Optimization of Low-Carbon Technology Adoption Decision for Generation Enterprises Considering Cost Uncertainty

doi:10.11930/j.issn.1004-9649.202403055

Abstract

Abstract:

To investigate the investment decision optimization issue under the condition of uncertain cost of multiple types of low-carbon technologies faced by power generation enterprises to actively achieve the goal of "dual carbon", this paper takes the medium- and long-term time-scale decision-making optimization of independent power generation enterprises as the research perspective. Considering the cost uncertainty of various technologies within the investment period, a two-stage robust model is constructed based on the expected output and installed capacity. In the first stage, the objective is to maximize the net profit of the enterprise's operations. In the second stage, the cost uncertainty of various technology investments and the expected output provided in the first stage are considered as constraints. A comprehensive consideration of the annual investment intensity of the enterprise and the total investment limit for the investment plan period is made to minimize the total investment cost. The second-stage model is transformed into an equivalent linearized model for subsequent solving of the problem in a robust equivalent form. The column-and-constraint generation algorithm is employed to solve the two-stage problem. The effectiveness of the proposed model is verified by comparing the evolution of the power generation company's power structure under different scenarios, which can provide valuable insights for power generation companies adopting low-carbon technologies.

Key words: low-carbon technology, technology adoption, uncertainty, two-stage decision, investment decision, C&CG algorithm

TAN Qinliang, HE Jiaming, LV Hanyu, DING Yihong. Optimization of Low-Carbon Technology Adoption Decision for Generation Enterprises Considering Cost Uncertainty[J]. Electric Power, 2025, 58(5): 62-73.

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URL: https://www.electricpower.com.cn/EN/10.11930/j.issn.1004-9649.202403055

https://www.electricpower.com.cn/EN/Y2025/V58/I5/62

Figures/Tables 14

Fig.1 System layout

Fig.2 Procedure of the solution algorithm

Fig.3 Simulation result of the carbon emissions price

Fig.4 Simulation result of levelized cost of electricity

Fig.5 Simulation result of hydrogen fuels price

Fig.6 Investment bound in each stage

Table 1 Current investment cost of each technology

模块	技术	单位成本
发电	光伏发电	1013.7 万元/MW
	风力发电	915.8 万元/MW
	水力发电	1801.8 万元/MW
	火力发电	2133.1 万元/MW
储能	抽水蓄能	1848 万元/MW
	电池储能	1106 万元/MW
	热储能	39.9 万元/MW
	重力储能	1448.0 万元/MW
降碳	EOR技术	0.05 万元/t
	MET技术	35.7 万元/t
	ALK技术	599.2 万元/MW
	PEM技术	1199.8 万元/MW

Table 2 Scenario explanations

情景	碳中和年份	投资收益率/%	发电份额占比/%	额外投资决策条件
0	2060	6	100	无
1	2050	6	100	无
2	2060	6	75	无水电/抽蓄
3	2050	6	75	无水电/抽蓄

Fig.7 Annual installed capacity and energy for each energy source under the original scenario

Fig.8 Installed capacity of energy storage under the original scenario

Fig.9 Distribution of annual investment

Fig.10 Comparison of the investment costs and environmental benefits under different neutrality scenarios

Fig.11 Comparison of the investment of energy sources and storage technologies under different pumped-water scenarios

Fig.12 Comparison of the distribution of multiple energy sources under scenario 2 and 3

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