Suchergebnisse - common short‐term load‐forecasting algorithm

Short-term power-forecasting method of distributed PV power system for consideration of its effects on load forecasting von Liu, Yu, Li, Zhi, Bai, Kai, Zhang, Zhaoguang, Lu, Xining, Zhang, Xiaomeng

“… , and load data reconfiguration method, by using common short-term load-forecasting algorithm …”
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An integrated federated learning algorithm for short-term load forecasting von Yang, Yang, Wang, Zijin, Zhao, Shangrui, Wu, Jinran

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Short-term ANN load forecasting from limited data using generalization learning strategies von Chan, Zeke S.H., Ngan, H.W., Rad, A.B., David, A.K., Kasabov, N.

“… The emergence of the new competitive electricity market environment has made short-term load forecasting a more complex task, owing to the effect of marketers …”
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A hybrid forecasting model based on date-framework strategy and improved feature selection technology for short-term load forecasting von Jiang, Ping, Liu, Feng, Song, Yiliao

“… However, common FS technologies applied for Short-term load forecasting (STLF) ignore to select date information of the observed series as feature candidates and pay …”
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Graph Neural Network-Based Short‑Term Load Forecasting with Temporal Convolution von Sun, Chenchen, Ning, Yan, Shen, Derong, Nie, Tiezheng

“… An accurate short-term load forecasting plays an important role in modern power system’s operation and economic development …”
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Multi-Gradient-Descent Federated Learning With Parity for Cooperative Short-Term Load Forecasting von Wang, Haijin, Xing, Shuangshuang, Si, Caomingzhe, Pan, Zibin, Zhao, Junhua, Qiu, Jing, Dong, Zhaoyang

“… Short-term load forecasting (STLF) is essential in power system research. In scenarios where multiple distribution system operators are involved in cooperative …”
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A Hybrid Short-Term Load Forecasting Model Based on Improved Fuzzy C-Means Clustering, Random Forest and Deep Neural Networks von Liu, Fu, Dong, Tian, Hou, Tao, Liu, Yun

“… Short-term load forecasting (STLF) plays an important role in the secure and reliable operation of the electric power system …”
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An adaptive hybrid fractal model for short-term load forecasting in power systems von Li, Xiaolan, Zhou, Jun

“… •Short-term load forecasting (STLF) of power loads involves fractal features, due to complexity of power systems …”
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A Short-Term Power Load Forecasting Method Using CNN-GRU with an Attention Mechanism von Hua, Qingbo, Fan, Zengliang, Mu, Wei, Cui, Jiqiang, Xing, Rongxin, Liu, Huabo, Gao, Junwei

“… This paper proposes a short-term electric load forecasting method combining convolutional neural networks and gated recurrent units with an attention mechanism …”
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Clustering Informed MLP Models for Fast and Accurate Short-Term Load Forecasting von Arvanitidis, Athanasios Ioannis, Bargiotas, Dimitrios, Daskalopulu, Aspassia, Kontogiannis, Dimitrios, Panapakidis, Ioannis P., Tsoukalas, Lefteri H.

“… Fast and highly accurate Short-Term Load Forecasting (STLF) is critical for the daily operation of power plants, and state-of-the-art approaches for it involve …”
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Short-term Power Load Forecasting Based on Improved BP Neural Network from Genetic Algorithm and Simulated Annealing Algorithm von Zhong, Licheng, Wang, Yulu

“… In this paper, GA algorithm and SA algorithm are used to modify the weights of BP neural network, and a short-term load forecasting model, namely BP-GSA model, is established …”
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Short-Term Power Load Forecasting Based on ICEEMDAN-GRA-SVDE-BiGRU and Error Correction Model von Li, Lianbing, Jing, Ruixiong, Zhang, Yanliang, Wang, Lanchao, Zhu, Le

“… The significance of short-term power load forecasting extends to grid dispatching and future planning …”
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Weather station selection for electric load forecasting von Hong, Tao, Wang, Pu, White, Laura

“… (s) plays a vital role in electric load forecasting. Nevertheless, minimal research efforts have been devoted to weather station selection …”
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Industrial Ultra-Short-Term Load Forecasting With Data Completion von Jiang, Haoyu, Wu, Angjian, Wang, Bo, Xu, Peizhe, Yao, Gang

“… Accurate and efficient ultra-short-term load forecasting is crucial for industrial power users to have stabilized and optimized operations …”
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Enhancing Load Forecasting Accuracy in Smart Grids: A Novel Parallel Multichannel Network Approach Using 1D CNN and Bi‐LSTM Models von Hasanat, Syed Muhammad, Younis, Rehmana, Alahmari, Saad, Ejaz, Muhammad Talha, Haris, Muhammad, Yousaf, Hamza, Watara, Sadia, Ullah, Kaleem, Ullah, Zahid

“… Load forecasting plays a pivotal role in the efficient energy management of smart grid …”
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Hyperparameter Tuning of Load-Forecasting Models Using Metaheuristic Optimization Algorithms—A Systematic Review von Mumtahina, Umme, Alahakoon, Sanath, Wolfs, Peter

“… This article presents a complete framework for short-term load forecasting using metaheuristic algorithms …”
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Short-Term Power Load Forecasting Model Based on t-SNE Dimension Reduction Visualization Analysis, VMD and LSSVM Improved with Chaotic Sparrow Search Algorithm Optimization von Wang, Lingyun, Tian, Tian, Xu, Honglei, Tong, Huamin

“… The stable operation of power system has the strong constraint of load balance. Accurate power load forecasting is of great significance in ensuring power system planning and reliable and economic operation …”
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A combined deep learning application for short term load forecasting von Ozer, Ilyas, Efe, Serhat Berat, Ozbay, Harun

“… Nowadays, the electricity prediction based on sensor data has become quite common with the increasing popularity of smart meter applications …”
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Short-Term Power Load Forecasting Based on Reduction of Meteorological Data Dimensionality and Hybrid Deep Learning von Shen, Hongtao, Li, Fei, Shi, Lun, Sun, Shengbo, Yang, Zhenning, Yang, Ting

“… Accurate short-term load forecasting can provide guidance for the dispatching operation of power grids by predicting the required power loads …”
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A new method for short-term load forecasting based on weighted fusion of base models von Bian, Kai, Xu, Jing, Wang, Haohao, Ding, Junfeng

“… The setting and dynamic adjustment of their operating parameters depend heavily on power load forecasting …”
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