An Architecture for Distributed Energies Trading in Byzantine-Based Blockchain

TL;DR

This paper presents a blockchain-based system for secure and efficient distributed energy trading in smart cities, introducing a new consensus mechanism and game-theoretic modeling to optimize interactions and ensure performance.

Contribution

It proposes a novel blockchain architecture with a credit-based Byzantine consensus and models energy trading interactions using a multi-leader multi-follower game, advancing secure distributed energy markets.

Findings

The new consensus mechanism improves blockchain throughput and latency.

The game-theoretic model accurately predicts aggregator behaviors.

Simulations verify the system's efficiency and correctness.

Abstract

With the development of smart cities, not only are all corners of the city connected to each other, but also connected from city to city. They form a large distributed network together, which can facilitate the integration of distributed energy station (DES) and corresponding smart aggregators. Nevertheless, because of potential security and privacy protection arisen from trustless energies trading, how to make such energies trading goes smoothly is a tricky challenge. In this paper, we propose a blockchain-based multiple energies trading (B-MET) system for secure and efficient energies trading by executing a smart contract we design. Because energies trading requires the blockchain in B-MET system to have high throughput and low latency, we design a new byzantine-based consensus mechanism (BCM) based on node's credit to improve efficiency for the consortium blockchain under the B-MET system. Then, we take combined heat and power (CHP) system as a typical example that provides distributed energies. We quantify their utilities, and model the interactions between aggregators and DESs in a smart city by a novel multi-leader multi-follower Stackelberg game. It is analyzed and solved by reaching Nash equilibrium between aggregators, which reflects the competition between aggregators to purchase energies from DESs. In the end, we conduct plenty of numerical simulations to evaluate and verify our proposed model and algorithms, which demonstrate their correctness and efficiency completely.