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Anik Baul, Gobinda Chandra Sarker, Prokash Sikder, Utpal Mozumder and Ahmed Abdelgawad
Short-term load forecasting (STLF) plays a crucial role in the planning, management, and stability of a country?s power system operation. In this study, we have developed a novel approach that can simultaneously predict the load demand of different regio...
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Tiankai Yang, Zhenzhong Sun, Yongliang Liang and Lichuan Liu
With the rapid development of global trade, a large number of goods and resources are imported and exported via seaports. Multiple thermal loads and renewable energy merge into seaports, making the energy supply and demand structure increasingly complex....
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Kaijie Huang, Chengjun Qiu, Wenbin Xie, Wei Qu, Yuan Zhuang, Kaixuan Chen, Jiaqi Yan, Gao Huang, Chao Zhang and Jianfeng Hao
The paper presents a wind?photovoltaic-thermal hybrid-driven two-stage humidification and dehumidification desalination system for remote island regions lacking access to electricity and freshwater resources. By conducting an analysis of the wind and sol...
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Leonce W. Tokam and Sanoussi S. Ouro-Djobo
Without an appropriate monitoring system, the condition/state of electrical appliances/devices in operation in households cannot be fully assessed, resulting in uncontrolled expenses. The purpose of load monitoring techniques is to save electricity consu...
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George Stamatellos and Tassos Stamatelos
In spite of the significant developments in machine learning methods employed for short-term electrical load forecasting on a Country level, the complexity and diversity of the problem points to the need for investing more research effort in the selectio...
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Songtao Huang, Jun Shen, Qingquan Lv, Qingguo Zhou and Binbin Yong
Electricity load forecasting has seen increasing importance recently, especially with the effectiveness of deep learning methods growing. Improving the accuracy of electricity load forecasting is vital for public resources management departments. Traditi...
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Jie Cao, Ru-Xuan Zhang, Chao-Qiang Liu, Yuan-Bo Yang and Chin-Ling Chen
Daily load forecasting is the basis of the economic and safe operation of a power grid. Accurate prediction results can improve the matching of microgrid energy storage capacity allocation. With the popularization of smart meters, the interaction between...
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Daniel D. Campo-Ossa, Cesar A. Vega Penagos, Oscar D. Garzon and Fabio Andrade
This document presents the modeling of load profile consumption for Low-and-Moderate-Income (LMI) communities in the Caribbean Islands, as well as an assessment of the solar-rooftop energy potential. In this work, real data, together with synthetic and e...
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Zuoxin Wang and Xiaohu Zhao
Most current non-intrusive load monitoring methods focus on traditional load characteristic analysis and algorithm optimization, lack knowledge of users? electricity consumption behavior habits, and have poor accuracy. We propose a novel attention-guided...
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Ning Jin, Linlin Song, Gabriel Jing Huang and Ke Yan
Residential electricity consumption forecasting plays a crucial role in the rational allocation of resources reducing energy waste and enhancing the grid-connected operation of power systems. Probabilistic forecasting can provide more comprehensive infor...
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