Comparison of county-level rooftop photovoltaic development models in China's electricity spot market

To achieve its “dual carbon” objectives, China must refine its approach to the deployment of rooftop distributed photovoltaic (DPV) systems across entire counties. Existing research often neglects the rooftops of commercial, industrial, and public institutions and lacks comparative analyses of different development models. This paper innovatively integrates the Monte Carlo method into an asymmetric tripartite evolutionary game model to evaluate the efficiency of various guiding policies and business models. Additionally, it explores the potential impact of electricity spot trading on the development of rooftop DPV systems. The study finds that financial policies are more effective than pure price policies, whereas mixed policies are the least efficient. The optimal business model varies with the policy environment: under financial and mixed policies, the owner self-construction model yields the highest expected utility, while under pure price policies, the financial leasing model is preferable. Moreover, the introduction of electricity spot trading significantly reduces the expected benefits for rooftop PV operators and heightens benefit volatility. These findings remain robust even when installation scale constraints are relaxed. Furthermore, higher rooftop leasing prices hinder the development of commercial and industrial rooftop PV systems, while excessive ancillary service prices may alter the Nash equilibrium among stakeholders. Our findings offer valuable insights for policymakers aiming to address the “inversion” problem in the development of county-wide rooftop photovoltaic (PV) systems and provide practical references for building a renewable energy-friendly electricity system.