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With the electric power grid experiencing a rapid shift to the smart grid paradigm over a deregulated energy market, Internet of Things (IoT) based solutions are gaining prominence and innovative Peer To Peer (P2P) energy trading at micro-level are being deployed. Such advancement, however leave traditional security models vulnerable and pave the path for Blockchain, an Distributed Ledger Technology (DLT) with its decentralized, open and transparency characteristics as a viable alternative. However, due to deregulation in energy trading markets, massive volumes of micro transactions are required to be supported, which become a performance bottleneck with existing Blockchain solution such as Hyperledger, Ethereum and so on. In this paper, a lightweight 'Tangle' based framework, namely IOTA (Third generation DLT) is employed for designing an energy trading market that uses Directed Acyclic Graph (DAG) based solution that not only alleviates the reward overhead for micro-transactions but also provides scalability, quantum-proof, and high throughput of such transactions at low confirmation latency. Furthermore the Masked Authentication Messaging (MAM) protocol is used over the IOTA P2P energy trading framework that allows energy producer and consumer to share the data while maintaining the confidentiality, and facilitates the data accessibility. The Raspberry Pi 3 board along with voltage sensor (INA219) used for the setting up light node and publishing and fetching data from the Tangle. The results of the obtained benchmarking indicate low confirmation latency, high throughput, system with Hyperledger Fabric and Ethereum. Moreover, the effect of transaction rate decreases when the IOTA bundle size increases more than 10. For bundle size 5 and 10 it behaves absolutely better than any other platform. The speedy confirmation time of transactions in IOTA, is most suitable for peer to peer energy trading scenarios. This study serves as a guideline for deploying, end-to-end transaction with IOTA Distributed Ledger Technology (DLT) and improving the performance of Blockchain in the energy sector under various operating conditions. [ABSTRACT FROM AUTHOR]

Correction to: I Scientific Reports i https://doi.org/10.1038/s41598-022-18603-z, published online 25 August 2022 The original version of this Article contained an error in Affiliation 1, which was incorrectly given as 'School of Computer Science and Engineering (SCOPE), Vellore Institute of Technology, Vijayawada 522237, Andhra Pradesh, India'. The correct affiliation is listed below: School of Computer Science and Engineering (SCOPE), VIT-AP University, Vijayawada 522237, Andhra Pradesh, India. [Extracted from the article]