Adaptive optimization and dynamic pricing in decentralized energy markets using blockchain technology and consensus-based verification

Peer-to-peer (P2P) markets are the key to unlocking the streamlined convergence of the prominent 5D elements in microgrids. However, current implementations focus on conventional methods that prioritize electricity cost reduction which often results in sub-optimal grid operation. This underscores the need for holistic and adaptive optimization in decentralized energy markets. This research introduces a novel consensus strategy built on principles from blockchains to serve as an overarching cross-verification tool that ensures integrity between off-chain and on-chain computations. The strategy leverages a dynamic stake function and reputation system to outperform traditional proof-of-stake. An adaptive optimization model along with a dynamic pricing model is then proposed and validated through multiple Python simulations. The work is proven to improve P2P interactions and grid efficiency. Furthermore, the overall system was implemented in a Solidity smart contract and deployed on an Ethereum test work to demonstrate the interoperability and functionality of the framework proposed. Suggestions for subsequent research are additionally included. In summary, this paper contributes to decentralized, equitable, efficient and self-sufficient microgrids.