Game Strategy for Low-Carbon Investment by Electric Power Enterprises under the Dual Drivers of Carbon Quota Mechanism and Blockchain Technology

Main Article Content

C. N. He
H. D. Chen
H. J. Tian
J. Zhang
L. Zhang

Abstract

This study investigates low-carbon investment strategies in power supply chains under the combined influence of carbon quota mechanisms (CQM) and blockchain technology (BCT). A two-echelon system consisting of a power generator and an electricity retailer is modeled, and four decision scenarios are constructed by considering blockchain adoption under both the grandfathering method (GFM) and benchmarking method (BMM). A Stackelberg game framework is employed to analyze the interactions among low-carbon technology investment, low-carbon electricity promotion, market demand, and enterprise profitability. Results show that the BMM consistently induces higher low-carbon investment levels, stronger market demand, and greater retailer profitability than the GFM, regardless of blockchain adoption. Furthermore, blockchain-enabled information traceability exhibits a significant threshold effect: when implementation costs remain below a critical level, trusted information transmission enhances consumer green trust, stimulates demand for low-carbon electricity, and improves the economic performance of supply-chain participants. Sensitivity analysis further demonstrates that consumer green trust, low-carbon preference, and responsiveness to low-carbon promotion positively influence both emissionreduction efforts and enterprise profitability, whereas excessive blockchain deployment costs weaken these benefits. The proposed framework provides a quantitative methodology for analyzing information-enabled lowcarbon decision making and coordinated investment strategies in modern power systems.

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How to Cite
He, C. N., Chen, H. D., Tian, H. J., Zhang, J., & Zhang, L. (2026). Game Strategy for Low-Carbon Investment by Electric Power Enterprises under the Dual Drivers of Carbon Quota Mechanism and Blockchain Technology. Advanced Electromagnetics, 15(3), 2661–2681. https://doi.org/10.7716/aem.v15i3.3322
Section
Research Articles

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