From conventional to smart substations: A classification model

Santos, Gabriel Rodrigues; Zancul, Eduardo; Manassero, Giovanni; Spinola, Mauro

doi:10.1016/j.epsr.2023.109887

Cited by 3 publications

(1 citation statement)

References 57 publications

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“…As a dominant force in carbon emission reduction, the power industry contributes to carbon reduction in various ways, including the applications of CCUS (Carbon Capture, Utilization, and Storage) in the power generation process, the enhancement of energy saving, and the upgrading of the consumer side, etc. [2,3] However, at present, there are few carbon reduction measures in transmission and transformation projects [4]. Data show that the total investment in China's power grid during the "14th Five-Year Scheme" period is close to 3 trillion yuan, higher than the "Twelfth Five-Year Scheme" and "thirteenth Five-Year Scheme" period of 2 trillion yuan and 2.57 trillion yuan of investment [5].…”

Section: Introductionmentioning

confidence: 99%

Comprehensive Evaluation and Scheme Optimization for Power Transmission and Transformation Projects with the Adoption of Carbon Reduction Technologies

Zhao,

Chen,

Jia

et al. 2024

Energies

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To investigate the economic impact of carbon reduction technology on power transmission and transformation projects, carbon reduction technologies adapted to power transmission and transformation projects were investigated, and the evaluation indicator system for cost-benefit in power transmission and transformation projects was established based on AHP (Analytic Hierarchy Process) and EWM (Entropy Weight Method). Taking 110 kV and 220 kV transmission and transformation projects in a province located in northwest China as an example, a sensitivity analysis was carried out for the weight of each carbon reduction technology. Additionally, based on the evaluation indicator system, eight alternative carbon reduction schemes were proposed, and the net present value and scheme scores were analyzed with TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution). The results showed that in the criterion layer of the 110 kV case, the highest proportion of weight is “high-efficiency transformer”, accounting for 34.12%, and in the indicator layer, the highest proportion of weight is “ parasitic losses”, accounting for 12.35%. After conducting error analysis on the 110 kV and 220 kV cases, it was found that the errors were within an acceptable range both in the criterion layer and index layer. Moreover, it is expected to achieve greater economic benefits through lower costs according to Scheme VI, and due to the limitations of carbon reduction technologies and the lack of a relevant policy system, it is difficult to achieve the goal of covering costs with benefits for the eight schemes studied.

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