Quantifying the Influence and Projections of Zero-Carbon Smart Park Infrastructures on Urban Electricity Consumption

In the pursuit of China's ambitious goals of achieving carbon neutrality and peak carbon emissions, the establishment of zero-carbon smart park stands out as a pivotal initiative. This study uses the panel regression model and the radial basis neural network model to study the relationship betw...

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Bibliographic Details
Published in2024 8th International Conference on Green Energy and Applications (ICGEA) pp. 235 - 241
Main Authors Hong, Fubin, Wu, Kaibin, Xu, Huiming, Qiu, Zejing
Format Conference Proceeding
LanguageEnglish
Published IEEE 14.03.2024
Subjects
Carbon neutral
Electricity
electricity consumption
Energy efficiency
Neural networks
panel data
Planning
Power demand
Predictive models
radial basis function neural network model
zero-carbon smart park
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Summary:In the pursuit of China's ambitious goals of achieving carbon neutrality and peak carbon emissions, the establishment of zero-carbon smart park stands out as a pivotal initiative. This study uses the panel regression model and the radial basis neural network model to study the relationship between these smart park and urban electricity consumption. We find that, for one thing, with the construction of zero-carbon smart park, urban electricity consumption increases 73.36, which exerts a significant and positive impact on urban electricity consumption; for another thing, the trained Radial Basis Neural Network model exhibits minimal error and robust predictive capabilities for forecasting urban electricity consumption. These results highlight the importance of constructing zero-carbon smart urban zones to manage and improve how cities consume energy, aligning with China's broader goals for sustainability.
DOI:10.1109/ICGEA60749.2024.10561081