Carbon emission responsibility allocation based on optimal flow tracing considering peer-to-peer energy trading

Reasonable carbon emission allocation is the crucial cornerstone of the low-carbon development of power systems. However, electricity transactions change the economic characteristics of electricity carbon emission responsibility and pose great challenges to the present allocation models. This paper fills the research gap by proposing a brand-new model to allocate responsibility among generation companies, load aggregators, and grid companies simultaneously, with the consideration of Peer-to-Peer trading and physical power flow distribution. First, the trading power shift distribution factor is introduced to analyze the directions of line flow pieces corresponding to each transaction. Then, the allocation model is established based on optimal flow tracing and the trading power shift distribution factor, where the power flow section is divided into several portions corresponding to electricity trades, and the power, together with the responsibility within each portion, can be traced to generators through optimal flow tracing. The responsibility allocated to each entity comprises the parts related to trading power and active losses. The model is further reformulated as a Nash bargaining and transformed with rotated second-order cones and the binary expansion method. Case studies demonstrate that the proposed model can manifest the impacts of different forms of trades on the responsibility allocation intuitively. The contrast between the proposed model and the carbon emission flow method indicates the outstanding advantages in physical rationality and in reducing emissions based on transaction characteristics. Eventually, the scalability is verified on a provincial power system.