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Load forecasting models in smart grid using smart meter information: a review
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 …
A review on time series forecasting techniques for building energy consumption
Energy consumption forecasting for buildings has immense value in energy efficiency and
sustainability research. Accurate energy forecasting models have numerous implications in …
sustainability research. Accurate energy forecasting models have numerous implications in …
An advanced framework for net electricity consumption prediction: Incorporating novel machine learning models and optimization algorithms
X Li, Z Wang, C Yang, A Bozkurt - Energy, 2024 - Elsevier
In recent years, the escalating demand for electric energy has underscored the need for
robust prediction models capable of accurately anticipating consumption patterns. The …
robust prediction models capable of accurately anticipating consumption patterns. The …
Forecasting short-term electricity load using hybrid support vector regression with grey catastrophe and random forest modeling
GF Fan, M Yu, SQ Dong, YH Yeh, WC Hong - Utilities Policy, 2021 - Elsevier
This paper develops a novel short-term load forecasting model that hybridizes several
machine learning methods, such as support vector regression (SVR), grey catastrophe (GC …
machine learning methods, such as support vector regression (SVR), grey catastrophe (GC …
Optimal load dispatch of community microgrid with deep learning based solar power and load forecasting
L Wen, K Zhou, S Yang, X Lu - Energy, 2019 - Elsevier
A deep recurrent neural network with long short-term memory units (DRNN-LSTM) model is
developed to forecast aggregated power load and the photovoltaic (PV) power output in …
developed to forecast aggregated power load and the photovoltaic (PV) power output in …
Forecasting methods in energy planning models
KB Debnath, M Mourshed - Renewable and Sustainable Energy Reviews, 2018 - Elsevier
Energy planning models (EPMs) play an indispensable role in policy formulation and energy
sector development. The forecasting of energy demand and supply is at the heart of an EPM …
sector development. The forecasting of energy demand and supply is at the heart of an EPM …
A hybrid short-term load forecasting model based on variational mode decomposition and long short-term memory networks considering relevant factors with …
F He, J Zhou, Z Feng, G Liu, Y Yang - Applied energy, 2019 - Elsevier
Short-term load forecasting plays an essential role in the safe and stable operation of power
systems and has always been a vital research issue of energy management. In this …
systems and has always been a vital research issue of energy management. In this …
Grey data analysis
In this book, we answer the calls of the readers of our previous publications and
systematically present the main advances in grey system theory and applications. By …
systematically present the main advances in grey system theory and applications. By …
A comprehensive survey on particle swarm optimization algorithm and its applications
Particle swarm optimization (PSO) is a heuristic global optimization method, proposed
originally by Kennedy and Eberhart in 1995. It is now one of the most commonly used …
originally by Kennedy and Eberhart in 1995. It is now one of the most commonly used …
Short term electricity load forecasting using a hybrid model
J Zhang, YM Wei, D Li, Z Tan, J Zhou - Energy, 2018 - Elsevier
Short term electricity load forecasting is one of the most important issue for all market
participants. Short term electricity load is affected by natural and social factors, which makes …
participants. Short term electricity load is affected by natural and social factors, which makes …