional regional load …
A model of customizing electricity retail prices based on load profile clustering analysis
The problem of customizing electricity retail prices using data mining techniques is studied
in this paper. The density-based spatial clustering of applications with noise is first applied to …
in this paper. The density-based spatial clustering of applications with noise is first applied to …
Clustering load profiles for demand response applications
With the development of smart grid technologies, residential and commercial loads have
large potentialities to participate in demand response (DR) programs. This makes the data …
large potentialities to participate in demand response (DR) programs. This makes the data …