Research on the relationship between the digital transformation of new energy enterprises in the context of electricity reform
DOI:
https://doi.org/10.4108/ew.10320Keywords:
wind power, photovoltaic power, energy governance, power index governance, microgrid operationAbstract
The development of new energy sources such as wind power and photovoltaic power needs to be optimized to improve the sustainability of new energy development. At present, there are digital bottlenecks in the development of new energy, and there is a lack of systematic identification of operating indicators such as current, voltage and power flow, which affects the development of new energy enterprises. In order to expand the development scope of new energy, this paper proposes the Hausmann method to extract data from power generation equipment such as wind power and photovoltaic power, digitize the power index, and verify it with actual cases. Firstly, the power data is mapped, the dataset is constructed, and the fitting of the dataset is realized. Then, we can identify abnormal data values, determine the signal characteristics of power flow, voltage, and current, and optimize them. Finally, the governance results of the power index are output. The results show that the demand for data governance in new energy enterprises is high, and digital transformation can improve the effect of governance, the post-grid connection coefficient of voltage is 0.25, and the variation difference is 0.000, and there is no obvious multicollinearity problem between power indicators, the results of power governance are reliable and high, and the volatility of power indicators is in a controllable range of about 0.42~0.75%. Quantitative results show that digital governance stabilizes key power indices, with grid-connected voltage coefficient reaching 0.25, variation difference approaching 0.000, and power index volatility maintained within 0.42–0.75% for durations below 0.8 seconds. Through further analysis, it is found that there is a correlation between the power indicator and digital transformation, which is within the constraint range, and the fluctuation duration is short, less than 0.8 seconds. Under data governance, the stability of voltage, current and power flow is high, the distribution ratio is reasonable, the distribution ratio is 0.33~0.55, and the power index change after grid connection can be suppressed, and the inhibition rate reaches 10%. Therefore, in the face of external factors such as the policy environment, changes in market demand, and technological innovation, digital transformation can optimize the power generation structure of new energy, improve the control rate of power indicators, maintain the stability of current operation, and improve the sustainability of new energy development.
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