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A deep learning-based load forecasting algorithm for energy consumption monitoring system using dimension expansion
As a basic task in energy consumption monitoring system, load forecasting has great effects on system operation safety, generation costs and economic...
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Deep learning-driven hybrid model for short-term load forecasting and smart grid information management
Accurate power load forecasting is crucial for the sustainable operation of smart grids. However, the complexity and uncertainty of load, along with...
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Adaptive Forecasting of Extreme Electricity Load
Electricity load forecasting is a necessary capability for power system operators and electricity market participants. Both demand and supply...
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Short-Term Electrical Load Forecasting Based on Fuzzy Rough Set Feature Selection and Multi-kernel Extreme Learning Machine
As the complexity of power systems increases, accurate load forecasting becomes crucial. This paper proposes a method for short-term electrical load...
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Medium-long-term electricity load forecasting based on NSNP systems and attention mechanism
Accurate load forecasting can provide important information support for intelligent operation of power systems, it can assist the power grid to...
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Models of Load Forecasting
World is growing every day in many aspects. Economic growth, population growth, technical growth, etc., leads to a common factor: a never-ending...
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Short-term Power Load Forecasting Based on Phase Space Reconstruction and EMD-ELM
With the increasing complexity of the world energy structure, the uncertainty of the power system increases significantly, and the accuracy of the...
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Net load forecasting using different aggregation levels
In the electricity grid, constantly balancing the supply and demand is critical for the network’s stability and any expected deviations require...
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Short-Term Load Demand Forecasting Based on Weather and Influencing Factors Using Deep Neural Network Experts for Sustainable Development Goal 7
Due to the increasing essentiality of electricity in this modern world, its sustainable management is crucial for the economic development of a...
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Short Term Load Forecasting (STLF)
As storing electricity is expensive, it is better to be consumed when produced. Thus to make all the stakeholders such as producers, distributors,...
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Short-term aggregate electric vehicle charging load forecasting in diverse conditions with minimal data using transfer and meta-learning
The proliferation of electric vehicles (EVs) necessitates accurate EV charging load forecasting for demand-side management and electric-grid...
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Fuzzy Inference Model for Short-Term Load Forecasting
For planning and operation of an energy management system, load forecasting (LF) is essential. For smooth power system operation (PS), LF enhances...
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Short-term load forecasting using time series clustering
Short-term load forecasting plays a major role in energy planning. Its accuracy has a direct impact on the way power systems are operated and...
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Short time load forecasting for Urmia city using the novel CNN-LTSM deep learning structure
In the present time, electricity stands as one of the most fundamental needs within human societies. This is evident in the fact that all industrial...
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Pinball-Huber boosted extreme learning machine regression: a multiobjective approach to accurate power load forecasting
Power load data frequently display outliers and an uneven distribution of noise. To tackle this issue, we present a forecasting model based on an...
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A data decomposition and attention mechanism-based hybrid approach for electricity load forecasting
An accurate and reliable prediction of future energy patterns is of utmost significance for the smooth operation of several related activities such...
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Core Concepts and Methods in Load Forecasting With Applications in Distribution Networks
This comprehensive open access book enables readers to discover the essential techniques for load forecasting in electricity networks, particularly...
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Short-term forecasting electricity load by long short-term memory and reinforcement learning for optimization of hyper-parameters
Electricity load forecasting is an essential operation of the power system. Deep learning is used to improve accurate electricity load forecasting....
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Deep Learning Techniques for Load Forecasting
Electricity load dominates energy consumption and greenhouse gas emissions. There are increasing concerns about climate change and the need to...
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A novel gated dual convolutional neural network model with autoregressive method and attention mechanism for probabilistic load forecasting
Accurate load forecasting is prime in the electric power industry, while the complexity and variability of the load data make it a challenging...
