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Short-term electric load forecasting using particle swarm optimization-based convolutional neural network
Short-term electric load forecasting is essential for the operation of power systems and the
power market, including economic dispatch, unit commitment, peak load shaving, load …
power market, including economic dispatch, unit commitment, peak load shaving, load …
A novel seasonal segmentation approach for day-ahead load forecasting
Day-ahead load forecasting plays a crucial role in operation and management of power
systems. Weather conditions have a significant impact on daily load profile, hence, it follows …
systems. Weather conditions have a significant impact on daily load profile, hence, it follows …
A hybrid short-term load forecasting approach for individual residential customer
This article proposes a hybrid method (HM) to improve the accuracy of short-term individual
residential load forecasting. The HM includes an ensemble model (EM), deep ensemble …
residential load forecasting. The HM includes an ensemble model (EM), deep ensemble …
A novel two-stage framework for mid-term electric load forecasting
Electric utilities and planners rely heavily on accurate mid-term load projections to effectively
schedule maintenance, coordinate load dispatch, and manage fuel reserves. Current …
schedule maintenance, coordinate load dispatch, and manage fuel reserves. Current …
[HTML][HTML] Performance analysis and comparison of various techniques for short-term load forecasting
Rapidly varying load demand is one of the greatest problems that distribution system
operators are now experiencing. Many researchers have been implemented the load …
operators are now experiencing. Many researchers have been implemented the load …
An adaptive hybrid ensemble with pattern similarity analysis and error correction for short-term load forecasting
Forecasting future electricity consumption is one of the critical processes for addressing
energy management and supply–demand balance in modern electrical systems. In this …
energy management and supply–demand balance in modern electrical systems. In this …
A distributed short-term load forecasting method in consideration of holiday distinction
L Luo, J Dong, Q Zhang, S Shi - Sustainable Energy, Grids and Networks, 2024 - Elsevier
Accurate forecasting of power load is essential for effective power system scheduling. This
paper presents a short-term load forecasting method utilizing the neural network architecture …
paper presents a short-term load forecasting method utilizing the neural network architecture …
ES-dRNN: a hybrid exponential smoothing and dilated recurrent neural network model for short-term load forecasting
Short-term load forecasting (STLF) is challenging due to complex time series (TS) which
express three seasonal patterns and a nonlinear trend. This article proposes a novel hybrid …
express three seasonal patterns and a nonlinear trend. This article proposes a novel hybrid …
High-resolution probabilistic load forecasting: A learning ensemble approach
High-resolution probabilistic load forecasting can comprehensively characterize both the
uncertainties and the dynamic trends of the future load. Such information is key to the …
uncertainties and the dynamic trends of the future load. Such information is key to the …
基于人工智能技术的新型电力系统负荷预测研究综述
**富佳， 王晓辉， 乔骥， 史梦洁， 蒲天骄 - **电机工程学报, 2023 - epjournal.csee.org.cn
在“双碳” 目标的驱动下, 构建以新能源为主体的新型电力系统是促进现代电力系统低碳转型发展
的重要前提与必然趋势. 由于复杂易变的多元负荷是新型电力系统的重要组成部分 …
的重要前提与必然趋势. 由于复杂易变的多元负荷是新型电力系统的重要组成部分 …