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- W4383747712 abstract "Based on the carbon emissions requirements of global climate change for carbon emissions-constrained enterprises, this paper proposes a multi-energy scheduling strategy for carbon emissions-constrained enterprises. First, based on the production data of the enterprise, the energy-output model and the energy-carbon model can be established respectively by using the neural network. Then, based on the above two models, the model predictive control algorithm is used to predict the output and carbon emissions in the future, and establish an energy scheduling optimization function. Finally, use the particle swarm algorithm to solve the optimal energy scheduling scheme. The energy optimization scheduling strategy proposed in this paper can not only complete the production task, but also minimize carbon emissions and achieve the unification of economic and ecological benefits." @default.
- W4383747712 created "2023-07-11" @default.
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- W4383747712 date "2023-05-12" @default.
- W4383747712 modified "2023-10-15" @default.
- W4383747712 title "Multi-Energy Scheduling Strategy for Carbon Emissions-Constrained Enterprises Based on Model Predictive Control and Particle Swarm Optimization" @default.
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- W4383747712 doi "https://doi.org/10.1109/cieec58067.2023.10165816" @default.
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