Results 81 to 90 of about 127,570 (181)

Research on Short-term Load Forecasting Algorithm Based on VMD and TCN

open access: yesJournal of Harbin University of Science and Technology
Aiming at the low accuracy of short-term load forecasting in substation area, a temporal convolutional network short-term load forecasting algorithm based on variational mode decomposition is proposed in this paper.
WANG Qing   +6 more
doaj   +1 more source

Improving Short-Term Electricity Price Forecasting Using Day-Ahead LMP with ARIMA Models

open access: yes, 2018
Short-term electricity price forecasting has become important for demand side management and power generation scheduling. Especially as the electricity market becomes more competitive, a more accurate price prediction than the day-ahead locational ...
Miller, Carol   +3 more
core   +1 more source

Short-Term Load Forecasting Based on Wavelet Transform and Least Squares Support Vector Machine Optimized by Fruit Fly Optimization Algorithm

open access: yesJournal of Electrical and Computer Engineering, 2015
Electric power is a kind of unstorable energy concerning the national welfare and the people’s livelihood, the stability of which is attracting more and more attention.
Wei Sun, Minquan Ye
doaj   +1 more source

Short-Term Load Forecasting 2019 [PDF]

open access: yes, 2021
Antonio Gabaldón   +2 more
openaire   +3 more sources

Application of Deep Learning Long Short-Term Memory in Energy Demand Forecasting

open access: yes, 2019
The smart metering infrastructure has changed how electricity is measured in both residential and industrial application. The large amount of data collected by smart meter per day provides a huge potential for analytics to support the operation of a ...
D Alahakoon   +14 more
core   +1 more source

Short-Term Load Forecasting With Exponentially Weighted Methods

open access: yesIEEE Transactions on Power Systems, 2012
Short-term load forecasts are needed for the efficient management of power systems. Although weather-based modeling is common, univariate models can be useful when the lead time of interest is less than one day. A class of univariate methods that has performed well with intraday data is exponential smoothing.
openaire   +2 more sources

Wavelet-based short-term load forecasting using optimized anfis [PDF]

open access: yes, 2016
This paper focuses on forecasting electric load consumption using optimized Adaptive Neuro-Fuzzy inference System (ANFIS). It employs the use of Particle Swarm Optimization (PSO) to optimize ANFIS, with aim of improving its speed and accuracy.
Abubakar, I.   +3 more
core  

Enhanced Neuro-Fuzzy Architecture for Electrical Load Forecasting [PDF]

open access: yes, 2010
Previous researches about electrical load time series data forecasting showed that the result was not satisfying. This paper elaborates the enhanced neuro-fuzzy architecture for the same application.
Ferdinando, Hany   +2 more
core   +2 more sources

Short-Term Load Forecasting Using a Novel Deep Learning Framework

open access: yesEnergies, 2018
Short-term load forecasting is the basis of power system operation and analysis. In recent years, the use of a deep belief network (DBN) for short-term load forecasting has become increasingly popular. In this study, a novel deep-learning framework based
Xiaoyu Zhang   +4 more
doaj   +1 more source

Forecasting wholesale electricity prices: A review of time series models [PDF]

open access: yes
In this paper we assess the short-term forecasting power of different time series models in the electricity spot market. We calibrate autoregression (AR) models, including specifications with a fundamental (exogenous) variable - system load, to ...
Weron, Rafal
core   +1 more source

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