Assessing flexibility options in power systems using Fuzzy Logic and AHP methods

Alexopoulos, Dimitrios; Anastasiadis, Anestis G.; Kaminaris, Stavrοs D.; Vokas, Georgios A.; Psomopoulos, Constantinos S.

doi:10.1016/j.egyr.2022.07.079

Cited by 9 publications

(1 citation statement)

References 16 publications

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“…The equations for the consistency indicator CI and consistency ratio CR are as follows, where the range of values of RI is shown in Table 2, and the judgment matrix consistency test is considered to be passed when CR < 0.1 [14]. Entropy Weight Method (EWM) is an objective decision-making method adapted to multi-indicator constraints [15], whose basic principle is to determine the importance of each indicator by calculating the information entropy, which can be used to determine the weights of each indicator through the characteristics of the data itself without the need for subjective judgment [16].…”

Section: Consistency Testmentioning

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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Section: Consistency Testmentioning

confidence: 99%