Jul 2026· International Journal of Innovative Technology and Exploring Engineering· 0 citations· 13 references
TL;DR
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-based energy demand forecasting to facilitate secure and intelligent decentralised energy trading.
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 percent, 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 percent, 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 while reducing computational cost. These results demonstrated that integrating 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.
A decentralized, open, and scalable P2P power exchange is necessary due to the increasing dispersion of renewable energy sources. This study presents a blockchain-based design for green power trade and data sharing that addresses sustainability, privacy, trust, and scalability. A consensus method called Hybrid Proof-of-Energy Contribution (H-PoEC) uses adaptive trust scores and verifiable renewable energy contributions to choose validators on the fly. As a result, validation delays are reduced, and the process is made more equitable and eco-friendlier. Without compromising privacy by disclosing smart meter data, Zero-Knowledge Energy Credential (ZKEC) programs verify that renewable energy sources fulfill carbon criteria. Merkle-compressed Energy Certificates (MECs) reduce the amount of data stored on the blockchain without compromising data security. We constructed a blockchain testbed for a consortium using 500 prosumers, real solar output, and dynamic market interactions. Compared with Practical Byzantine Fault Tolerance (PBFT) and Tendermint, the proposed method achieves 35–48% higher throughput and a 32% reduction in block finalization delays in testing. Under duress, it can handle 2,000 Transactions Per Second (TPS). under peak load, 1,000 TPS. ZKEC proof files are 41% smaller after MEC compression, and monthly storage per prosumer drops from more than 50 MB to 14–16 MB. Market-level testing showed 18–24% more renewable energy, 37% less settlement delay, and a 50% lower dispute rate than with centralized trading. These findings show that the system may be used in the future for decentralized power markets that need to be scalable, protect privacy, and use less energy.
Hai-Fei Yuan, Nan Jiang· Journal of Engineering, Proj...· 0 citations
The growing adoption of renewable energy and small-scale power producers has increased the need for reliable and transparent peer-to-peer (P2P) energy trading. Traditional centralized markets often struggle with high transaction fees, limited transparency, and a greater risk of manipulation, which restrict efficient energy distribution. To overcome these issues, this study presents a decentralized P2P trading framework that implements a fully functional blockchain-based trading system with smart grid simulation and demonstrates a prototype machine learning forecasting module (Random Forest, 84% accuracy) designed for future integration. The trading mechanism is developed using Ethereum smart contracts and a custom ERC-20 token, the TUM Energy Coin (TEC), enabling secure and traceable energy exchange. System security is strengthened through dual confirmation steps, role-based access control, and consensus-driven market clearing. A double-sided auction model is used to match buyers and sellers fairly. Real-time grid behavior such as fluctuating loads, prosumer generation, and consumer demand is modeled using MATLAB Simulink to reflect realistic operating conditions. To enhance decision-making, a Random Forest model is integrated for load forecasting and dynamic pricing, achieving an accuracy of 84%. The simulation results show improved transaction throughput, more stable pricing, and strong resilience against false-data injection attacks. The primary novelty of this work lies in (1) an entirely operational and validated blockchain-trading system simulation with synchronized time using Simulink, (2) a working Random Forest forecasting tool demonstrating feasibility for incorporation in the future, and (3) an analysis of the system’s robustness in the case of FDIA attacks. The authors point out that the ML component used is a prototype and not yet integrated into the functioning block chain.
Sameen Fatima, M. Arshad· Sustainability· 0 citations
The growth of the Internet of Things (IoT) has introduced significant security challenges, mainly due to the resource constraints of devices and the limitations of centralized architectures. This paper proposes a blockchain-based Zero-Trust framework for secure and scalable IoT systems. The approach is architecture-agnostic and combines decentralized identity management, hybrid data storage, and edge-assisted computation. To optimize resource usage, raw data are stored off-chain while cryptographic hashes are anchored on the blockchain, ensuring integrity and immutability. A Merkle tree structure is employed to aggregate data efficiently, reducing communication overhead and blockchain transaction costs. Experimental results demonstrate that lightweight cryptographic mechanisms, combined with Merkle-based aggregation, provide strong security guarantees with low energy consumption. The proposed framework achieves improved scalability, robustness, and efficiency, making it suitable for resource-constrained IoT environments.
Florian Bonelli, Alexandre dos Santos Roque, E. P. de Freitas· International Conference on...· 0 citations
An optimal choice of consensus algorithm and type of blockchain, based on security, energy consumption and computing resources is proposed, which will enable the design of microgrid architectures and components that are compatible with decentralized cybersecurity technologies without affecting their operation.
Benedict Djouboussi, Elie Fute Tagne, G. Sèmassou· Journal of Hardware and Syst...· 0 citations
Rising energy demands, the proliferation of sustainable and renewable energy sources, are calling for a new perspective on conventional energy system management. this paper reports how blockchain technology can, through its decentralized and secure nature, enable transparent, automated and peer-to-peer (P2P) energy transactions. We conduct a comparative evaluation of BC applications in three diverse domains: renewable energy, smart grid and Microgrid, and P2P trading platforms. This article discusses different types of blockchains (public, private, consortium), consensus protocols, and their effect on scalability, security, and economic accessibility. The main takeaway is that public blockchains are very transparent but have scalability issues, whereas private and consortium blockchains are more scalable but less decentralized. The system gets more intelligent and smarter with the integration of AI and IOT. Although regulatory and interoperability challenges are being worked out, blockchain could have a significant impact on the industrial energy grid. the article closes with a discussion about how blockchain as part of a wider digital transformation could lead to ultimately more autonomously run and sustainable energy system.
Minatallah El Labbakh, Amina Aghanim, H. Chekenbah et al.· EPJ Web of Conferences· 0 citations
The proposed BlockSafeNet framework achieved significant improvements in secure IoT communication, privacy preservation, and AI-driven cyber threat detection within smart city infrastructures, providing a positive impact on the SC ecosystem.
Kanika Duggal, Gi-Chon Park· Telecom· 0 citations
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