Design and Evaluation of a Lightweight Blockchain Framework for Secure Decentralised Energy Trading in Smart Grids
Aliyu Musa Kida1, Christoper Umera Ngene2, Jafaru Usman3, Stephen Bassi4
1Aliyu Musa Kida, Department of Computer Engineering, University of Maiduguri, Maiduguri, 1069, Nigeria.
2Dr. Christoper Umera Ngene, Department of Computer Engineering, University of Maiduguri, Maiduguri, Nigeria.
3Dr. Jafaru Usman, Department of Electrical and Electronics Engineering, University of Maiduguri, Maiduguri, Nigeria.
4Dr. Stephen Bassi, Department of Computer Engineering, University of Maiduguri, Maiduguri, Nigeria.
Manuscript received on 02 July 2026 | First Revised Manuscript received on 06 July 2026 | Second Manuscript Accepted on 11 July 2026 | Manuscript Accepted on 15 July 2026 | Manuscript published on 30 July 2026 | PP: 12-22 | Volume-15 Issue-8, July 2026 | Retrieval Number: 100.1/ijitee.I128615090826 | DOI: 10.35940/ijitee.I1286.15080726
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: The increasing usage of distributed renewable energy resources has rapidly increased the transition to decentralised smart grids. This is where secure and efficient peer-to-peer (P2P) energy trading is crucial. However, conventional blockchain-based energy trading schemes suffer from high computational overhead, communication latency, and limited scalability, making them unsuitable for resource-constrained Internet of Things (IoT) networks. This research proposes a lightweight blockchain framework that incorporates Hyperledger Fabric with Practical Byzantine Fault Tolerance (PBFT) consensus, ZigbeePro communication, and Long Short-Term Memory (LSTM)-based energy demand forecasting to facilitate secure and intelligent decentralised energy trading. The framework was evaluated using MATLAB/Simulink simulation, NS-3, Hyperledger Fabric, and a Raspberry Pi/ESP32 prototype. The results of the experiment show that the proposed framework achieved an average latency of 48.9 ms, throughput of 185 transactions per second, packet delivery ratio of 97.8%, and support for up to 250 IoT nodes while maintaining low energy overhead. The LSTM forecasting model attained an R² of 0.964 with a MAPE of 4.7%, delivering accurate demand prediction for intelligent energy allocation. Compared with centralised and Proof-of-Work blockchain models, the proposed framework enhanced communication efficiency, scalability, and security integrating while reducing computational cost. These results demonstrated that lightweight blockchain, low-power communication, and Artificial Intelligence-based forecasting provides a practical and scalable solution for decentralised energy trading for the next-generation smart grids.
Keywords: Blockchain, Smart Grid, Decentralised Energy Trading, Communication Efficiency.
Scope of the Article: Computer Science and Engineering