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Weijian Huang, Qi Song and Yuan Huang
Short-term power load forecasting is of great significance for the reliable and safe operation of power systems. In order to improve the accuracy of short-term load forecasting, for the problems of random fluctuation in load and the complexity of load-in...
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Dongxiao Niu and Shuyu Dai
As an important part of power system planning and the basis of economic operation of power systems, the main work of power load forecasting is to predict the time distribution and spatial distribution of future power loads. The accuracy of load forecasti...
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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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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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Rui Zhou, Jiyin Cao, Gang Zhang, Xia Yang and Xinyu Wang
High heat load on diesel engines is a main cause of ship failure, which can lead to ship downtime and pose a risk to personal safety and the environment. As such, predictive detection and maintenance measures are highly important. During the operation of...
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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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Carla Sahori Seefoo Jarquin, Alessandro Gandelli, Francesco Grimaccia and Marco Mussetta
Understanding how, why and when energy consumption changes provides a tool for decision makers throughout the power networks. Thus, energy forecasting provides a great service. This research proposes a probabilistic approach to capture the five inherent ...
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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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Zezheng Zhao, Chunqiu Xia, Lian Chi, Xiaomin Chang, Wei Li, Ting Yang and Albert Y. Zomaya
From the perspective of energy providers, accurate short-term load forecasting plays a significant role in the energy generation plan, efficient energy distribution process and electricity price strategy optimisation. However, it is hard to achieve a sat...
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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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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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Liwen Xu, Chengdong Li, Xiuying Xie and Guiqing Zhang
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Cruz E. Borges, Yoseba K. Penya, Iván Fernández, Juan Prieto and Oscar Bretos
Short-term load forecasting (STLF) in buildings differs from its broader counterpart in that the load to be predicted does not seem to be stationary, seasonal and regular but, on the contrary, it may be subject to sudden changes and variations on its con...
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Milo? Bo?ic, Milo? Stojanovic, Zoran Stajic and Dragan Tasic
In the deregulated energy market, the accuracy of load forecasting has a significant effect on the planning and operational decision making of utility companies. Electric load is a random non-stationary process influenced by a number of factors which mak...
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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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Nima Amjady and Farshid Keynia
Short-term load forecast (STLF) is an important operational function in both regulated power systems and deregulated open electricity markets. However, STLF is not easy to handle due to the nonlinear and random-like behaviors of system loads, weather con...
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Qingliang Xiong, Mingping Liu, Yuqin Li, Chaodan Zheng and Suhui Deng
Due to difficulties with electric energy storage, balancing the supply and demand of the power grid is crucial for the stable operation of power systems. Short-term load forecasting can provide an early warning of excessive power consumption for utilitie...
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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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Yaju Rajbhandari, Anup Marahatta, Bishal Ghimire, Ashish Shrestha, Anand Gachhadar, Anup Thapa, Kamal Chapagain and Petr Korba
Short-term electricity demand forecasting is one of the best ways to understand the changing characteristics of demand that helps to make important decisions regarding load flow analysis, preventing imbalance in generation planning, demand management, an...
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