Suchergebnisse - common short‐term load‐forecasting algorithm

Short-Term Load Forecasting in the Greek Power Distribution System: A Comparative Study of Gradient Boosting and Deep Learning Models.

Autoren: Shiblee, Md Fazle Hasan Koukaras, Paraskevas

Quelle: Energies (19961073); Oct2025, Vol. 18 Issue 19, p5060, 27p

Schlagwörter: LOAD forecasting (Electric power systems), DEEP learning, SUPERVISED learning, DEMAND forecasting, BOOSTING algorithms, ENERGY consumption, ELECTRIC power distribution grids

Short-term Electric Energy Load Forecasting of Ankara Region Using Artificial İntelligence Methods

Autoren: Tuğba AKMAN Cemal YILMAZ Yusuf SÖNMEZ

Quelle: Volume: 26, Issue: 4 1517-1531
Journal of Polytechnic
Politeknik Dergisi

Schlagwörter: Hybrid Forecast Model, Short-term load forecasting, power systems, artificial neural networks, genetic algorithm, hybrid forecast model, Engineering, Mühendislik, 0202 electrical engineering, electronic engineering, information engineering, 02 engineering and technology, 7. Clean energy

Dateibeschreibung: application/pdf

Zugangs-URL: https://avesis.gazi.edu.tr/publication/details/37b5ddf0-408f-444f-9df9-925138517821/oai
https://dergipark.org.tr/tr/pub/politeknik/issue/81603/911634

Enhanced Firefly Algorithm Inspired by Cell Communication Mechanism and Genetic Algorithm for Short-Term Electricity Load Forecasting.

Autoren: Ekedegwa, Anthony I. G. Ashigwuike, Evans Mohammed S. B., Abdullahi

Quelle: Communication in Physical Sciences; 2025, Vol. 12 Issue 3, p914-932, 19p

Schlagwörter: ARTIFICIAL neural networks, METAHEURISTIC algorithms, ENERGY demand management, CELL communication, ENERGY management, LOAD forecasting (Electric power systems)

Short-Term Electricity Load Forecasting Based on Complete Ensemble Empirical Mode Decomposition with Adaptive Noise and Improved Sparrow Search Algorithm–Convolutional Neural Network–Bidirectional Long Short-Term Memory Model.

Autoren: Qiu, Han Hu, Rong Chen, Jiaqing et al.

Quelle: Mathematics (2227-7390); Mar2025, Vol. 13 Issue 5, p813, 32p

Schlagwörter: CONVOLUTIONAL neural networks, LONG short-term memory, LEVY processes, SEARCH algorithms, PREDICTION models, LOAD forecasting (Electric power systems)

Very Short-Term Load Forecasting Model for Large Power System Using GRU-Attention Algorithm.

Autoren: Kim, Tae-Geun Yoon, Sung-Guk Song, Kyung-Bin

Quelle: Energies (19961073); Jul2025, Vol. 18 Issue 13, p3229, 22p

Schlagwörter: LOAD forecasting (Electric power systems), RECURRENT neural networks, INFORMATION measurement, ELECTRIC power production, MACHINE learning, FEATURE selection, ELECTRIC power systems

Geografische Kategorien: KOREA

Symmetry-Aware Short-Term Load Forecasting in Distribution Networks: A Synergistic Enhanced KMA-MVMD-Crossformer Framework.

Autoren: Zhao, Jingfeng Liu, Kunhua You, Qi et al.

Quelle: Symmetry (20738994); Sep2025, Vol. 17 Issue 9, p1512, 34p

Schlagwörter: LOAD forecasting (Electric power systems), POWER distribution networks, PATTERN perception, FEATURE extraction, FORECASTING, ALGORITHMS, STATISTICAL correlation

Optimized Hybrid Deep Learning Framework for Short-Term Power Load Interval Forecasting via Improved Crowned Crested Porcupine Optimization and Feature Mode Decomposition.

Autoren: Luo, Shucheng Meng, Xiangbin Pang, Xinfu et al.

Quelle: Algorithms; Oct2025, Vol. 18 Issue 10, p659, 27p

Schlagwörter: LOAD forecasting (Electric power systems), DEEP learning, GAUSSIAN mixture models, FORECASTING, OPTIMIZATION algorithms, FEATURE extraction, COMPUTER performance

VMD-SSA-LSTM-Based Cooling, Heating Load Forecasting, and Day-Ahead Coordinated Optimization for Park-Level Integrated Energy Systems.

Autoren: Zheng, Lintao Li, Dawei Zhou, Zezheng et al.

Quelle: Buildings (2075-5309); Nov2025, Vol. 15 Issue 21, p3920, 24p

Schlagwörter: LONG short-term memory, ENERGY consumption forecasting, SCHEDULING, DYNAMICAL systems, OPTIMIZATION algorithms, ENERGY management, RENEWABLE energy sources

Geografische Kategorien: TIANJIN (China)

Short-Term Power Load Forecasting Based on ICEEMDAN-GRA-SVDE-BiGRU and Error Correction Model

Autoren: Lianbing Li Ruixiong Jing Yanliang Zhang et al.

Quelle: IEEE Access, Vol 11, Pp 110060-110074 (2023)

Schlagwörter: error correction, ICEEMDAN, bidirectional gated recurrent unit (BiGRU), Differential evolutionary algorithm, short-term power load forecasting, GRA, Electrical engineering. Electronics. Nuclear engineering, TK1-9971

Zugangs-URL: https://doaj.org/article/ae6a138d865a4c55af23ea39270a6bed

基于全连接时空图的短期电力负荷预测方法. (Chinese)

Alternate Title: Short-term power load forecast method based on fully-connected spatio-temporal graph. (English)

Autoren: 徐智远 缪卓窈 龙 卓 et al.

