IoT Cloud-based Distribution System State Estimation: Virtual Objects and Context-Awareness

TL;DR

This paper proposes a cloud-based distribution system state estimation approach utilizing virtualized PMUs at the network edge to improve bandwidth efficiency, latency, and QoS in smart grid applications.

Contribution

It introduces a novel architecture with virtualized PMUs at the edge and demonstrates its effectiveness for reliable, efficient state estimation in IoT-enabled distribution networks.

Findings

Achieves required QoS levels in cloud-based state estimation

Maintains estimation accuracy with local data transmission logic

Reduces latency and network load in smart grid scenarios

Abstract

This paper presents an IoT cloud-based state estimation system for distribution networks in which the PMUs (Phasor Measurement Units) are virtualized with respect to the physical devices. In the considered system only application level entities are put in the cloud, whereas virtualized PMUs are running in the communication network edge (i.e. closer to the physical objects) in order to have a certain degree of local logic, which allows to implement a bandwidth-efficient and smart data transmission to the involved applications in the cloud. The major contributions of the paper are the following: we demonstrate that a cloud-based architecture is capable of achieving the QoS level required by the specific state estimation application; we show that implementing a certain local logic for data transmission in the cloud, the result of the state estimation is not degraded with respect to the case of an estimation that takes place frequently at fixed intervals; we show the results in terms of latency and reduced network load for a reference smart grid network.