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A CNN-LSTM Hybrid Model Based Short-term Power Load Forecasting

2021 Power System and Green Energy Conference (PSGEC), 2021
Power load forecasting is always one of the most important research focuses in power systems, which can assist power companies to optimize dispatching and reduce cost.
Chang Ren, L. Jia, Zhangliang Wang
semanticscholar   +1 more source

Power load forecast system for Turkish electric market

2015 23nd Signal Processing and Communications Applications Conference (SIU), 2015
Forecasting the electric load demand in advance is very important in deregulated market conditions to give proper production, purchase, maintenance and investment decisions. Correct price forecasts also depend on accurate load prediction. In this study, effects of calendar, historical price and load data on short-term load forecast for Turkish ...
TAYŞİ, Ziya Cihan   +2 more
openaire   +2 more sources

A Hybrid LSTM-Transformer Model for Power Load Forecasting

IEEE Transactions on Smart Grid
This paper introduces a novel optimized hybrid model combining Long Short-Term Memory (LSTM) and Transformer deep learning architectures designed for power load forecasting.
Vasileios Pentsos   +3 more
semanticscholar   +1 more source

A Fast and Stable Forecasting Model to Forecast Power Load

International Journal of Pattern Recognition and Artificial Intelligence, 2015
As the traditional gray forecasting model GM(1, 1) has poor performance in forecasting the fast-growing power load, we present a chaotic co-evolutionary particle swarm optimization (CCPSO) algorithm, one with better efficiency than the PSO algorithm. Based on the GM(1, 1) model, the CCPSO algorithm is adopted to solve the values of parameters a and b ...
Li-Zhi Tan   +5 more
openaire   +1 more source

Industrial Power Load Forecasting Method Based on Reinforcement Learning and PSO-LSSVM

IEEE Transactions on Cybernetics, 2020
Influenced by many complex factors, it is very difficult to obtain high-performance industrial power load forecasting. The industrial power load forecasting is deeply studied by fusing some machine-learning methods for industrial enterprise power ...
Quanbo Ge   +6 more
semanticscholar   +1 more source

Regional Power Load Forecasting Based on PSOSVM

2018 IEEE 4th Information Technology and Mechatronics Engineering Conference (ITOEC), 2018
Power load forecasting is the basic work of power grid construction planning. Accurate load forecasting is a key requirement for modern power system planning and economic and safe operation. This paper first introduces the background and significance of power load forecasting, research status at home and abroad, and review of power load forecasting ...
Guoqiang Ji   +4 more
openaire   +1 more source

Power Load Forecasting Using a Refined LSTM

Proceedings of the 2019 11th International Conference on Machine Learning and Computing, 2019
The power load forecasting is based on historical energy consumption data of a region to forecast the power consumption of the region for a period of time in the future. Accurate forecasting can provide effective and reliable guidance for power construction and grid operation. This paper proposed a power load forecasting approach using a two LSTM (long-
Dedong Tang   +4 more
openaire   +1 more source

Heterogeneous ensemble for power load demand forecasting

2016 IEEE Region 10 Conference (TENCON), 2016
Electricity load demand is the fundamental building block for all utilities planning. The load demand data has nonlinear and non-stationary characteristics, which make it difficult to be predicted accurately by just computational intelligence or ensemble methods.
Aruna Charukesi Palaninathan   +2 more
openaire   +1 more source

Risk adjusted forecasting of electric power load

2014 American Control Conference, 2014
Load forecasting of energy demand is usually focused on mean values in related statistical models and ignores rare peak events. This paper provides Extreme Value Theory analysis of the peak events in electrical power load demand. It estimates risk of the peak events by combining forecast of the mean with extreme value modeling of distribution tail. The
Saahil Shenoy, Dimitry Gorinevsky
openaire   +1 more source

Research on Power Load Forecasting Method Based on LSTM Model

2020 IEEE 5th Information Technology and Mechatronics Engineering Conference (ITOEC), 2020
Power load forecasting is an important part of power system planning and the foundation of power system economic operation. It is very important for power system planning and operation.
Can Cui   +5 more
semanticscholar   +1 more source

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