Dynamic Comprehensive Evaluation of a 660 MW Ultra-Supercritical Coal-Fired Unit Based on Improved Criteria Importance through Inter-Criteria Correlation and Entropy Weight Method

Author:

Yuan Haotian1ORCID,Ma Xiaojing12ORCID,Cheng Zening34,Kari Tusongjiang1

Affiliation:

1. Collage of Electrical Engineering, Xinjiang University, Urumqi 830049, China

2. Engineering Research Center of Northwest Energy Carbon Neutrality, Ministry of Education, Xinjiang University, Urumqi 830049, China

3. Zhundong Energy Research Institute, Xinjiang Tianchi Energy Co., Ltd., Changji 831100, China

4. Xinjiang Changji Tebian Energy Co., Ltd., Changji 831100, China

Abstract

To address the issue of traditional static evaluation models being unable to comprehensively analyze the performance of ultra-supercritical coal-fired units under varying loads, we propose a dynamic comprehensive evaluation model based on the improved Criteria Importance Through Inter-criteria Correlation (CRITIC) method and entropy weight method (EWM). The comprehensive performance evaluation index system of ultra-supercritical coal fired units is constructed by examining the boiler performance, turbine performance, plant power performance, environmental performance, and flexible performance of coal-powered units. The CRITIC and EWM methods are used to calculate the weights of the indicators, which are then combined with the static evaluation results. Using a dynamic comprehensive evaluation model, we analyze ultra-supercritical coal-fired units, taking into account time weight. This allows us to obtain the comprehensive dynamic real-time evaluation value of the units under different loads. The research indicates that the weight of the evaluation index is changed when using the dynamic comprehensive evaluation model of the improved CRITIC and EWM. The index with lower weight is increased by 6.2%, while the index with higher weight is decreased by 0.22%. This alteration in weight range can provide a more objective reflection of the relationship between evaluation indicators. This model offers significant advantages in improving evaluation accuracy, weight balance distribution, and generality.

Funder

Major Science and Technology Special Project of Xinjiang Uygur Autonomous Region

National Natural Science Foundation of China

Xinjiang Uygur Autonomous Region Tianshan Talent Training Program-Youth Talent Support Project

Key Research and Development Task Special Project of Xinjiang Uygur Autonomous Region

Xinjiang Uygur Autonomous Region Tianshan Talent Training Plan

Publisher

MDPI AG

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