In the context of large-scale grid integration of renewable energy
accurately assessing the power supply capacity of large-scale renewable energy is crucial for improving the economy and reliability of power systems. To address the issues of high subjectivity in index weight allocation and single-dimensional evaluation in existing assessment methods
this paper proposes an evaluation method for large-scale renewable energy power supply capacity based on the best-worst network (BWN) method and the improved criteria importance through intercriteria correlation (CRITIC) method. First
a dual-dimension evaluation index system covering “renewable energy transmission capacity” and “local consumption capacity” is constructed to comprehensively characterize the core features of large-scale renewable energy power supply capacity. For index weighting
the BWN method is used to integrate expert experience and determine subjective weights
while the coefficient of variation is introduced to improve the CRITIC method for more accurate extraction of objective information from data. Finally
subjective and objective weights are combined via multiplicative synthesis to achieve bidirectional adjustment of index importance. Case study results show that the proposed method effectively aligns with the actual operational characteristics of power grids
offering both scientific rigor and engineering practicality
and can provide quantitative decision support for the planning and operation of power systems with a high proportion of renewable energy.
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