Turnitin
降AI改写
早检测系统
早降重系统
Turnitin-UK版
万方检测-期刊版
维普编辑部版
Grammarly检测
Paperpass检测
checkpass检测
PaperYY检测
[HTML][HTML] Aggregated demand-side energy flexibility: A comprehensive review on characterization, forecasting and market prospects
Existing grids have been designed with traditional large centralized generation in mind;
however, with the ever-increasing utilization of renewable distributed energy resources, the …
however, with the ever-increasing utilization of renewable distributed energy resources, the …
Industry 4.0 and demand forecasting of the energy supply chain: A literature review
The number of publications in demand forecasting of the energy supply chain augmented
meaningfully due to the 2008 global financial crisis and its consequence on the global …
meaningfully due to the 2008 global financial crisis and its consequence on the global …
Let's wait awhile: How temporal workload shifting can reduce carbon emissions in the cloud
Depending on energy sources and demand, the carbon intensity of the public power grid
fluctuates over time. Exploiting this variability is an important factor in reducing the emissions …
fluctuates over time. Exploiting this variability is an important factor in reducing the emissions …
[HTML][HTML] Blockchain based decentralized local energy flexibility market
Large-scale deployment of renewable energy sources brings new challenges for smart grid
management requiring the development of decentralized solutions and active participation …
management requiring the development of decentralized solutions and active participation …
Virtual power plant optimization in smart grids: A narrative review
Virtual power plants (VPPs) are promising solutions to address the decarbonization and
energy efficiency goals in the smart energy grid. They assume the coordination of local …
energy efficiency goals in the smart energy grid. They assume the coordination of local …
[HTML][HTML] A comparative assessment of deep learning models for day-ahead load forecasting: Investigating key accuracy drivers
Short-term load forecasting (STLF) is vital for the effective and economic operation of power
grids and energy markets. However, the non-linearity and non-stationarity of electricity …
grids and energy markets. However, the non-linearity and non-stationarity of electricity …
In search of deep learning architectures for load forecasting: A comparative analysis and the impact of the Covid-19 pandemic on model performance
In power grids, short-term load forecasting (STLF) is crucial as it contributes to the
optimization of their reliability, emissions, and costs, while it enables the participation of …
optimization of their reliability, emissions, and costs, while it enables the participation of …
[HTML][HTML] A tri-layer optimization framework for day-ahead energy scheduling based on cost and discomfort minimization
Over the past few decades, industry and academia have made great strides to improve
aspects related with optimal energy management. These include better ways for efficient …
aspects related with optimal energy management. These include better ways for efficient …
A profit driven optimal scheduling of virtual power plants for peak load demand in competitive electricity markets with machine learning based forecasted generations
The operation of generating resources connected to VPPs during peak demand is crucial for
determining the economic sustainability of participants in a competitive electricity market and …
determining the economic sustainability of participants in a competitive electricity market and …
[HTML][HTML] Blockchain-based distributed federated learning in smart grid
The participation of prosumers in demand-response programs is essential for the success of
demand-side management in renewable-powered energy grids. Unfortunately, the …
demand-side management in renewable-powered energy grids. Unfortunately, the …