Energy Efficient Optimization of Current Transformer Error Compensation in Smart Grids Using Sparse Coding and Blockchain-Secured IoT Framework
DOI:
https://doi.org/10.13052/dgaej2156-3306.40565Keywords:
Current transformer error modeling, sparse coding, blockchain security, IoT-based power monitoring, optimization algorithms, smart grid instrumentationAbstract
In the advancement of smart grids and renewable energy systems, the accuracy and security of CT measurements become paramount in guaranteeing reliable power monitoring and protection. This work proposes an intelligent CT error compensation mechanism using Sparse Coding algorithms in conjunction with a blockchain-secured IoT architecture. Sparse representations extracted from real-time CT signals model and identify nonlinear measurement errors in terms of changing load and harmonic conditions. With the aim of minimizing reconstruction loss, the typical parameters of the sparse dictionary are fine-tuned using the Whale Optimization Algorithm (WOA). Further, the blockchain records and timestamps measurement data in a manner immune to tampering from distributed CTs in different substations, thereby assuring transparency and compliance in energy metering. The system achieves a 42.1% reduction in the Mean Absolute Error (MAE) of the measurements, 97.6% Signal Reconstruction Accuracy (SRA), and less than 4.2 milliseconds in communication latency across distributed CTs. Model simulation and validation are carried out using MATLAB Simulink in CT error modeling and Hyper ledger Fabric-based Blockchain integration. This approach provides a scalable, smart, secure method for error-containment of the transformers engaged in the next-generation smart grid surveillance and verification.
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