A tripartite evolutionary game model for tradable green certificate transaction strategies in China

Shiwei Yu (), Chengzhu Gong, Weidong Jia and Li Ma
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Shiwei Yu: University of Geosciences
Chengzhu Gong: University of Geosciences
Weidong Jia: University of Geosciences
Li Ma: University of Geosciences

Operational Research, 2024, vol. 24, issue 4, No 15, 29 pages

Abstract: Abstract As a market-oriented approach to ensure the consumption of renewable energy (RE), tradable green certificate (TGC) transactions drive the reactions and decisions of market participants; the strategic behavior exhibited by these participants plays a crucial role in shaping the development of the TGC market. This study proposes a tripartite evolutionary game model that includes various stakeholders (energy regulators, power producers, and power sellers) to analyze their behavioral strategies and evolution processes under different policy settings. Instead of numerical simulation, two heterogeneous provinces (Liaoning and Hunan) with distinct physical RE consumption capacities are selected as empirical case studies. The results indicate that the evolutionarily stable strategy for power producers is to sell TGCs, whereas that for power sellers is to not purchase them. However, the stable strategies for energy regulators differ significantly. Moreover, the TGC price, penalty levels for unfulfilled renewable portfolio standard (RPS) quotas, and rewards for exceeding quota consumption affect only players' behavioral evolution process; they do not alter their ultimate stabilization strategy. Nevertheless, secondary TGC transactions can increase power sellers' willingness to buy them and activate the TGC market. The findings can help identify the key determinants underlying the current lack of trading activity, thereby providing valuable insights for enhancing the efficiency and effectiveness of the TGC market.

Keywords: OR in energy; Tripartite evolutionary game; Strategic behavior; Tradable green certificate transactions; Renewable energy (search for similar items in EconPapers)
Date: 2024
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DOI: 10.1007/s12351-024-00874-1

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