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Jiaan Zhang, Chenyu Liu and Leijiao Ge
The large fluctuations in charging loads of electric vehicles (EVs) make short-term forecasting challenging. In order to improve the short-term load forecasting performance of EV charging load, a corresponding model-based multi-channel convolutional neur...
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Venkataramana Veeramsetty, Dongari Rakesh Chandra, Francesco Grimaccia and Marco Mussetta
Electrical load forecasting study is required in electric power systems for different applications with respect to the specific time horizon, such as optimal operations, grid stability, Demand Side Management (DSM) and long-term strategic planning. In th...
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Manuel Lopez-Martin, Antonio Sanchez-Esguevillas, Luis Hernandez-Callejo, Juan Ignacio Arribas and Belen Carro
This work brings together and applies a large representation of the most novel forecasting techniques, with origins and applications in other fields, to the short-term electric load forecasting problem. We present a comparison study between different cla...
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Namrye Son, Seunghak Yang and Jeongseung Na
Forecasting domestic and foreign power demand is crucial for planning the operation and expansion of facilities. Power demand patterns are very complex owing to energy market deregulation. Therefore, developing an appropriate power forecasting model for ...
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Eduardo Caro and Jesús Juan
In any electric power system, the Transmission System Operator (TSO) requires the use of short-term load forecasting algorithms. These predictions are essential for appropriate planning of the energy resources and optimal coordination for the generation ...
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Gwiman Bak and Youngchul Bae
The most important thing to operate a power system is that the power supply should be close to the power demand. In order to predict the amount of electric power transaction (EPT), it is important to choose and decide the variable and its starting date. ...
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Peng Liu, Peijun Zheng and Ziyu Chen
Accurate short-term electric load forecasting is significant for the smart grid. It can reduce electric power consumption and ensure the balance between power supply and demand. In this paper, the Stacked Denoising Auto-Encoder (SDAE) is adopted for shor...
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Accurate short-term electric load forecasting is significant for the smart grid. It can reduce electric power consumption and ensure the balance between power supply and demand. In this paper, the Stacked Denoising Auto-Encoder (SDAE) is adopted for shor...
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Aqdas Naz, Muhammad Umar Javed, Nadeem Javaid, Tanzila Saba, Musaed Alhussein and Khursheed Aurangzeb
A Smart Grid (SG) is a modernized grid to provide efficient, reliable and economic energy to the consumers. Energy is the most important resource in the world. An efficient energy distribution is required as smart devices are increasing dramatically. The...
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Pan Duan, Kaigui Xie, Tingting Guo and Xiaogang Huang
This paper presents a new combined method for the short-term load forecasting of electric power systems based on the Fuzzy c-means (FCM) clustering, particle swarm optimization (PSO) and support vector regression (SVR) techniques. The training samples us...
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Pan Duan, Kaigui Xie, Tingting Guo and Xiaogang Huang
This paper presents a new combined method for the short-term load forecasting of electric power systems based on the Fuzzy c-means (FCM) clustering, particle swarm optimization (PSO) and support vector regression (SVR) techniques. The training samples us...
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Juncheng Zhu, Zhile Yang, Monjur Mourshed, Yuanjun Guo, Yimin Zhou, Yan Chang, Yanjie Wei and Shengzhong Feng
Load forecasting is one of the major challenges of power system operation and is crucial to the effective scheduling for economic dispatch at multiple time scales. Numerous load forecasting methods have been proposed for household and commercial demand, ...
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Yunyan Li, Yuansheng Huang and Meimei Zhang
Accurate and stable prediction of short-term load for electric vehicle charging stations is of great significance in ensuring economical and safe operation of electric vehicle charging stations and power grids. In order to improve the accuracy and stabil...
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Alex Sleiman and Wencong Su
The power system has undergone significant growth and faced considerable challenges in recent decades, marked by the surge in energy demand and advancements in smart grid technologies, including solar and wind energies, as well as the widespread adoption...
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Venkataramana Veeramsetty, Modem Sai Pavan Kumar and Surender Reddy Salkuti
Short-term electric power load forecasting is a critical and essential task for utilities in the electric power industry for proper energy trading, which enables the independent system operator to operate the network without any technical and economical ...
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Ahmad Mohsenimanesh, Evgueniy Entchev and Filip Bosnjak
Forecasting the aggregate charging load of a fleet of electric vehicles (EVs) plays an important role in the energy management of the future power system. Therefore, accurate charging load forecasting is necessary for reliable and efficient power system ...
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Maher Selim, Ryan Zhou, Wenying Feng and Peter Quinsey
Building safe, reliable, fully automated energy smart grid systems requires a trustworthy electric load forecasting system. Recent work has shown the efficacy of Long Short-Term Memory neural networks in energy load forecasting. However, such predictions...
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The aim of this study is to analyze the perception of the meaning of sustainability in the food sector. A sample of 268 University students belonging to the Millennial generation was identified and a survey was carried out to assess the interaction betwe...
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Weide Li, Demeng Kong and Jinran Wu
Electric load forecasting plays an important role in electricity markets and power systems. Because electric load time series are complicated and nonlinear, it is very difficult to achieve a satisfactory forecasting accuracy. In this paper, a hybrid mode...
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Yanbing Lin, Hongyuan Luo, Deyun Wang, Haixiang Guo and Kejun Zhu
The experience with deregulated electricity market has shown the increasingly important role of short-term electric load forecasting in the energy producing and scheduling. However, because of nonlinear, stochastic and nonstable characteristics associate...
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