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Validation of Embedded State Estimator Modules for Decentralized Monitoring of Power Distribution Systems Using IoT

Rosvando Marques Gonzaga Junior¹, Sergio Márquez-Sánchez^2,3, Jorge Herrera Santos²

¹São Carlos School of Engineering, University of São Paulo, São Carlos 13566-590, Brazil.

Sensors (Basel, Switzerland)

|March 26, 2022

Summary

Decentralized architectures for real-time Power Distribution Systems (PDSs) reduce data transmission and computation. Lab validation confirms this approach using Embedded State Estimator Modules (ESEMs) for efficient PDS monitoring.

Keywords:

Internet of Things advanced measurement infrastructure distribution systems edge computing embedded systems smart meters state estimation

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Area of Science:

Electrical Engineering
Computer Science
Control Systems

Background:

Traditional centralized architectures for Power Distribution Systems (PDSs) face challenges in real-time operation due to high data transmission and processing demands.
Recent theoretical studies suggest decentralized architectures offer significant advantages for PDS operation, particularly in state estimation.

Purpose of the Study:

To provide laboratory validation for the advantages and feasibility of decentralized monitoring in PDSs.
To emulate realistic conditions and hardware setups for testing decentralized PDS operation.

Main Methods:

Development and implementation of an Advanced Measurement Infrastructure (AMI) prototype simulating a smart grid environment.
Integration of IoT and Edge Computing concepts using wireless communication modules for real-time information traffic emulation.
Laboratory development and implementation of a decentralized architecture utilizing Embedded State Estimator Modules (ESEMs) for real-time state estimation in lower voltage networks.

Main Results:

The decentralized architecture with ESEMs effectively managed information from smart meters.
Simulations on a 208-bus PDS demonstrated considerable reduction in data transit and computational requirements for real-time monitoring.
No loss of accuracy was observed in the state estimation process with the decentralized approach.

Conclusions:

Decentralized monitoring of PDSs using ESEMs is feasible and offers significant benefits over centralized systems.
The proposed laboratory setup and decentralized architecture successfully validate the reduction in data and computational load for real-time PDS monitoring.
This approach enhances the efficiency and scalability of smart grid operations.