Electrical load forecasting models: A critical systematic review
Electricity forecasting is an essential component of smart grid, which has attracted
increasing academic interest. Forecasting enables informed and efficient responses for …
increasing academic interest. Forecasting enables informed and efficient responses for …
Applications of hybrid models in chemical, petroleum, and energy systems: A systematic review
Mathematical modeling and simulation methods are important tools in studying various
processes in science and engineering. In the current review, we focus on the applications of …
processes in science and engineering. In the current review, we focus on the applications of …
Deep learning framework to forecast electricity demand
The increasing world population and availability of energy hungry smart devices are major
reasons for alarmingly high electricity consumption in the current times. So far, various …
reasons for alarmingly high electricity consumption in the current times. So far, various …
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 review on machine learning forecasting growth trends and their real-time applications in different energy systems
T Ahmad, H Chen - Sustainable Cities and Society, 2020 - Elsevier
Energy forecasting and planning play an important role in energy sector development and
policy formulation. The forecasting model selection mostly based on the availability of the …
policy formulation. The forecasting model selection mostly based on the availability of the …
A novel composite electricity demand forecasting framework by data processing and optimized support vector machine
P Jiang, R Li, N Liu, Y Gao - Applied Energy, 2020 - Elsevier
Reliable forecast of electricity can encourage accessible and responsible information for
scholars, policymakers, end-consumers and managers of the electricity market. Numerous …
scholars, policymakers, end-consumers and managers of the electricity market. Numerous …
Forecasting the annual electricity consumption of Turkey using an optimized grey model
Energy demand forecasting is an important issue for governments, energy sector investors
and other related corporations. Although there are several forecasting techniques, selection …
and other related corporations. Although there are several forecasting techniques, selection …
Forecasting annual gross electricity demand by artificial neural networks using predicted values of socio-economic indicators and climatic conditions: Case of Turkey
ME Günay - Energy Policy, 2016 - Elsevier
In this work, the annual gross electricity demand of Turkey was modeled by multiple linear
regression and artificial neural networks as a function population, gross domestic product …
regression and artificial neural networks as a function population, gross domestic product …
A multi-stage method to predict carbon dioxide emissions using dimensionality reduction, clustering, and machine learning techniques
The main purpose of this paper is to develop an efficient multi-stage methodology to predict
carbon dioxide emissions based on two important variables including the energy …
carbon dioxide emissions based on two important variables including the energy …
Long-term electrical energy consumption formulating and forecasting via optimized gene expression programming
This study formulates the effects of two different historical data types on electrical energy
consumption of ASEAN-5 counties. On this basis, optimized GEP (gene expression …
consumption of ASEAN-5 counties. On this basis, optimized GEP (gene expression …