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Short-term load forecasting method based on fuzzy optimization combined model of load feature recognition
With the continuous development of smart grid construction and the gradual improvement of power market operation mechanisms, the importance of power...
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Fuzzy support vector regressions for short-term load forecasting
The accurate short-term point and probabilistic load forecasts are critically important for efficient operation of power systems and electricity...
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Transformer training strategies for forecasting multiple load time series
In the smart grid of the future, accurate load forecasts on the level of individual clients can help to balance supply and demand locally and to...
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Statistical Learning Tools for Electricity Load Forecasting
This monograph explores a set of statistical and machine learning tools that can be effectively utilized for applied data analysis in the context of...
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Multiplicative neuron models for very short-term load forecasting
Load forecasting has always been a crucial component of operational and managerial aspect of efficient power system planning. Since there are several...
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Advances in Deep Learning Techniques for Short-term Energy Load Forecasting Applications: A Review
Today, the majority of the leading power companies place a significant emphasis on forecasting the electricity load in the balance of power and...
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Knowledge-Data Fusion Model for Multivariate Load Short-Term Forecasting of Integrated Energy System
The short-term forecasting of multiple loads is crucial for the optimization and scheduling of integrated energy system (IES). However, the load...
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The effect of electricity consumption determinants in household load forecasting models
Usually, household electricity consumption fluctuates, often driven by several electrical consumption determinants such as income, household size,...
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Probabilistic load forecasting based on quantile regression parallel CNN and BiGRU networks
In the dynamic smart grid landscape, accurate probabilistic forecasting of electric load is critical. This paper presents a novel 24-hour-ahead...
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Graph Neural Network-Based Short‑Term Load Forecasting with Temporal Convolution
An accurate short-term load forecasting plays an important role in modern power system’s operation and economic development. However, short-term load...
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Online SARIMA applied for short-term electricity load forecasting
Short-term Load Forecasting (STLF) plays a crucial role in balancing the supply and demand of load dispatching operations and ensures stability for...
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SP2LSTM: a patch learning-based electrical load forecasting for container terminal
Short-term electricity load forecasting plays a crucial role in modern container terminal. In this work, we design a short-term forecasting approach...
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Short-term load forecasting system based on sliding fuzzy granulation and equilibrium optimizer
Short-term electricity load forecasting is critical and challenging for scheduling operations and production planning in modern power management...
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Urban Gas Load Forecasting Based on Time Series Methods
Accurate forecasting of natural gas load forecasting is of great practical significance to balance supply and demand of gas system. Load forecasting...
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Enhancing source domain availability through data and feature transfer learning for building power load forecasting
During the initial phases of operation following the construction or renovation of existing buildings, the availability of historical power usage...
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Load Forecasting Using Different Techniques
Load forecasting uses previous data from the electrical system to predict future electric load. For the planning and operation of the utility,...
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Short-term load analysis and forecasting using stochastic approach considering pandemic effects
The COVID-19 pandemic and its containment have changed the pattern of electricity load. Hence, accurate forecasting of load for shorter interval of...
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Short-Term Load Forecasting of Microgrid Based on TVFEMD-LSTM-ARMAX Model
The accuracy of short-term load forecasting in microgrids is crucial for their safe and economic operation. Microgrids have higher unpredictability...
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Electricity Load Forecasting Using LSTM for Household Usage
For the electrical industry to run smoothly, load projections are crucial. Electricity demand varies over time, short-term energy forecasting is very...
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Energy load forecasting: one-step ahead hybrid model utilizing ensembling
In the light of the adverse effects of climate change, data analysis and Machine Learning (ML) techniques can provide accurate forecasts, which...
