Short Term Load Forecasting

Short-term load forecasting (STLF) aims to accurately predict electricity demand over short time horizons, crucial for efficient grid management and market operations. Current research emphasizes improving forecasting accuracy and robustness using advanced machine learning models, including recurrent neural networks (RNNs), convolutional neural networks (CNNs), transformer networks, and hybrid approaches that combine these architectures with techniques like meta-learning, attention mechanisms, and multi-scale temporal decomposition. These advancements address challenges posed by data scarcity, heterogeneity, and privacy concerns, particularly in the context of smart grids and federated learning. The resulting improvements in STLF accuracy have significant implications for optimizing energy resource allocation, enhancing grid stability, and facilitating the integration of renewable energy sources.

Papers

October 19, 2024

Testing the Efficacy of Hyperparameter Optimization Algorithms in Short-Term Load Forecasting
Tugrul Cabir Hakyemez, Omer Adar
Bayesian Optimization Hyperparameter Optimization Level Test Forecasting Performance Short Term Load Forecasting Surrogate Model Training

June 9, 2024

Few-Shot Load Forecasting Under Data Scarcity in Smart Grids: A Meta-Learning Approach
Georgios Tsoumplekas, Christos L. Athanasiadis, Dimitrios I. Doukas, Antonios Chrysopoulos, Pericles A. Mitkas
Meta Learning Load Forecasting Smart Grid Data Scarcity Agnostic Meta learnIng Short Term Load Forecasting Historical Load

June 2, 2024

Multi-variable Adversarial Time-Series Forecast Model
Xiaoqiao Chen
Time Series Power System Load Forecasting Short Term Load Forecasting

May 29, 2024

Multiscale Spatio-Temporal Enhanced Short-term Load Forecasting of Electric Vehicle Charging Stations
Zongbao Zhang, Jiao Hao, Wenmeng Zhao, Yan Liu, Yaohui Huang, Xinhang Luo
Spatio Temporal Load Forecasting Short Term Load Forecasting Electric Vehicle Charging Station

April 7, 2024

Some variation of COBRA in sequential learning setup
Aryan Bhambu, Arabin Kumar Dey
Human Prediction Multivariate Time Series Forecasting Category Wise Variation Bayesian Optimisation System Configuration Short Term Load Forecasting Original CoBRA Structured Regression

April 1, 2024

Addressing Heterogeneity in Federated Load Forecasting with Personalization Layers
Shourya Bose, Yu Zhang, Kibaek Kim
Energy Consumption Load Forecasting Smart Meter Short Term Load Forecasting Heterogeneity Challenge Personalization Layer

February 18, 2024

Interpretable Short-Term Load Forecasting via Multi-Scale Temporal Decomposition
Yuqi Jiang, Yan Li, Yize Chen
Load Forecasting Short Term Load Forecasting Multi Scale Decomposition Global Temporal

November 21, 2023

Privacy-Preserving Load Forecasting via Personalized Model Obfuscation
Shourya Bose, Yu Zhang, Kibaek Kim
Load Forecasting Obfuscation Technique Smart Meter Short Term Load Forecasting

October 26, 2023

Secure short-term load forecasting for smart grids with transformer-based federated learning
Jonas Sievers, Thomas Blank
Transformer Based Federated Learning Load Forecasting Smart Grid Short Term Load Forecasting

September 22, 2023

Federated Short-Term Load Forecasting with Personalization Layers for Heterogeneous Clients
Shourya Bose, Kibaek Kim
Personalized Federated Learning Energy Consumption Heterogeneous Client Short Term Load Forecasting Personalization Layer

September 7, 2023

Short-Term Load Forecasting Using A Particle-Swarm Optimized Multi-Head Attention-Augmented CNN-LSTM Network
Paapa Kwesi Quansah, Edwin Kwesi Ansah Tenkorang
Network Programming Particle Swarm Optimization Energy Consumption Forecasting Performance Multi Head Short Term Load Forecasting

September 2, 2023

Short-term power load forecasting method based on CNN-SAEDN-Res
Yang Cui, Han Zhu, Yijian Wang, Lu Zhang, Yang Li
Deep Learning Convolutional Neural Network Load Forecasting Short Term Load Forecasting

