A Novel Power Data Sharing Platform

Abstract

The expansion of advanced metering, distributed energy resources, dispatch operations, asset management, and electricity-market data has exposed the limitations of traditional database-to-database exchange and manually administered authorization. Such conventional solutions cannot simultaneously achieve semantic interoperability, cross-domain least-privilege access, low-latency delivery, privacy minimization, and end-to-end accountability. This paper presents CECF, the Cloud-Edge-Chain Feedback platform for power-data sharing. The IEC Common Information Model provides the semantic foundation. Edge gateways perform tasks such as protocol adaptation, time-stamp correction, data quality filtering, sensitive field masking, stream data buffering and hotspot content caching. The cloud data plane integrates object storage services, time-series databases and event bus components. The authorization framework combines role-based access control, attribute-based security policies, access purpose declaration and real-time context risk evaluation. Large operational payloads remain encrypted off-chain. Only message digests, policy versions, timestamps, authorization decisions and audit evidence indexes are recorded on a permissioned ledger. Using monitoring indicators including P95 latency, queue length, cache-hit rate, failure rate and policy risk value, the feedback controller adjusts evidence micro-batch parameters, cache prefetching strategies and policy thresholds. A differential-privacy interface supports statistical data sharing scenarios. The reported simulations use Poisson arrival flow and multi-stage queueing models. At an offered load of 1200 requests per second, CECF achieves P95 latency of 16.38 ms. Relative to centralized architecture, full on-chain scheme and static-hybrid architecture, its P95 latency drops by 42.1%, 69.5% and 14.6% respectively. When the offered request rate rises to 1800 requests/s, the platform maintains 1802.8 SLO-qualified requests per second. The ablation results indicate that edge caching and closed-loop feedback control are the principal mechanisms that prevent a sharp increase in tail latency. The design provides a feasible route to power-data sharing with high efficiency, verifiability and standardized governance. Its parameters nevertheless require recalibration on a testbed close to production conditions.