4.5 Article

Best-tree wavelet packet transform bidirectional GRU for short-term load forecasting

相关参考文献

注意:仅列出部分参考文献,下载原文获取全部文献信息。
Article Computer Science, Hardware & Architecture

Fuzzy-based weighting long short-term memory network for demand forecasting

Maryam Imani

Summary: This paper proposes a hybrid forecasting method that combines fuzzy expert systems and deep learning methods for electrical load forecasting. The method first extracts the relationships between different time instances of the load time series using a fuzzy system, and then uses a long short-term memory network to forecast the load based on the obtained weights. Experimental results show the superior performance of the proposed method in various evaluation measures.

JOURNAL OF SUPERCOMPUTING (2023)

Article Engineering, Electrical & Electronic

A convolutional neural network-based approach to composite power system reliability evaluation

Md. Kamruzzaman et al.

Summary: This paper introduces a machine learning-based approach combined with Monte Carlo simulation to enhance the computational efficiency of composite power system reliability evaluation. The proposed convolutional neural network (CNN) regression method is used to determine the minimum load curtailments of sampled states without having to solve the optimal power flow problem.

INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS (2022)

Article Computer Science, Hardware & Architecture

A clustering-based short-term load forecasting using independent component analysis and multi-scale decomposition transform

Roohollah Keshvari et al.

Summary: A short-term electrical load forecasting model based on ICA, discrete wavelet transform, clustering, ANOVA, and SVR was proposed, which successfully reduced forecasting errors on multiple datasets and generated the most informative subsequences.

JOURNAL OF SUPERCOMPUTING (2022)

Review Engineering, Electrical & Electronic

Review of load forecasting based on artificial intelligence methodologies, models, and challenges**

Hui Hou et al.

Summary: This paper comprehensively summarizes the load forecasting based on artificial intelligence models, including data processing, forecasting methods, and the selection of artificial intelligence models. The future research trends are also discussed.

ELECTRIC POWER SYSTEMS RESEARCH (2022)

Article Multidisciplinary Sciences

A Hybrid Solar Irradiance Forecasting Using Full Wavelet Packet Decomposition and Bi-Directional Long Short-Term Memory (BiLSTM)

Pardeep Singla et al.

Summary: The paper proposes a hybrid model using FWPD and BiLSTM to forecast solar irradiance, addressing the threat of intermittency and stochastic nature of solar PV output on grid security and reliability. The model shows better performance in decomposition and prediction errors compared to traditional contrast models, demonstrating its effectiveness.

ARABIAN JOURNAL FOR SCIENCE AND ENGINEERING (2022)

Article Energy & Fuels

Short-term electric load forecasting for buildings using logistic mixture vector autoregressive model with curve registration

Dongyeon Jeong et al.

Summary: This paper introduces a novel day-ahead electric load forecasting model that combines clustering and forecasting through the logistic mixture vector autoregressive model. Experimental results demonstrate that the proposed model outperforms traditional forecasting methods.

APPLIED ENERGY (2021)

Article Energy & Fuels

Comparison of Heat Demand Prediction Using Wavelet Analysis and Neural Network for a District Heating Network

Szabolcs Kovac et al.

Summary: Short-Term Load Prediction (STLP) is crucial in energy planning, focusing on analyzing historical data to forecast heat consumption. Artificial Neural Networks (ANNs) are utilized, with challenges including lack of precise architectural guidelines and presence of false information in training data. The research compares various processing and training algorithms, emphasizing the need for normalizing raw data using wavelet transforms.

ENERGIES (2021)

Article Engineering, Multidisciplinary

Short-Term Load Forecasting Using Neural Network and Particle Swarm Optimization (PSO) Algorithm

Zahra Shafiei Chafi et al.

Summary: In this study, a short-term electrical load forecasting method using neural network and particle swarm optimization algorithm was proposed to improve prediction accuracy by determining neural network parameters and defining an error function. The method was tested on the Iranian power grid using MATLAB software, and the results demonstrated the capabilities of accurately predicting the electrical load.

MATHEMATICAL PROBLEMS IN ENGINEERING (2021)

Article Engineering, Electrical & Electronic

Convolutional and recurrent neural network based model for short-term load forecasting

Hosein Eskandari et al.

Summary: This paper presents a method for electrical load forecasting based on CNN and RNN, improving the accuracy of load consumption prediction by considering external factors. Experimental results demonstrate the superiority of this method in short-term load forecasting compared to other recent works.

ELECTRIC POWER SYSTEMS RESEARCH (2021)

Article Energy & Fuels

Forecasting of Market Clearing Volume Using Wavelet Packet-Based Neural Networks with Tracking Signals

Sumit Saroha et al.