June 30, 2023

BuildingsBench: A Large-Scale Dataset of 900K Buildings and Benchmark for Short-Term Load Forecasting
Patrick Emami, Abhijeet Sahu, Peter Graf
Zero Shot New Benchmark Large Scale Dataset Load Forecasting Residential Building Short Term Load Forecasting Short Term Forecasting

February 25, 2023

In Search of Deep Learning Architectures for Load Forecasting: A Comparative Analysis and the Impact of the Covid-19 Pandemic on Model Performance
Sotiris Pelekis, Evangelos Karakolis, Francisco Silva, Vasileios Schoinas, Spiros Mouzakitis, Georgios Kormpakis, Nuno Amaro, John Psarras
Long Short Term Memory Comparative Study Deep Learning Architecture Model Performance Load Forecasting Covid 19 Pandemic Short Term Load Forecasting Neural Forecasting Net Load Forecasting

December 18, 2022

Contextually Enhanced ES-dRNN with Dynamic Attention for Short-Term Load Forecasting
Slawek Smyl, Grzegorz Dudek, Paweł Pełka
Recurrent Neural Network Load Forecasting Short Term Load Forecasting Dynamic Attention

August 1, 2022

Short-term Load Forecasting with Distributed Long Short-Term Memory
Yi Dong, Yang Chen, Xingyu Zhao, Xiaowei Huang
Long Short Term Memory Energy Consumption Load Forecasting Demand Response Short Term Load Forecasting

June 23, 2022

Deep Reinforcement Learning-Assisted Federated Learning for Robust Short-term Utility Demand Forecasting in Electricity Wholesale Markets
Chenghao Huang, Weilong Chen, Shengrong Bu, Yanru Zhang
Deep Reinforcement Short Term Load Forecasting

December 29, 2021

Artificial Intelligence and Statistical Techniques in Short-Term Load Forecasting: A Review
Ali Bou Nassif, Bassel Soudan, Mohammad Azzeh, Imtinan Attilli, Omar AlMulla
Neural Network Artificial Intelligence Narrative Review Hybrid Model Demand Forecasting Statistical Method Short Term Load Forecasting Short Term Forecasting

November 23, 2021

Appliance Level Short-term Load Forecasting via Recurrent Neural Network
Yuqi Zhou, Arun Sukumaran Nair, David Ganger, Abhinandan Tripathi, Chaitanya Baone, Hao Zhu
Recurrent Neural Network Long Short Term Memory Load Forecasting Short Term Load Forecasting

Short Term Load Forecasting

Papers

Testing the Efficacy of Hyperparameter Optimization Algorithms in Short-Term Load Forecasting

Few-Shot Load Forecasting Under Data Scarcity in Smart Grids: A Meta-Learning Approach

Multi-variable Adversarial Time-Series Forecast Model

Multiscale Spatio-Temporal Enhanced Short-term Load Forecasting of Electric Vehicle Charging Stations

Some variation of COBRA in sequential learning setup

Addressing Heterogeneity in Federated Load Forecasting with Personalization Layers

Interpretable Short-Term Load Forecasting via Multi-Scale Temporal Decomposition

Privacy-Preserving Load Forecasting via Personalized Model Obfuscation

Secure short-term load forecasting for smart grids with transformer-based federated learning

Federated Short-Term Load Forecasting with Personalization Layers for Heterogeneous Clients

Short-Term Load Forecasting Using A Particle-Swarm Optimized Multi-Head Attention-Augmented CNN-LSTM Network

Short-term power load forecasting method based on CNN-SAEDN-Res

BuildingsBench: A Large-Scale Dataset of 900K Buildings and Benchmark for Short-Term Load Forecasting

In Search of Deep Learning Architectures for Load Forecasting: A Comparative Analysis and the Impact of the Covid-19 Pandemic on Model Performance

Contextually Enhanced ES-dRNN with Dynamic Attention for Short-Term Load Forecasting

Short-term Load Forecasting with Distributed Long Short-Term Memory

Deep Reinforcement Learning-Assisted Federated Learning for Robust Short-term Utility Demand Forecasting in Electricity Wholesale Markets

Artificial Intelligence and Statistical Techniques in Short-Term Load Forecasting: A Review

Appliance Level Short-term Load Forecasting via Recurrent Neural Network