Research on the economic optimal configuration of energy storage in distribution networks under carbon-green certificate trading mechanisms
With the increasing penetration of renewable energy sources, active distribution networks face significant challenges in voltage regulation and carbon emission mitigation. Energy storage systems (ESS) provide a flexible solution, yet their economic viability is heavily influenced by emerging market mechanisms such as Carbon Trading and Green Certificate Trading. This paper proposes a dynamic optimization framework for ESS configuration. Firstly, a cooperative differential game model aiming for social welfare maximization is established between the Distribution Network Operator (DNO) and independent Energy Storage Operators (ESO), where the state-of-charge (SoC) and cumulative carbon intensity are modeled by analogizing epidemiological dynamics. Subsequently, Pontryagin’s Maximum Principle (PMP) is employed to derive the theoretical feedback Nash equilibrium and optimal trajectories. To address the model dependency and computational complexity of analytical methods in high-dimensional network environments, a data-driven solution framework based on Proximal Policy Optimization (PPO) is further proposed. By reconstructing the continuous-time game into a Markov Decision Process (MDP), the PPO agent achieves adaptive scheduling through autonomous interaction with the market environment.