High Precision LSTM Model for Short-Time Load Forecasting in Power Systems

High Precision LSTM Model for Short-Time Load Forecasting in Power Systems

The paper presents the application of recurrent LSTM neural networks for short-time load forecasting in the Polish Power System (PPS) and a small region of a power system in Central Poland. The objective of the present work was to develop an efficient and accurate method of forecasting the 24-h patt...

Full description

Bibliographic Details
Main Authors:	Tomasz Ciechulski, Stanisław Osowski
Format:	Article
Language:	English
Published:	MDPI AG 2021-05-01
Series:	Energies
Subjects:	recurrent LSTM network load forecasting prediction systems power systems demand-side management
Online Access:	https://www.mdpi.com/1996-1073/14/11/2983

Similar Items

Neural Approaches to Short-Time Load Forecasting in Power Systems—A Comparative Study
by: Stanislaw Osowski, et al.
Published: (2022-04-01)

Wind Power Short-Term Time-Series Prediction Using an Ensemble of Neural Networks
by: Tomasz Ciechulski, et al.
Published: (2024-01-01)

Deep Learning Approach to Power Demand Forecasting in Polish Power System
by: Tomasz Ciechulski, et al.
Published: (2020-11-01)

Multivariate Load Forecasting of Integrated Energy System Based on CEEMDAN-CSO-LSTM-MTL
by: WANG Yongli, LIU Zeqiang, DONG Huanran, LI Dexin, CHEN Xin, GUO Lu, WANG Jiarui
Published: (2025-01-01)

Research on urban power load forecasting based on improved LSTM
by: Zhou Zhenglei, et al.
Published: (2024-10-01)

LS-LSTM-AE: Power load forecasting via Long-Short series features and LSTM-Autoencoder
by: Xin Tong, et al.
Published: (2022-04-01)

A Novel NODE Approach Combined with LSTM for Short-Term Electricity Load Forecasting
by: Songtao Huang, et al.
Published: (2022-12-01)

An EV load forecasting method for using GCN-LSTM
by: HUANG Jian, et al.
Published: (2024-12-01)

Load forecasting analysis for regional and industry power systems-based on ARIMA model and LSTM model
by: Chen Jiongcheng, et al.
Published: (2022-01-01)

Evaluating the EEMD-LSTM model for short-term forecasting of industrial power load: A case study in Vietnam
by: Nam Nguyen Vuu Nhat, et al.
Published: (2023-09-01)

Improving the Efficiency of Multistep Short-Term Electricity Load Forecasting via R-CNN with ML-LSTM
by: Mohammed F. Alsharekh, et al.
Published: (2022-09-01)

Electrical Load Forecast by Means of LSTM: The Impact of Data Quality
by: Alfredo Nespoli, et al.
Published: (2021-02-01)

The Effect of Input Length on Prediction Accuracy in Short-Term Multi-Step Electricity Load Forecasting: A CNN-LSTM Approach
by: Seyda Ozdemir, et al.
Published: (2025-01-01)

Short-term power load forecasting using informer encoder and bi-directional LSTM
by: Tan Shiyu, et al.
Published: (2024-01-01)

Enhancing microgrid forecasting accuracy with SAQ-MTCLSTM: A self-adjusting quantized multi-task ConvLSTM for optimized solar power and load demand predictions
by: Ehtisham Lodhi, et al.
Published: (2024-10-01)

A Data Driven Approach for Day Ahead Short Term Load Forecasting
by: Azfar Inteha, et al.
Published: (2022-01-01)

An enhanced CNN-LSTM based multi-stage framework for PV and load short-term forecasting: DSO scenarios
by: Mohammad Ahmad A. Al-Ja’afreh, et al.
Published: (2023-11-01)

Bayesian Optimization-Based LSTM for Short-Term Heating Load Forecasting
by: Binglin Li, et al.
Published: (2023-08-01)

Adaptive Bi-Directional LSTM Short-Term Load Forecasting with Improved Attention Mechanisms
by: Kun Yu
Published: (2024-07-01)

Multi-horizon short-term load forecasting using hybrid of LSTM and modified split convolution
by: Irshad Ullah, et al.
Published: (2023-09-01)

A Multi-Step Time-Series Clustering-Based Seq2Seq LSTM Learning for a Single Household Electricity Load Forecasting
by: Zaki Masood, et al.
Published: (2022-04-01)

Short-Term Net Load Forecasting with Singular Spectrum Analysis and LSTM Neural Networks
by: Akylas Stratigakos, et al.
Published: (2021-07-01)

An LSTM-SAE-Based Behind-the-Meter Load Forecasting Method
by: Aydin Zaboli, et al.
Published: (2023-01-01)

A Short-Term Residential Load Forecasting Model Based on LSTM Recurrent Neural Network Considering Weather Features
by: Yizhen Wang, et al.
Published: (2021-05-01)

Short-Term Power Load Forecasting in FGSM-Bi-LSTM Networks Based on Empirical Wavelet Transform
by: Qingchan Liu, et al.
Published: (2023-01-01)

Short-term wind power forecasting through stacked and bi directional LSTM techniques
by: Mehmood Ali Khan, et al.
Published: (2024-03-01)

A Hybrid System Based on LSTM for Short-Term Power Load Forecasting
by: Yu Jin, et al.
Published: (2020-11-01)

Smoothed Bernstein Online Aggregation for Short-Term Load Forecasting in IEEE DataPort Competition on Day-Ahead Electricity Demand Forecasting: Post-COVID Paradigm
by: Florian Ziel
Published: (2022-01-01)

Short term power load forecasting based on BES-VMD and CNN-Bi-LSTM method with error correction
by: Nier Wang, et al.
Published: (2023-01-01)

Use of Available Daylight to Improve Short-Term Load Forecasting Accuracy
by: Miguel López, et al.
Published: (2020-12-01)

LSTM-RNN-FNN Model for Load Forecasting Based on Deleuze’s Assemblage Perspective
by: Jie Xin, et al.
Published: (2022-05-01)

Short-term residential load forecasting based on LSTM recurrent neural network
by: Kong, Weicong, et al.
Published: (2021)

Computational Intelligence on Short-Term Load Forecasting: A Methodological Overview
by: Seyedeh Narjes Fallah, et al.
Published: (2019-01-01)

Fusion ConvLSTM-Net: Using Spatiotemporal Features to Increase Residential Load Forecast Horizon
by: Abhishu Oza, et al.
Published: (2025-01-01)

Short-Term Power Load Prediction Method Based on VMD and EDE-BiLSTM
by: Yibo Lai, et al.
Published: (2025-01-01)

Short-Term Load Forecasting Based on Mutual Information and BI-LSTM Considering Fluctuation in Importance Values of Features
by: Shubo Hu, et al.
Published: (2024-01-01)

Short-Term Heavy Overload Forecasting of Public Transformers Based on Combined LSTM-XGBoost Model
by: Hao Ma, et al.
Published: (2023-02-01)

Day Ahead Electric Load Forecast: A Comprehensive LSTM-EMD Methodology and Several Diverse Case Studies
by: Michael Wood, et al.
Published: (2023-03-01)

Energy Demand Load Forecasting for Electric Vehicle Charging Stations Network Based on ConvLSTM and BiConvLSTM Architectures
by: Faisal Mohammad, et al.
Published: (2023-01-01)

Short-Term Load Forecasting Using an LSTM Neural Network for a Grid Operator
by: Joan Sebastian Caicedo-Vivas, et al.
Published: (2023-12-01)