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Ranking provincial power generation sources of China: a decision-maker preferences based integrated multi-criteria framework

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Abstract

The ranking of power generation sources is a very important prerequisite for power generation installation planning and power supply security. This study proposed a new multi-criteria system for ranking regional power generation sources in one country, including resources, economy, technology, environment, and society, using 11 sub-criteria. Based on the system, a novel decision-maker (DMs) preference-based integrated MCDM framework involving four methods (Visekriterijumsko Kompromisno Rangiranje (VIKOR), Technique for Order Preference by Similarity to Ideal Solution (TOPSIS), Preference Ranking Organization Method for Enrichment Evaluations (PROMETHEE), and Weighted Sum Method (WSM)) was developed for ranking six power generation sources (thermal, nuclear, wind, hydro, solar PV, and biomass) at the level of China’s 30 provinces. Six different preferences of DMs are considered in the ranking according to five criteria. The results show that wind should be the power generation source given the top priority in most provinces in China whereas nuclear power and thermal power are the last choice for 26 provinces. Biomass is the most preferable power source for 17 provinces based on technological preference in which DMs regard the technology criteria is prior to all other criteria. Thermal power would still the preferred or secondary power source for provinces rich in coal resources such as Shanxi, Inner Mongolia, Henan, and Shaanxi.

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Notes

  1. The total number of nuclear power plants includes all nuclear power plants in operation, establishment, and preparation.

  2. This is mainly due to the high actual utilization hours of thermal power

  3. Preferential taxation policies to promote the development of wind power include: levying half of the value-added tax payable on wind power; in terms of income tax, wind power companies enjoy the former 3-year income tax exemptions and later 6-year halve and so on.

  4. Accelerate the application of distributed photovoltaics in various fields, implement the five major sunshine projects of “Sunshine Campus, Sunshine Business, Sunshine Park, Sunshine Agriculture, and Sunshine Infrastructure,” encourage residential households to apply distributed photovoltaic power generation systems, and promote the participation of the whole society in development and utilization of solar PV.

  5. Encourage and support enterprises to develop roof photovoltaics in the form of roof leasing, cooperative co-construction, etc., and develop photovoltaic power plants of” agricultural light complementary” and “fishing and Light Complementary”.

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Funding

This study received financial supports from the National Natural Science Foundation of China (Grant Nos.71822403 and 31961143006) and Hubei Natural Science Outstanding Foundation (Grant No. 2019CFA089).

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Authors and Affiliations

  1. Center for Energy Environmental Management and Decision-making, China University of Geosciences, Wuhan, 430074, China

    Shiwei Yu, Yali Zheng, Longxi Li & Kaiming Wang

  2. School of Economics and Management, China University of Geosciences, Wuhan, 430074, China

    Shiwei Yu, Yali Zheng, Longxi Li & Kaiming Wang

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  1. Shiwei Yu
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  2. Yali Zheng
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Correspondence to Shiwei Yu.

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Appendix

Appendix

Table 3 Preference vector and a collective multiplicative preference relation
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Table 4 Power generation sources’ orders of four MCDMs based on equal preference
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Table 5 Power generation sources’ orders based on different preferences except equal preference
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Yu, S., Zheng, Y., Li, L. et al. Ranking provincial power generation sources of China: a decision-maker preferences based integrated multi-criteria framework. Environ Sci Pollut Res 27, 36391–36410 (2020). https://doi.org/10.1007/s11356-020-09609-z

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