A review on artificial intelligence based load demand forecasting techniques for smart grid and buildings
MQ Raza, A Khosravi - Renewable and Sustainable Energy Reviews, 2015 - Elsevier
Electrical load forecasting plays a vital role in order to achieve the concept of next
generation power system such as smart grid, efficient energy management and better power …
generation power system such as smart grid, efficient energy management and better power …
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 …
Optimal deep learning lstm model for electric load forecasting using feature selection and genetic algorithm: Comparison with machine learning approaches
Background: With the development of smart grids, accurate electric load forecasting has
become increasingly important as it can help power companies in better load scheduling …
become increasingly important as it can help power companies in better load scheduling …
Deep neural network based demand side short term load forecasting
In the smart grid, one of the most important research areas is load forecasting; it spans from
traditional time series analyses to recent machine learning approaches and mostly focuses …
traditional time series analyses to recent machine learning approaches and mostly focuses …
A survey on electric power demand forecasting: future trends in smart grids, microgrids and smart buildings
Recently there has been a significant proliferation in the use of forecasting techniques,
mainly due to the increased availability and power of computation systems and, in particular …
mainly due to the increased availability and power of computation systems and, in particular …
Energy models for demand forecasting—A review
Energy is vital for sustainable development of any nation–be it social, economic or
environment. In the past decade energy consumption has increased exponentially globally …
environment. In the past decade energy consumption has increased exponentially globally …
[HTML][HTML] Effective RNN-based forecasting methodology design for improving short-term power load forecasts: Application to large-scale power-grid time series
AO Aseeri - Journal of Computational Science, 2023 - Elsevier
This article introduces a carefully-engineered forecasting methodology for day-ahead
electric power load forecasts evaluated using the European Network of Transmission …
electric power load forecasts evaluated using the European Network of Transmission …
Day-ahead load forecast using random forest and expert input selection
The electrical load forecast is getting more and more important in recent years due to the
electricity market deregulation and integration of renewable resources. To overcome the …
electricity market deregulation and integration of renewable resources. To overcome the …
Neural networks for short-term load forecasting: A review and evaluation
HS Hippert, CE Pedreira… - IEEE Transactions on …, 2001 - ieeexplore.ieee.org
Load forecasting has become one of the major areas of research in electrical engineering,
and most traditional forecasting models and artificial intelligence techniques have been tried …
and most traditional forecasting models and artificial intelligence techniques have been tried …
Modeling and forecasting short-term power load with copula model and deep belief network
Load forecasting is critical for effective scheduling and operation of power systems, which
are becoming increasingly complex and uncertain, especially with the penetration of …
are becoming increasingly complex and uncertain, especially with the penetration of …