Asynchronous blockchain‐based federated learning for tokenized smart power contract of heterogeneous networked microgrid system

Abstract

In a networked microgrid system (NMS), various heterogeneous microgrids are interconnected. A networked microgrid system facilitates a new kind of physical design that provides numerous advantages such as distributed economic optimization, reliability, resiliency, and focusing on distributed generations and customers. Designing the secure and privacy‐protected smart power contract between electricity suppliers and consumers, considered as agents, of different microgrids, is a challenging task in the networked‐ microgrid system. Each microgrid implements a heterogeneous or isomorphic blockchain based platform. The blockchain interoperability, inherently, presents in different blockchains implemented by various microgrids. This paper reviews the interoperability issues and smart contract designs in blockchain‐based systems and proposes new mechanisms to cater blockchain interoperability challenges to facilitate the design of secure and seamless smart contracts among different blockchains of microgrids. A network hub of heterogeneous blockchains of network microgrids has been proposed. A methodology has been developed to transfer tokens between interoperable blockchains. A distributed identity‐based microgrid (DIBM) scheme is incorporated to make the networked microgrid system secure and trustworthy. This paper suggests an effective consensus protocol for cross‐chain architecture that improves the tokenization system and smart power contract designs. Asynchronous blockchain based federated learning for peer‐to‐peer smart power exchange has been implemented in learning process of interoperable and heterogeneous blockchain based network hub of microgrid. For simulation purposes, MATLAB and python programming have been used with real‐time data of microgrids.