Boiler Load Forecasting of CHP Plant Based on Attention Mechanism and Deep Neural Network
Shanghai Jiaotong Daxue xuebao, 2023 Accurate boiler load forecasting of cogeneration units plays a direct role in production management and dispatching of power plants. A long-term load forecasting model of combined heat and power (CHP) based on attention mechanism and the deep convolution
WAN Anping, YANG Jie, MIAO Xu, CHEN Ting, ZUO Qiang, LI Ke
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Local Short Term Electricity Load Forecasting: Automatic Approaches
, 2017 Short-Term Load Forecasting (STLF) is a fundamental component in the efficient management of power systems, which has been studied intensively over the past 50 years. The emerging development of smart grid technologies is posing new challenges as well as
Bianchi, Filippo Maria +2 more
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NEW APPROACHES FOR VERY SHORT-TERM STEADY-STATE ANALYSIS OF AN ELECTRICAL DISTRIBUTION SYSTEM WITH WIND FARMS [PDF]
, 2010 Distribution networks are undergoing radical changes due to the high level of penetration of dispersed generation. Dispersed generation systems require particular attention due to their incorporation of uncertain energy sources, such as wind farms, and ...
Angela Russo +9 more
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TPE-Based Boosting Short-Term Load Forecasting Method
Shanghai Jiaotong Daxue xuebaoShort-term load forecasting is generally applied in power system real-time dispatching and day-ahead generation planning, which is of great significance for power system economic dispatching and safe operation of the system. Many researches on short-term
LUO Min, YANG Jinfeng, YU Hui, LAI Yuchen, GUO Yangyun, ZHOU Shangli, XIANG Rui, TONG Xing, CHEN Xiao
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Short-Term Load Forecasting: The Similar Shape Functional Time Series Predictor [PDF]
, 2012 We introduce a novel functional time series methodology for short-term load forecasting. The prediction is performed by means of a weighted average of past daily load segments, the shape of which is similar to the expected shape of the load segment to be
Paparoditis, Efstathios +1 more
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Short-Term Load Forecasting Based on Multi-Scale Ensemble Deep Learning Neural Network
IEEE Access, 2023 High-precision load forecasting is crucial for the power system planning and electricity market transactions. Recently, deep learning models have been widely used due to their powerful data mining capabilities. However, the existing research mainly focus
Qin Shen +5 more
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Jaringan Syaraf Tiruan Sebagai Metode Peramalan Beban Listrik Harian Di PT. Pismatex Pekalongan [PDF]
, 2014 Load electricity forecasting of industry can provide an information support to the Top Management and other stakeholders in terms of estimating and monitoring the power requirements and effort in providing it. With the artificial neural network method as
Assaffat, L. (Luqman) +1 more
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Improving Short-Term Electricity Price Forecasting Using Day-Ahead LMP with ARIMA Models
, 2018 Short-term electricity price forecasting has become important for demand side management and power generation scheduling. Especially as the electricity market becomes more competitive, a more accurate price prediction than the day-ahead locational ...
Miller, Carol +3 more
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Energies, 2023 With the increasing demand of the power industry for load forecasting, improving the accuracy of power load forecasting has become increasingly important.
Wenhui Zeng +6 more
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Studi Peramalan Beban Rata – Rata Jangka Pendek Menggunakan Metoda Autoregressive Integrated Moving Average (Arima [PDF]
, 2017 Forecasting. Plans, power plants ,. Electricity needs are increasingly changing daily, so the State Electricity Company (PLN) as a provider of energy must be able to predict daily electricity needs. Short-term forecasting is the prediction of electricity
Jurnal, R. T. (Redaksi)
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