From the perspective of interactions between energy firm behavior and government intervention strategies, this study develops a contagion control model for energy firm debt default risk utilizing cellular automata and complex network theory. This research investigates the spatio-temporal evolution of risk transmission and evaluates the efficacy of various mitigation protocols through computational simulation. The research results indicate that: (1) An escalation in both the transmission likelihood and the rate of immunity decay significantly amplifies the propagation strength of debt default risks. Conversely, the stability of the energy firm network is bolstered as the probabilities of immunity and recovery increase. (2) The contagion intensity for debt default risk is positively correlated with market noise, the risk appetite of energy firms, and their corporate influence. It is negatively correlated with risk awareness, creditworthiness, regulatory intensity, and policy subsidies. Furthermore, it exhibits an inverted U-shaped relationship with investor sentiment. (3) Within the interconnected network of energy firms, risk contagion can be effectively mitigated not only by enhancing risk perception and credit standing but also by guiding risk preference and managing firm influence. Furthermore, the integration and adjustment of government intervention strategies, such as regulatory intensity and policy subsidies, can more efficiently accelerate the eradication of debt default risk among energy firms.

Within a coordinated fiscal financial policy framework, this study combines complex network analysis with cellular automata to construct a contagion model of debt risk across industrial enterprises. It then uses numerical simulations to examine the dynamic evolution and mitigation strategies of debt risk contagion. The results show that the following: (1) As the contagion probability, immunity failure probability, and contagion probability of immune enterprises increase, debt risk contagion among industrial enterprises is strengthened, whereas higher immunity probability and recovery probability improve network stability. (2) Market noise, carbon tax rate, credit interest rate, and risk preference increase the basic reproduction number relative to the critical boundary of one, whereas fiscal subsidy intensity, green credit ratio, and risk assessment capability reduce it. Within the normalized simulation framework, a carbon tax rate around 0.3, fiscal subsidy intensity around 0.15, and green credit ratio around 0.5 serve as illustrative model-based reference values for interpreting changes in debt risk contagion pressure and risk-mitigation effects. (3) Coordinated fiscal–financial intervention can more effectively reduce $R_0$ and narrow the contagion scope than a single policy tool, suggesting that debt risk prevention should combine fiscal support, green credit allocation, risk assessment improvement, and carbon-policy rhythm management.