Quelle: Journal of Electric Power Science & Technology; May2025, Vol. 40 Issue 3, p123-132, 10p

Schlagwörter: ELECTRIC power consumption forecasting, LOAD forecasting (Electric power systems), GRAPH neural networks, ALGORITHMS, ELECTRIC power systems, FORECASTING, SPATIOTEMPORAL processes, FEATURE extraction

Symmetry-Enhanced Locally Adaptive COA-ELM for Short-Term Load Forecasting.

Autoren: Dai, Shiyu Sun, Zhe Sun, Zhixin

Quelle: Symmetry (20738994); Aug2025, Vol. 17 Issue 8, p1335, 25p

Schlagwörter: EXTREME learning machines, POWER distribution networks, MARKET equilibrium, OPTIMIZATION algorithms, ELECTRIC power production forecasting, MATHEMATICAL optimization, ELECTRIC power system stability

Short-Term Electrical Load Forecasting Based on XGBoost Model.

Autoren: Beloev, Hristo Ivanov Saitov, Stanislav Radikovich Filimonova, Antonina Andreevna et al.

Quelle: Energies (19961073); Oct2025, Vol. 18 Issue 19, p5144, 32p

Schlagwörter: ELECTRICAL load, ELECTRIC power engineering, FORECASTING, BUSINESS losses, ECONOMIC efficiency, BOOSTING algorithms, DATA scrubbing

Geografische Kategorien: TATARSTAN (Russia)

Short-Term Power Load Prediction of VMD-LSTM Based on ISSA Optimization.

Autoren: Wu, Shuai Cai, Huafeng

Quelle: Applied Sciences (2076-3417); May2025, Vol. 15 Issue 9, p5037, 28p

Schlagwörter: LONG short-term memory, SEARCH algorithms, POWER series, ENTROPY, FORECASTING, LOAD forecasting (Electric power systems)

Integrated Energy Short-Term Adaptive Load Forecasting Method Based on Coupled Feature Extraction.

Autoren: Qin, Yidan Huang, Bonan Wang, Luyuan et al.

Quelle: Information; Nov2025, Vol. 16 Issue 11, p940, 17p

Schlagwörter: LOAD forecasting (Electric power systems), FEATURE extraction, INTERCONNECTED power systems, RENEWABLE energy sources, FORECASTING, STOCHASTIC processes, MACHINE learning, ENSEMBLE learning

Electricity load forecasting models based on LSTM and GRU with their bidirectional recurrent neural networks.

Alternate Title: Çift yönlü tekrarlayan sinir ağlarına sahip LSTM ve GRU tabanlı elektrik yükü tahmin modelleri. (Turkish)

Autoren: Alhashemi, Khalid Altinoz, Okkes Tolga

Quelle: Nigde Omer Halisdemir University Journal of Engineering Sciences / Niğde Ömer Halisdemir Üniversitesi Mühendislik Bilimleri Dergisi; 2025, Vol. 14 Issue 4, p1372-1384, 13p

Schlagwörter: LOAD forecasting (Electric power systems), LONG short-term memory, CLEAN energy, DEEP learning, ELECTRIC power system reliability, RECURRENT neural networks, ARTIFICIAL neural networks

A short-term load forecasting framework for air conditioning system based on model stacking.

Autoren: Liu, Tianjie Jiao, Wenling Huang, Zhiwei et al.

Quelle: Scientific Reports; 10/22/2025, Vol. 15 Issue 1, p1-17, 17p

Schlagwörter: AIR conditioning, MACHINE learning, FEATURE selection, PREDICTION models, ESTIMATION theory, DEMAND forecasting, ENSEMBLE learning

Short-Term Power Load Forecasting Based on the Quantum Genetic Algorithm Artificial Recurrent Memory Network.

Autoren: Zhang, Qian Zhou, Yang Huang, Sunhua et al.

Quelle: Electronics (2079-9292); Jun2025, Vol. 14 Issue 12, p2417, 19p

Schlagwörter: PREDICTION models, QUANTUM computing, POWER resources, SUPPLY & demand, RECURRENT neural networks, MICROGRIDS

Short-Term Load Forecasting Based on Pelican Optimization Algorithm and Dropout Long Short-Term Memories–Fully Convolutional Neural Network Optimization.

Autoren: Wang, Haonan Huang, Shan Yin, Yue et al.

Quelle: Energies (19961073); Dec2024, Vol. 17 Issue 23, p6115, 15p

Schlagwörter: CONVOLUTIONAL neural networks, LONG short-term memory, OPTIMIZATION algorithms, DATA mining, TIME series analysis

A hybrid short-term load forecasting method using CEEMDAN-RCMSE and improved BiLSTM error correction.

Autoren: Ning, Yi Liu, Meiyu Guo, Xifeng et al.

Quelle: Journal of Intelligent & Fuzzy Systems; Jul2025, Vol. 49 Issue 1, p61-78, 18p

Schlagwörter: LOAD forecasting (Electric power systems), LONG short-term memory, HILBERT-Huang transform, ELECTRONIC data processing, ELECTRIC power systems, FORECASTING methodology, FORECASTING

Improved Bacterial Foraging Optimization Algorithm with Machine Learning-Driven Short-Term Electricity Load Forecasting: A Case Study in Peninsular Malaysia.

Autoren: Zaini, Farah Anishah Sulaima, Mohamad Fani Razak, Intan Azmira Wan Abdul et al.

Quelle: Algorithms; Nov2024, Vol. 17 Issue 11, p510, 28p

Schlagwörter: ARTIFICIAL neural networks, OPTIMIZATION algorithms, SUPPORT vector machines, DEMAND forecasting, KERNEL functions, LOAD forecasting (Electric power systems)