Fraud Incidence Response in Power Sector Using Optimized Consensus Blockchain Technique
Abstract Every year, the global power sector losses $80 billion globally due to non-technical losses, and one major contributor to this problem is fraud across the Energy Supply Chain Management System (ESCMS). Related works reviewed has positioned blockchain as a reliable solution to help combat fraud across global ESCMS; however the research gap is that traditional consensus algorithms like Proof of Authority (PoA) fall short of reliability, flexibility and delay in fraud incidence response. To solve this problem, the aim of this paper is fraud incidence response in power sector using optimized consensus blockchain technique. The methodology is experimental. The method of design began with modeling of the ESCMS framework, modeling of improved blockchain using novel dynamic validator algorithms, integration of the with the ESCMS, implementation as software, validation with real-world grid import report data collected from the Enugu State Electricity Distribution Company (EEDC). The results when tested showed that when fraud is carried at the recorded transaction, there is real-time incidence response at the node where is fraud was perpetrated. Comparism of the improved PoA with existing algorithms considering key attributes such as trust, multi validator and real-time incidence response showed that our system competes among the best, nut the most reliable due to its ability for real-time fraud detection.
Authors
- Udeh Chukwuma Callistus
- Ebere Uzoka Chidi
- Nwamuo Chibuzo Udochukwu
- Ozoani Uchechukwu Isaac
- Mbamalu Ikenna Chuddy
- Eze Marcel Nduka
- Lois Onyejere Nwobodo
Institutions
- University of Nigeria (NG)
- Enugu State University of Science and Technology (NG)
- Milton Keynes Hospital (GB)
- Caritas University (NG)
Publication Details
- Journal
- Zenodo (CERN European Organization for Nuclear Research)
- Published
- 2026-05-16
- DOI
- https://doi.org/10.5281/zenodo.20229269
- Primary Topic
- Electricity Theft Detection Techniques
- Type
- article
- Field-Weighted Citation Impact
- 0.00