Low-Carbon Policies and Power Generation Modes: An Evolutionary Game Analysis of Vertical Governments and Power Generation Groups

Given the great proportion of CO2 emissions from electricity generation in total energy-related CO2 emissions, this article constructs a tripartite evolutionary game model consisting of vertical governments and power generation groups (PGGs), where the vertical governments include the central government (CG) and local governments (LGs), considering the externalities of different power generation modes on energy security and the environment. This article analyzes the stable strategies of the three players through replicator dynamics equations, draws the evolutionary phase diagrams, and analyzes the asymptotic stability of equilibrium points by using Jacobian matrices. To validate and broaden the results, this article also provides a numerical simulation. This article concludes that (1) a reduction in the supervision, enforcement, or low-carbonization costs of the CG, LGs, or PGGs motivates it or them to choose “supervision”, “enforcement”, or “low-carbonization” strategies; (2) an increase in penalty incomes or expenses encourages the CG or LGs to choose the “supervision” or “enforcement” strategies; (3) a rise in extra tax expenses motivates PGGs to choose the “low-carbonization” strategy; (4) a change in the externalities of energy security or the environment has no impact on the CG’s strategy. The above conclusions offer the CG and LGs with references for making effective low-carbon policies and provide PGGs with references for choosing an appropriate power generation mode.

Authors

Institutions

Publication Details

Journal
Energies
Published
2025-09-30
DOI
https://doi.org/10.3390/en18195210
Primary Topic
Climate Change Policy and Economics
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Low-Carbon Policies and Power Generation Modes: An Evolutionary Game Analysis of Vertical Governments and Power Generation Groups

Jun Yu, Feng Zong-xian
Energies
Climate Change Policy and Economics
article

Low-Carbon Policies and Power Generation Modes: An Evolutionary Game Analysis of Vertical Governments and Power Generation Groups

Jun Yu, Feng Zong-xian
article en

Abstract

Given the great proportion of CO2 emissions from electricity generation in total energy-related CO2 emissions, this article constructs a tripartite evolutionary game model consisting of vertical governments and power generation groups (PGGs), where the vertical governments include the central government (CG) and local governments (LGs), considering the externalities of different power generation modes on energy security and the environment. This article analyzes the stable strategies of the three players through replicator dynamics equations, draws the evolutionary phase diagrams, and analyzes the asymptotic stability of equilibrium points by using Jacobian matrices. To validate and broaden the results, this article also provides a numerical simulation. This article concludes that (1) a reduction in the supervision, enforcement, or low-carbonization costs of the CG, LGs, or PGGs motivates it or them to choose “supervision”, “enforcement”, or “low-carbonization” strategies; (2) an increase in penalty incomes or expenses encourages the CG or LGs to choose the “supervision” or “enforcement” strategies; (3) a rise in extra tax expenses motivates PGGs to choose the “low-carbonization” strategy; (4) a change in the externalities of energy security or the environment has no impact on the CG’s strategy. The above conclusions offer the CG and LGs with references for making effective low-carbon policies and provide PGGs with references for choosing an appropriate power generation mode.

EnergiesVol. 18(19)
Xi'an Jiaotong University (CN)
Openalex Percentile: Top 65%
Climate Change Policy and Economics
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.