Related references
Note: Only part of the references are listed.Novel machine learning approach for solar photovoltaic energy output forecast using extra-terrestrial solar irradiance
Cornelia A. Fjelkestam Frederiksen et al.
APPLIED ENERGY (2022)
FPSeq2Q: Fully Parameterized Sequence to Quantile Regression for Net-Load Forecasting With Uncertainty Estimates
Anthony Faustine et al.
IEEE TRANSACTIONS ON SMART GRID (2022)
A hybrid methodology for distribution level photovoltaic power production forecasting verified at the distribution system of Cyprus
Spyros Theocharides et al.
IET RENEWABLE POWER GENERATION (2022)
Data processing and quality verification for improved photovoltaic performance and reliability analytics
Andreas Livera et al.
PROGRESS IN PHOTOVOLTAICS (2021)
Review of low voltage load forecasting: Methods, applications, and recommendations
Stephen Haben et al.
APPLIED ENERGY (2021)
SolarNet: A hybrid reliable model based on convolutional neural network and variational mode decomposition for hourly photovoltaic power forecasting
Deniz Korkmaz
APPLIED ENERGY (2021)
A temporal distributed hybrid deep learning model for day-ahead distributed PV power forecasting
Yinpeng Qu et al.
APPLIED ENERGY (2021)
Short-term electric load forecasting for buildings using logistic mixture vector autoregressive model with curve registration
Dongyeon Jeong et al.
APPLIED ENERGY (2021)
A novel short-term load forecasting framework based on time-series clustering and early classification algorithm
Zhe Chen et al.
ENERGY AND BUILDINGS (2021)
Extensive comparison of physical models for photovoltaic power forecasting
Martin Janos Mayer et al.
APPLIED ENERGY (2021)
Short-term load forecasting using multimodal evolutionary algorithm and random vector functional link network based ensemble learning
Yi Hu et al.
APPLIED ENERGY (2021)
Comparative Analysis of Machine Learning Models for Day-Ahead Photovoltaic Power Production Forecasting
Spyros Theocharides et al.
ENERGIES (2021)
Multi-energy net load forecasting for integrated local energy systems with heterogeneous prosumers
Bin Zhou et al.
INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS (2021)
Short-Term Net Load Forecasting with Singular Spectrum Analysis and LSTM Neural Networks
Akylas Stratigakos et al.
ENERGIES (2021)
Prediction of solar energy guided by pearson correlation using machine learning
Imane Jebli et al.
ENERGY (2021)
Theory-guided deep-learning for electrical load forecasting (TgDLF) via ensemble long short-term memory
Yuntian Chen et al.
ADVANCES IN APPLIED ENERGY (2021)
A hybrid approach based on autoregressive integrated moving average and least-square support vector machine for long-term forecasting of net electricity consumption
Fazil Kaytez
ENERGY (2020)
Using Bayesian Deep Learning to Capture Uncertainty for Residential Net Load Forecasting
Mingyang Sun et al.
IEEE TRANSACTIONS ON POWER SYSTEMS (2020)
High-resolution net load forecasting for micro-neighbourhoods with high penetration of renewable energy sources
P. Kobylinski et al.
INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS (2020)
Day-ahead photovoltaic power production forecasting methodology based on machine learning and statistical post-processing
Spyros Theocharides et al.
APPLIED ENERGY (2020)
A novel electrical net-load forecasting model based on deep neural networks and wavelet transform integration
Mohammadali Alipour et al.
ENERGY (2020)
Spatial Aggregation of Small-Scale Photovoltaic Generation Using Voronoi Decomposition
Javier Lopez Lorente et al.
IEEE TRANSACTIONS ON SUSTAINABLE ENERGY (2020)
Grey System Theory Based Net Load Forecasting for High Renewable Penetrated Power Systems
Sreenu Sreekumar et al.
TECHNOLOGY AND ECONOMICS OF SMART GRIDS AND SUSTAINABLE ENERGY (2020)
Computational Intelligence on Short-Term Load Forecasting: A Methodological Overview
Seyedeh Narjes Fallah et al.
