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Nhung Nguyen Hong and Huy Nguyen Duc
In recent years, with the rapid increase in renewable energy sources (RESs), a Virtual Power Plant (VPP) concept has been developed to integrate many small-scale RESs, energy storage systems (ESSs), and customers into a unified agent in the electricity m...
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Yun-Sheng Tsai, Chi-Wen Chen, Cheng-Chien Kuo and Hung-Cheng Chen
In recent years, the escalating electricity demand in Taiwan has heightened the prominence and discourse surrounding the issue of power supply. With the enactment of the European climate law, global commitment to achieving net-zero emissions has gained m...
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Shih-Lun Fang, Yi-Shan Lin, Sheng-Chih Chang, Yi-Lung Chang, Bing-Yun Tsai and Bo-Jein Kuo
The reference evapotranspiration (ET0) information is crucial for irrigation planning and water resource management. While the Penman-Monteith (PM) equation is widely recognized for ET0 calculation, its reliance on numerous meteorological parameters cons...
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Lisa Pierotti, Cristiano Fidani, Gianluca Facca and Fabrizio Gherardi
Variations in the CO2 dissolved in water springs have long been observed near the epicenters of moderate and strong earthquakes. In a recent work focused on data collected during the 2017?2021 period from a monitoring site in the Northern Apennines, Ital...
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Peihua Xu, Maoyuan Zhang, Zhenhong Chen, Biqiang Wang, Chi Cheng and Renfeng Liu
Due to the increasing proportion of wind power connected to the grid, day-ahead wind power prediction plays a more and more important role in the operation of the power system. This paper proposes a day-ahead wind power short-term prediction model based ...
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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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Nika Nizharadze, Arash Farokhi Soofi and Saeed Manshadi
Predicting the price gap between the day-ahead Market (DAM) and the real-time Market (RTM) plays a vital role in the convergence bidding mechanism of Independent System Operators (ISOs) in wholesale electricity markets. This paper presents a model to pre...
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Daniel Manfre Jaimes, Manuel Zamudio López, Hamidreza Zareipour and Mike Quashie
This paper proposes a new hybrid model to forecast electricity market prices up to four days ahead. The components of the proposed model are combined in two dimensions. First, on the ?vertical? dimension, long short-term memory (LSTM) neural networks and...
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Michael Wood, Emanuele Ogliari, Alfredo Nespoli, Travis Simpkins and Sonia Leva
Optimal behind-the-meter energy management often requires a day-ahead electric load forecast capable of learning non-linear and non-stationary patterns, due to the spatial disaggregation of loads and concept drift associated with time-varying physics and...
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Seyed Mahdi Miraftabzadeh, Cristian Giovanni Colombo, Michela Longo and Federica Foiadelli
Climate change and global warming drive many governments and scientists to investigate new renewable and green energy sources. Special attention is on solar panel technology, since solar energy is considered one of the primary renewable sources and solar...
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