Load Forecasting

17 papers with code • 0 benchmarks • 0 datasets

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Most implemented papers

Deep Adaptive Input Normalization for Time Series Forecasting

passalis/dain 21 Feb 2019

Deep Learning (DL) models can be used to tackle time series analysis tasks with great success.

LFRT, A MATLAB Toolbox for Load Forecast & Assesment of Additional Capacity for an Electrical Power System

hazooree/lfrt Conference 2016

A developing country like Pakistan with sizable pressure on their limited financial resources can ill afford either of these two situations about energy forecast: 1) Too optimistic 2) Too conservative.

Fast and Accurate Time Series Classification with WEASEL

patrickzib/SFA 26 Jan 2017

On the popular UCR benchmark of 85 TS datasets, WEASEL is more accurate than the best current non-ensemble algorithms at orders-of-magnitude lower classification and training times, and it is almost as accurate as ensemble classifiers, whose computational complexity makes them inapplicable even for mid-size datasets.

Short-term Load Forecasting with Deep Residual Networks

yalickj/load-forecasting-resnet 30 May 2018

We present in this paper a model for forecasting short-term power loads based on deep residual networks.

Deep Learning for Time Series Forecasting: The Electric Load Case

albertogaspar/dts 22 Jul 2019

Management and efficient operations in critical infrastructure such as Smart Grids take huge advantage of accurate power load forecasting which, due to its nonlinear nature, remains a challenging task.

Coronavirus Optimization Algorithm: A bioinspired metaheuristic based on the COVID-19 propagation model

DataLabUPO/CVOA_academic 30 Mar 2020

A novel bioinspired metaheuristic is proposed in this work, simulating how the coronavirus spreads and infects healthy people.

N-BEATS neural network for mid-term electricity load forecasting

boreshkinai/nbeats-midterm 24 Sep 2020

We show that our proposed deep neural network modeling approach based on the deep neural architecture is effective at solving the mid-term electricity load forecasting problem.

Short-Term Load Forecasting using Bi-directional Sequential Models and Feature Engineering for Small Datasets

manastahir/Short-Term-Load-Forecasting 28 Nov 2020

Electricity load forecasting enables the grid operators to optimally implement the smart grid's most essential features such as demand response and energy efficiency.

Probabilistic Load Forecasting Based on Adaptive Online Learning

MachineLearningBCAM/Load-forecasting-IEEE-TPWRS-2020 30 Nov 2020

Conventional load forecasting techniques obtain single-value load forecasts by exploiting consumption patterns of past load demand.