Summary: A hybrid model based on wavelet packet decomposition and linear neural network was proposed for demand forecasting in the Indian electricity market. The model showed excellent performance in terms of accuracy and universality, confirming that hybrid models are effective forecasting tools.

ENERGIES (2021)

Article Engineering, Electrical & Electronic

A proposed intelligent short-term load forecasting hybrid models of ANN, WNN and KF based on clustering techniques for smart grid

Hamed H. H. Aly

ELECTRIC POWER SYSTEMS RESEARCH (2020)

Article Engineering, Electrical & Electronic

A Multivariate Approach to Probabilistic Industrial Load Forecasting

Antonio Bracale et al.

ELECTRIC POWER SYSTEMS RESEARCH (2020)

Article Computer Science, Information Systems

A Multifactorial Framework for Short-Term Load Forecasting System as Well as the Jinan's Case Study

Ya Gao et al.

IEEE ACCESS (2020)

Article Computer Science, Information Systems

Hybrid CNN-LSTM Model for Short-Term Individual Household Load Forecasting

Musaed Alhussein et al.

IEEE ACCESS (2020)

Article Computer Science, Information Systems

Multimodal Feature Extraction and Fusion Deep Neural Networks for Short-Term Load Forecasting

Zhengmin Kong et al.

IEEE ACCESS (2020)

Proceedings Paper Engineering, Electrical & Electronic

Sequence to Image Transform Based Convolutional Neural Network for Load Forecasting

Maryam Imani et al.

2019 27TH IRANIAN CONFERENCE ON ELECTRICAL ENGINEERING (ICEE 2019) (2019)

Article Engineering, Electrical & Electronic

Deep Learning for Household Load Forecasting-A Novel Pooling Deep RNN

Heng Shi et al.

IEEE TRANSACTIONS ON SMART GRID (2018)

Article Computer Science, Artificial Intelligence

Multicolumn RBF Network

Ammar O. Hoori et al.

IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS (2018)

Review Engineering, Electrical & Electronic

Forecasting the load of electrical power systems in mid- and long-term horizons: a review

Swasti R. Khuntia et al.

IET GENERATION TRANSMISSION & DISTRIBUTION (2016)

Article Engineering, Electrical & Electronic

Short-term load forecasting by wavelet transform and evolutionary extreme learning machine

Song Li et al.

ELECTRIC POWER SYSTEMS RESEARCH (2015)

Proceedings Paper Computer Science, Hardware & Architecture

A Data-driven Hybrid Optimization Model for Short-term Residential Load Forecasting

Xiu Cao et al.

CIT/IUCC/DASC/PICOM 2015 IEEE INTERNATIONAL CONFERENCE ON COMPUTER AND INFORMATION TECHNOLOGY - UBIQUITOUS COMPUTING AND COMMUNICATIONS - DEPENDABLE, AUTONOMIC AND SECURE COMPUTING - PERVASIVE INTELLIGENCE AND COMPUTING (2015)

Article Computer Science, Artificial Intelligence

An Incremental Design of Radial Basis Function Networks

Hao Yu et al.

IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS (2014)

Article Engineering, Electrical & Electronic

Very Short-Term Load Forecasting: Wavelet Neural Networks With Data Pre-Filtering

Che Guan et al.

IEEE TRANSACTIONS ON POWER SYSTEMS (2013)

Article Engineering, Electrical & Electronic

A Strategy for Short-Term Load Forecasting by Support Vector Regression Machines

Ervin Ceperic et al.

IEEE TRANSACTIONS ON POWER SYSTEMS (2013)

Article Engineering, Electrical & Electronic

Short-Term Load Forecasting: Similar Day-Based Wavelet Neural Networks

Ying Chen et al.

IEEE TRANSACTIONS ON POWER SYSTEMS (2010)

Article Engineering, Biomedical

A Novel Criterion of Wavelet Packet Best Basis Selection for Signal Classification With Application to Brain-Computer Interfaces

Denis Vautrin et al.

IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING (2009)

Article Economics

An evaluation of methods for very short-term load forecasting using minute-by-minute British data

James W. Taylor

INTERNATIONAL JOURNAL OF FORECASTING (2008)

Article Engineering, Electrical & Electronic

Feature extraction via multiresolution analysis for short-term load forecasting

AJR Reis et al.

IEEE TRANSACTIONS ON POWER SYSTEMS (2005)

Article Management

Short-term electricity demand forecasting using double seasonal exponential smoothing

JW Taylor

JOURNAL OF THE OPERATIONAL RESEARCH SOCIETY (2003)