Toward Secure and Privacy-Preserving Distributed Scheduling in Data-Center-Integrated Microgrids via Blockchain

As data centers become major and schedulable loads of the new power system, connecting them to multiple microgrids offers a promising route to absorb local renewable energy through cross-domain coordination. However, when the microgrids belong to competing operators, coordinated scheduling forces each party to disclose its data-center load curve, storage state, and pricing strategy, which constitutes a core operational secret that no microgrid is willing to reveal. This paper develops a secure and privacy-preserving distributed scheduling scheme for data-center-integrated microgrids built on blockchain. A “data-stays-local, energy-crosses-centers” model is established that elevates privacy from an add-on feature to a first-order architectural constraint, defining a “three-no” principle and a two-layer architecture in which each microgrid optimizes its interior in plaintext and exposes only encrypted matchable factors. On this basis, a decentralized ciphertext scheduling-negotiation algorithm is designed on blockchain smart contracts, performing cross-microgrid matching under secure multi-party computation entirely in the encrypted domain, committing auditable encrypted digests on-chain, and dynamically allocating scheduling priority through an on-chain reputation mechanism. Case studies on a cluster of interconnected microgrids show that the proposed scheme attains cost and renewable accommodation within about three-tenths of a percent of the centralized optimum while reducing operational data-leakage risk from 96.7 percent to 3.8 percent, at the manageable expense of a few seconds of negotiation latency. Benchmarking against an exact mixed-integer solver on small-scale systems bounds the mean optimality gap of the decomposed scheme at 0.74 percent, with a worst case of 2.54 percent over sixty instances.