A Comprehensive Architectural, Game-Theoretic, and Cryptographic Analysis of Blockchain-Enabled Peer-to-Peer Transactive Energy Trading and Vehicle-to-Grid (V2G) Coordination in Smart Microgrids

The rapid proliferation of Distributed Energy Resources (DERs)—including rooftop solar photovoltaics (PV), behind-the-meter Battery Energy Storage Systems (BESS), and bidirectional Electric Vehicles (EVs)—is fundamentally transforming legacy unidirectional power grids into decentralized, bidirectional cyber-physical microgrids. In this emerging landscape, traditional passive electricity consumers are evolving into active 'prosumers' capable of generating, storing, and trading surplus renewable energy locally. However, conventional centralized Distribution System Operator (DSO) market clearinghouses suffer from single-point-of-failure vulnerabilities, high settlement latencies, opaque tariff structures, and severe privacy leakage of granular Advanced Metering Infrastructure (AMI) load profiles. Furthermore, uncoordinated EV charging threatens distribution substation transformers with severe peak-load congestion and voltage instability. Blockchain technology—endowed with tamperproof distributed ledgers, low-latency permissioned consensus, and deterministic smart contracts—provides a trustless cyber-physical backbone for automated Peer-to-Peer (P2P) transactive energy markets. This paper presents a comprehensive architectural, game-theoretic, and cryptographic investigation of blockchain technology in smart microgrids and Vehicle-to-Grid (V2G) ecosystems. We propose a five-layer cyber-physical reference architecture integrating AMI/IEC 61850 edge hardware, fog aggregators, permissioned consortium blockchains, and Layer-2 micro-payment state channels. We formulate rigorous mathematical models for McAfee-based Continuous Double Auction (CDA) smart contract market clearing, Stackelberg game-theoretic pricing equilibrium, AC distribution network physical power-flow and nodal voltage constraints, and V2G battery degradation-aware peak shaving. To prevent household behavioral profiling from public auction bids, we formalize a privacy-preserving protocol utilizing Pedersen cryptographic commitments and Zero-Knowledge Range Proofs (zk-SNARKs). Finally, we evaluate realworld pilot deployments, benchmark consensus throughput across up to 1,000 prosumer nodes, and outline future research directions in AI-driven predictive bidding and post-quantum smart grid ledgers.