Optimal modelling and analysis of DG-GC joint multilateral transaction in energy blockchain environment: from the REP perspective

In the energy blockchain environment, distributed generation (DG) and green certificate (GC) joint transaction is secured through smart contracts, which is seen as one of the potential ways for supporting future electricity market development. However, existing studies rarely take into account the mechanistic relationships and modelling analyses between DG and GC firms and users across a variety of trading scenarios, including carbon emission allowance (CEA) and renewable portfolio standard (RPS), green electricity, conventional energy, and GC. First, with retail electricity provider (REP) as the core, the energy blockchain DG-GC joint transaction framework is built in this paper. Secondly, the study analyzes and designs the joint transaction mechanism and process within this framework. On this basis, an optimization model with economy, low carbon and power purchase satisfaction as the objective function is established for the first time. Then, a bacterial community chemotaxis (BCC) algorithm is proposed to solve the objective values. Finally, the effectiveness of BCC algorithm and model are validated through the case study. The study findings indicate that Mode 3, incorporating both CEA and RPS trading options, significantly decreases power purchase costs, while enhancing low-carbon practices and satisfaction with power procurement.