ENERGIES (2019)
Short-Term Load Forecasting in Smart Grids: An Intelligent Modular Approach
Ashfaq Ahmad et al.
ENERGIES (2019)
Energy management in microgrid with considering high penetration of renewable resources and surplus power generation problem
Vahid Sohrabi Tabar et al.
ENERGY (2019)
Probabilistic forecasting of electricity consumption, photovoltaic power generation and net demand of an individual building using Gaussian Processes
D. W. van der Meer et al.
APPLIED ENERGY (2018)
Data-Driven Probabilistic Net Load Forecasting With High Penetration of Behind-the-Meter PV
Yi Wang et al.
IEEE TRANSACTIONS ON POWER SYSTEMS (2018)
Two-Stage Artificial Neural Network Model for Short-Term Load Forecasting
Yuan-Yu Hsu et al.
IFAC PAPERSONLINE (2018)
THE WEATHER RESEARCH AND FORECASTING MODEL Overview, System Efforts, and Future Directions
Jordan G. Powers et al.
BULLETIN OF THE AMERICAN METEOROLOGICAL SOCIETY (2017)
Net load forecasting for high renewable energy penetration grids
Amanpreet Kaur et al.
ENERGY (2016)
Probabilistic electric load forecasting: A tutorial review
Tao Hong et al.
INTERNATIONAL JOURNAL OF FORECASTING (2016)
A Novel RBF Training Algorithm for Short-Term Electric Load Forecasting and Comparative Studies
Carlo Cecati et al.
IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS (2015)
A new scenario generation-based method to solve the unit commitment problem with high penetration of renewable energies
G. J. Osorio et al.
INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS (2015)
A review on artificial intelligence based load demand forecasting techniques for smart grid and buildings
Muhammad Qamar Raza et al.
RENEWABLE & SUSTAINABLE ENERGY REVIEWS (2015)
A Review of Short Term Load Forecasting using Artificial Neural Network Models
Arjun Baliyan et al.
INTERNATIONAL CONFERENCE ON COMPUTER, COMMUNICATION AND CONVERGENCE (ICCC 2015) (2015)
Uncertainty handling using neural network-based prediction intervals for electrical load forecasting
Hao Quan et al.
ENERGY (2014)
The daily and hourly energy consumption and load forecasting using artificial neural network method: a case study using a set of 93 households in Portugal
Filipe Rodrigues et al.
6TH INTERNATIONAL CONFERENCE ON SUSTAINABILITY IN ENERGY AND BUILDINGS (2014)
Very Short-Term Load Forecasting: Wavelet Neural Networks With Data Pre-Filtering
Che Guan et al.
IEEE TRANSACTIONS ON POWER SYSTEMS (2013)
Energy models for demand forecasting-A review
L. Suganthi et al.
RENEWABLE & SUSTAINABLE ENERGY REVIEWS (2012)
Prediction of daily global solar irradiation data using Bayesian neural network: A comparative study
R. Yacef et al.
RENEWABLE ENERGY (2012)
Medium-term electric load forecasting using singular value decomposition
Nazih Abu-Shikhah et al.
ENERGY (2011)
Machine learning based switching model for electricity load forecasting
Shu Fan et al.
ENERGY CONVERSION AND MANAGEMENT (2008)
RBF neural network and ANFIS-based short-term load forecasting approach in real-time price environment
Zhang Yun et al.
IEEE TRANSACTIONS ON POWER SYSTEMS (2008)
Short-term load forecasting methods: An evaluation based on European data
James W. Taylor et al.
IEEE TRANSACTIONS ON POWER SYSTEMS (2007)
A comparison of univariate methods for forecasting electricity demand up to a day ahead
JW Taylor et al.
INTERNATIONAL JOURNAL OF FORECASTING (2006)
Neural networks for short-term load forecasting: A review and evaluation
HS Hippert et al.
IEEE TRANSACTIONS ON POWER SYSTEMS (2001)
Share Paper
