The evaluation of thermal power enterprise coal suppliers based on analytical hierarchy process

Duan, Xuhui

doi:10.1109/iciii.2013.6702908

Cited by 1 publication

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“…A multi-generation system based on the integrated three-effects refrigeration system was proposed to substantially improve thermal power efficiency [14]. Other scholars researched the fuel cost of thermal power enterprises, which is the central link of production control and economic calculation of the enterprises [15]. A hybrid fuzzy multi-attribute decision-making approach (fuzzy entropy-TOPSIS) was proposed to select the best green supplier [16].…”

Section: Introductionmentioning

confidence: 99%

An Operation Benefit Analysis and Decision Model of Thermal Power Enterprises in China against the Background of Large-Scale New Energy Consumption

et al. 2020

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With the continuous increase in new energy installed capacity, the slowdown in the growth of social power consumption, the pressure created by high coal prices, and the reduction in on-grid electricity tariffs, the challenges facing the survival and development of thermal power generation enterprises are becoming more severe. Hence, based on the cost–benefit analysis method, this paper proposes a diversified operating benefit analysis and decision model for thermal power generation enterprises that includes four profit models: power sales, peak load regulation (without oil), peak load regulation (with oil), and generation right trading. The opportunity cost of peak load regulation and generation rights trading was considered, and six scenarios were designed. An empirical analysis was conducted by selecting a thermal power enterprise in Ningxia, Northwest China, as an example, using scenario and sensitivity analyses. The results show that under the diversified business model, thermal power generation enterprises can more effectively avoid the risks when the external environment changes and significantly improve its economic benefits. The consumption of new energy can be promoted, and positive social effects will be achieved. Therefore, the findings will help the thermal power generation enterprises to face these challenges.

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Section: Introductionmentioning

confidence: 99%