Load forecasting models in smart grid using smart meter information: a review
F Dewangan, AY Abdelaziz, M Biswal - Energies, 2023 - mdpi.com
The smart grid concept is introduced to accelerate the operational efficiency and enhance
the reliability and sustainability of power supply by operating in self-control mode to find and …
the reliability and sustainability of power supply by operating in self-control mode to find and …
Enhancing smart grid with microgrids: Challenges and opportunities
The modern electric power systems are going through a revolutionary change because of
increasing demand of electric power worldwide, developing political pressure and public …
increasing demand of electric power worldwide, developing political pressure and public …
Review of smart meter data analytics: Applications, methodologies, and challenges
The widespread popularity of smart meters enables an immense amount of fine-grained
electricity consumption data to be collected. Meanwhile, the deregulation of the power …
electricity consumption data to be collected. Meanwhile, the deregulation of the power …
A novel hybrid short-term load forecasting method of smart grid using MLR and LSTM neural network
The short-term load forecasting is crucial in the power system operation and control.
However, due to its nonstationary and complicated random features, an accurate forecast of …
However, due to its nonstationary and complicated random features, an accurate forecast of …
Energy big data: A survey
As a significant application of energy, smart grid is a complicated interconnected power grid
that involves sensors, deployment strategies, smart meters, and real-time data processing. It …
that involves sensors, deployment strategies, smart meters, and real-time data processing. It …
A novel RBF training algorithm for short-term electric load forecasting and comparative studies
Because of their excellent scheduling capabilities, artificial neural networks (ANNs) are
becoming popular in short-term electric power system forecasting, which is essential for …
becoming popular in short-term electric power system forecasting, which is essential for …
Big data issues in smart grids: A survey
M Ghorbanian, SH Dolatabadi… - IEEE Systems Journal, 2019 - ieeexplore.ieee.org
The smart power systems are based upon information and communication technologies,
which lead to a deluge of data originating from various sources. To address these …
which lead to a deluge of data originating from various sources. To address these …
Short-term load-forecasting method based on wavelet decomposition with second-order gray neural network model combined with ADF test
B Li, J Zhang, Y He, Y Wang - IEEE Access, 2017 - ieeexplore.ieee.org
Improving the accuracy of power system load forecasting is important for economic dispatch.
However, a load sequence is highly nonstationary and hence makes accurate forecasting …
However, a load sequence is highly nonstationary and hence makes accurate forecasting …
Incorporating practice theory in sub-profile models for short term aggregated residential load forecasting
B Stephen, X Tang, PR Harvey… - … on Smart Grid, 2015 - ieeexplore.ieee.org
Aspirations of grid independence could be achieved by residential power systems
connected only to small highly variable loads if overall demand on the network can be …
connected only to small highly variable loads if overall demand on the network can be …
Robust ensemble learning framework for day-ahead forecasting of household based energy consumption
Smart energy management mandates a more decentralized energy infrastructure, entailing
energy consumption information on a local level. Household-based energy consumption …
energy consumption information on a local level. Household-based energy consumption …