Results 11 to 20 of about 72,416 (315)

Performance Analysis of Statistical, Machine Learning and Deep Learning Models in Long-Term Forecasting of Solar Power Production

, 2023
The Machine Learning/Deep Learning (ML/DL) forecasting model has helped stakeholders overcome uncertainties associated with renewable energy resources and time planning for probable near-term power fluctuations.
Qin Wang, Pol, Suhas, Dhamala, Anibesh, Argenis Bilbao, Ashish Sedai, Anibesh Dhamala, Gautam, Shishir, Suhas Pol, Sedai, Ashish, Wigington, Adam, Adam Wigington, Shishir Gautam, Dhakal, Rabin, Rabin Dhakal, Bilbao, Argenis, Wang, Qin   +15 more
core   +1 more source

Intra-Day Solar Power Forecasting Strategy for Managing Virtual Power Plants

Sensors, 2021
Solar energy penetration has been on the rise worldwide during the past decade, attracting a growing interest in solar power forecasting over short time horizons.
Guillermo Moreno, Carlos Santos, Pedro Martín, Francisco Javier Rodríguez, Rafael Peña, Branislav Vuksanovic   +5 more
doaj   +1 more source

Probabilistic Power Quality Level Forecasting through Quantile Regression Models

, 2022
Waveform distortions are Power Quality (PQ) disturbances with harmful impacts on power system components, and planning engineers and system operators are deeply interested in new methodologies able to provide a support to limit this impact.
De Falco P., Caramia P., Carpinelli G., Bracale A.   +3 more
core   +1 more source

Using conditional kernel density estimation for wind power density forecasting [PDF]

, 2012
Of the various renewable energy resources, wind power is widely recognized as one of the most promising. The management of wind farms and electricity systems can benefit greatly from the availability of estimates of the probability distribution of wind ...
Jeon, Jooyoung, Taylor, James W., Jeon, Jooyong, Taylor, James   +3 more
core   +1 more source

Residential Power Load Forecasting

Procedia Computer Science, 2014
AbstractThe prepaid electric power metering market is being driven in large part by advancements in and the adoption of Smart Grid technology. Advanced smart meters facilitate the deployment of prepaid systems with smart prepaid meters. A successful program hinges on the ability to accurately predict the amount of energy consumed on a daily basis for ...
Patrick Day, Michael Fabian, Don Noble, George Ruwisch, Ryan Spencer, Jeff Stevenson, Rajesh Thoppay   +6 more
openaire   +1 more source

A Hybrid Model for Multi-Day-Ahead Electricity Price Forecasting considering Price Spikes

, 2023
This paper proposes a new hybrid model to forecast electricity market prices up to four days ahead. The components of the proposed model are combined in two dimensions.
Manuel Zamudio López, Hamidreza Zareipour, Mike Quashie, Daniel Manfre Jaimes   +3 more
core   +1 more source

Forecasting of Power Demands Using Deep Learning

Applied Sciences, 2020
The forecasting of electricity demands is important for planning for power generator sector improvement and preparing for periodical operations. The prediction of future electricity demand is a challenging task due to the complexity of the available ...
Taehyung Kang, Dae Yeong Lim, Hilal Tayara, Kil To Chong   +3 more
doaj   +1 more source

Asset Bundling for Wind Power Forecasting

CoRR, 2023
The growing penetration of intermittent, renewable generation in US power grids, especially wind and solar generation, results in increased operational uncertainty. In that context, accurate forecasts are critical, especially for wind generation, which exhibits large variability and is historically harder to predict.
Hanyu Zhang, Mathieu Tanneau, Chaofan Huang, V. Roshan Joseph, Shangkun Wang, Pascal Van Hentenryck   +5 more
openaire   +2 more sources

Characterisation of large changes in wind power for the day-ahead market using a fuzzy logic approach [PDF]

, 2014
Wind power has become one of the renewable resources with a major growth in the electricity market. However, due to its inherent variability, forecasting techniques are necessary for the optimum scheduling of the electric grid, specially during ramp ...
Cant, R, Martínez-Arellano, G, Cant, R., Lotfi, A, Lotfi, A., Windmill, C., Windmill, C, Nolle, L., Nolle, L, Martínez-Arellano, G.   +9 more
core   +1 more source

Different Forecasting Horizons Based Performance Analysis of Electricity Load Forecasting Using Multilayer Perceptron Neural Network

, 2021
With an uninterrupted power supply to the consumer, it is obligatory to balance the electricity generated by the electricity load. The effective planning of economic dispatch, reserve requirements, and quality power provision for accurate consumer ...
Manogaran Madhiarasan, Mohamed Louzazni
core   +1 more source