Energy, as one of the larger contributing industries to greenhouse gas emissions, has an urgent task to reduce emissions, and standardizing the carbon footprint and trading mechanism of the energy market is an important concern for the development of the current energy industry. Under the guidance of the principle of green, low-carbon and sustainable development of the energy market, this paper first uses heterogeneous blockchain and federated reinforcement learning to design a decentralized energy trading mechanism model. It is found that the model fails to realize the intelligent detection and control of carbon footprint, in this regard, on the original model, the carbon footprint origin algorithm is introduced. Combining the above models and algorithms, the current interactive energy market is explored and analyzed. Consumer user 5 has the largest net benefit, with a specific value of 15.05 million yuan, and comprehensive energy supplier 3 has the largest net benefit, with a value of 37,467,000 yuan, indicating that this paper’s model implements the principle of green, low-carbon and sustainable development of energy while meeting the energy needs of consumers and suppliers, maximizing the interests of each other in the process of energy trading, which proves that this paper’s research has excellent practical application value.
