<abstract xmlns="http://www.w3.org/1999/xhtml">

<p>In this paper, a new grid planning combined with low-carbon operation simulation is proposed, a new grid planning and low-carbon operation simulation model is proposed, and the new grid planning model is investigated and illustrated from the four dimensions of constraints. For the new grid simulation planning model, the solution efficiency of the new grid planning model combined with low-carbon operation simulation is improved by the time series clustering method and the extreme scenario identification method based on the amount of lost load. Starting from the low-carbon benefit dynamics of the generation side and the consumption side, a refined urban new grid low-carbon benefit dynamic evaluation model is constructed, while the model parameters and table functions are set, and the low-carbon urban grid simulation planning based on low-carbon simulation is empirically analyzed by means of simulation analysis. The results show that in grid planning, when the carbon emission intensity is 1000gCO2/kWh, the S4 scenario only needs to add an extreme scenario in the iterative process to achieve a relative error accuracy of 0.1%, and the method of using the new grid planning and the low-carbon operation simulation model is sufficient to achieve the target of the loss of load rate and carbon emission intensity. In the evaluation of the low-carbon effect, with the increase in investment amount, the installed capacity of clean energy and the total CO<sub>2</sub> emission reduction of the refined urban grid will show two relatively obvious upward trends.</p>
</abstract>

In this paper, a new grid planning combined with low-carbon operation simulation is proposed, a new grid planning and low-carbon operation simulation model is proposed, and the new grid planning model is investigated and illustrated from the four dimensions of constraints. For the new grid simulation planning model, the solution efficiency of the new grid planning model combined with low-carbon operation simulation is improved by the time series clustering method and the extreme scenario identification method based on the amount of lost load. Starting from the low-carbon benefit dynamics of the generation side and the consumption side, a refined urban new grid low-carbon benefit dynamic evaluation model is constructed, while the model parameters and table functions are set, and the low-carbon urban grid simulation planning based on low-carbon simulation is empirically analyzed by means of simulation analysis. The results show that in grid planning, when the carbon emission intensity is 1000gCO2/kWh, the S4 scenario only needs to add an extreme scenario in the iterative process to achieve a relative error accuracy of 0.1%, and the method of using the new grid planning and the low-carbon operation simulation model is sufficient to achieve the target of the loss of load rate and carbon emission intensity. In the evaluation of the low-carbon effect, with the increase in investment amount, the installed capacity of clean energy and the total CO2 emission reduction of the refined urban grid will show two relatively obvious upward trends.

Refined Urban Grid Simulation Planning Based on Low Carbon Goal Achievement

Applied Mathematics and Nonlinear Sciences

This work is licensed under the Creative Commons Attribution 4.0 International License.

{"article-title":"Refined Urban Grid Simulation Planning Based on Low Carbon Goal Achievement"}

In this paper, a new grid planning combined with low-carbon operation simulation is proposed, a new grid planning and low-carbon operation simulation model is...

Refined Urban Grid Simulation Planning Based on Low Carbon Goal Achievement

Publié en ligne: 29 nov. 2023

Pages: -

Reçu: 30 déc. 2022

Accepté: 09 juin 2023

DOI: https://doi.org/10.2478/amns.2023.2.01287

Mots clés
Time-series clustering method, Extreme scenario identification, Low carbon simulation model, Refined city, New grid planning

© 2023 Cuizhi Tong et al., published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Refined Urban Grid Simulation Planning Based on Low Carbon Goal Achievement

Publié en ligne: 29 nov. 2023

Pages: -

Reçu: 30 déc. 2022

Accepté: 09 juin 2023

DOI: https://doi.org/10.2478/amns.2023.2.01287

Mots clésTime-series clustering method, Extreme scenario identification, Low carbon simulation model, Refined city, New grid planning

© 2023 Cuizhi Tong et al., published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Mots clés
Time-series clustering method, Extreme scenario identification, Low carbon simulation model, Refined city, New grid planning