Abstract

With the rapid development of smart grid, constructing distributed energy trading market (DETM) based on blockchain to coordinate distributed energy resources (DER) has become a future direction. However, existing consensus algorithms of blockchain face many challenges in large-scale energy trading scenarios, such as high resource overhead, slow transaction procedure. To solve the above crucial problems for wide deployment of distributed energy trading, this study proposes a novel consensus algorithm named Lightweight adaptive Byzantine fault tolerant consensus (LA-BFT), and a reputation calculation method based on behavioral characteristics for selection of consensus nodes. The LA-BFT consists of two parts: (i) weak consensus for normal cases. By introducing threshold signature mechanism, weak consensus simplifies the consensus process to achieve linear communication complexity O(n). (ii) byzantine node detection scheme is enable for malicious cases. With consensus committee, the detection scheme can detect the potential byzantine nodes by cross-validation, which ensures transaction safety. The reputation calculation method is presented to cooperate with LA-BFT to elect leaders and candidates for consensus procedure. Once a round of consensus is completed, the reputation of each node needs to be updated, only nodes with high reputation are eligible to become leaders or committee nodes in the next round. With the reputation calculation method, honest nodes and byzantine nodes can be effectively identified, ensuring the security of the consensus process. Numerical results indicate that LA-BFT exhibits superior performance on communication overhead and bandwidth occupancy in large-scale concurrent energy trading scenarios. When the number of nodes is 50, under normal scenarios, LA-BFT’s communication overhead is notably lower, constituting a mere 6.02% of PBFT and 24.26% of SHBFT, while bandwidth occupancy amounts to merely 5.55% of PBFT and 9.76% of SHBFT.

Full Text
Published version (Free)

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call