Dynamic Potential Assessment of Source-containing Industrial Parks: A Novel Method for Sustainable Energy Grid Management
DOI:
https://doi.org/10.13052/spee1048-5236.4519Keywords:
Logarithmic mean divisia index, distributed photovoltaic, source-containing industrial parks, potential assessment, demand-side response, grid sustainabilityAbstract
This paper proposes a dynamic potential assessment method for source-containing industrial parks based on the Logarithmic Mean Divisia Index (LMDI) decomposition method. First, missing data are filled using Random Forest, and influence factors are quantitatively assessed by considering multi-featured factors using the LMDI decom-position method and the limit value normalization method, including distributed photovoltaic (PV) power generation impact factors, incentive tariff impact factors, energy-use behavior impact factors, and response willingness impact factors. Secondly, based on the LMDI method combined with an improved weighted polynomial regression model, the next scenario containing source industrial users is determined, providing a relatively real and reliable demand response potential assessment value. Finally, real historical response values from a certain park in the power grid were used for fitting and validation. The response deviation value was used as the evaluation criterion. Compared to the evaluation methods that do not consider data completion and those that consider only a single factor, the average response deviation rates were 4.34%, 3.23%, and 1.35%, respectively. The method proposed in this paper had the lowest average deviation rate. Additionally, this method demonstrated the changes in the weights of influencing factors. By providing a transparent and highly accurate tool for managing demand-side resources, this work facilitates greater renewable energy integration, contributing to a more efficient, stable, and sustainable power system.
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