Mid Term Electricity

Mid-term electricity load forecasting, predicting electricity demand from weeks to a year ahead, is crucial for power system planning, grid stability, and energy trading. Research focuses on improving forecasting accuracy using advanced machine learning models, such as Generalized Additive Models (GAMs), Convolutional Neural Networks (CNNs), Recurrent Neural Networks (RNNs, including LSTMs and BiLSTMs), and hybrid architectures combining these approaches, often incorporating weather data and calendar information. These improvements are significant because accurate mid-term forecasts enable better resource allocation, enhance grid reliability, and optimize energy market operations.

Papers

September 18, 2024

Location based Probabilistic Load Forecasting of EV Charging Sites: Deep Transfer Learning with Multi-Quantile Temporal Convolutional Network
Mohammad Wazed Ali (Intelligent Embedded Systems (IES), University of Kassel, Kassel, Germany), Asif bin Mustafa (School of CIT, Technical University of Munich, Munich, Germany), Md. Aukerul Moin Shuvo (Dept. of Computer Science and Engineering, Rajshahi University of Engg. & Technology, Rajshahi, Bangladesh), Bernhard Sick (Intelligent Embedded Systems (IES), University of Kassel, Kassel, Germany)
Load Forecasting Location Information Deep Transfer Load Prediction Electric Vehicle Charging Station Probabilistic Load Mid Term Electricity

June 10, 2024

Short-Term Electricity Demand Forecasting of Dhaka City Using CNN with Stacked BiLSTM
Kazi Fuad Bin Akhter, Sadia Mobasshira, Saief Nowaz Haque, Mahjub Alam Khan Hesham, Tanvir Ahmed
Convolutional Neural Network Long Short Term Memory LSTM Network Load Forecasting Forecasting Performance Mid Term Electricity

May 27, 2024

Efficient mid-term forecasting of hourly electricity load using generalized additive models
Monika Zimmermann, Florian Ziel
Additive Model Generalized Additive Model Mid Term Electricity Novel Forecasting

February 15, 2024

mshw, a forecasting library to predict short-term electricity demand based on multiple seasonal Holt-Winters
Oscar Trull, J. Carlos García-Díaz, Angel Peiró-Signes
Forecasting Performance Demand Forecasting Electricity Demand Mid Term Electricity

January 26, 2024

Electrical Behavior Association Mining for Household ShortTerm Energy Consumption Forecasting
Heyang Yu, Yuxi Sun, Yintao Liu, Guangchao Geng, Quanyuan Jiang
Load Forecasting Association Rule Association Test Mid Term Electricity Home Energy Management

October 24, 2023

Transfer learning for day-ahead load forecasting: a case study on European national electricity demand time series
Alexandros-Menelaos Tzortzis, Sotiris Pelekis, Evangelos Spiliotis, Spiros Mouzakitis, John Psarras, Dimitris Askounis
Case Study Formality Transfer Electricity Demand Forecasting Method Mid Term Electricity

October 23, 2023

Mid-Long Term Daily Electricity Consumption Forecasting Based on Piecewise Linear Regression and Dilated Causal CNN
Zhou Lan, Ben Liu, Yi Feng, Danhuang Dong, Peng Zhang
Consumption Forecasting Electricity Demand Energy Prediction Piecewise Polynomial Mid Term Electricity

June 19, 2023

An Error Correction Mid-term Electricity Load Forecasting Model Based on Seasonal Decomposition
Liping Zhang, Di Wu, Xin Luo
Long Short Term Memory Energy Consumption Microbial Decomposition Multi Step Mid Term Electricity

February 23, 2023

A comparative assessment of deep learning models for day-ahead load forecasting: Investigating key accuracy drivers
Sotiris Pelekis, Ioannis-Konstantinos Seisopoulos, Evangelos Spiliotis, Theodosios Pountridis, Evangelos Karakolis, Spiros Mouzakitis, Dimitris Askounis
Deep Learning Model Long Short Term Memory Comparative Evaluation Day Ahead Enhancing Accuracy Mid Term Electricity

February 14, 2023

Masked Multi-Step Probabilistic Forecasting for Short-to-Mid-Term Electricity Demand
Yiwei Fu, Nurali Virani, Honggang Wang
Mid Term Electricity Learning Based Forecasting

September 28, 2022

Masked Multi-Step Multivariate Time Series Forecasting with Future Information
Yiwei Fu, Honggang Wang, Nurali Virani
Mid Term Electricity

Mid Term Electricity

Papers

Location based Probabilistic Load Forecasting of EV Charging Sites: Deep Transfer Learning with Multi-Quantile Temporal Convolutional Network

Short-Term Electricity Demand Forecasting of Dhaka City Using CNN with Stacked BiLSTM

Efficient mid-term forecasting of hourly electricity load using generalized additive models

mshw, a forecasting library to predict short-term electricity demand based on multiple seasonal Holt-Winters

Electrical Behavior Association Mining for Household ShortTerm Energy Consumption Forecasting

Transfer learning for day-ahead load forecasting: a case study on European national electricity demand time series

Mid-Long Term Daily Electricity Consumption Forecasting Based on Piecewise Linear Regression and Dilated Causal CNN

An Error Correction Mid-term Electricity Load Forecasting Model Based on Seasonal Decomposition

A comparative assessment of deep learning models for day-ahead load forecasting: Investigating key accuracy drivers

Masked Multi-Step Probabilistic Forecasting for Short-to-Mid-Term Electricity Demand

Masked Multi-Step Multivariate Time Series Forecasting with Future Information