Blockchain Papers

Abdullah Umar, Prashant K. Jamwal, Deepak Kumar, Nitin Gupta · 6 authors

No abstract is available for this record.

Gia Ky Huynh, Ajmery Sultana

The energy sector faces inefficiencies, fraud, and lack of transparency, while the traditional peer-to-peer (P2P) energy trading market faces challenges of trust, interoperability, and flexibility. This paper proposes an innovative solution leveraging blockchain technology to address these issues. By representing energy units as unique, verifiable Non-Fungible Tokens (NFTs), our aim is to create a transparent, secure, and efficient energy marketplace. Our architecture integrates a Web3 marketplace with smart contracts to manage trading transactions, NFTs to visualize energy, and a sophisticated loyalty program to incentivize user participation. Furthermore, the platform improves user accessibility through cross-chain token bridging via the Across Protocol, enabling seamless fund transfers from Layer 1 or other Layer 2 networks to the Base network. These features collectively reduce entry barriers and expand market participation. Using blockchain technology, our solution addresses the limitations of traditional systems, offering enhanced security, user engagement, improved efficiency, and simplified access to the energy marketplace.

Rhana Elsayed, Mohamed I. Ismail, Ahmed F. Ashour, Hesham A. Sakr · 6 authors

Cyber-physical Systems (CPS) are increasingly utilized by Smart Building Management Systems (SBMS) to achieve intelligent, energy-efficient operations. The significant energy footprint of buildings (approximately 40% of worldwide energy use) and the desire to improve sustainability without compromising occupant comfort are the primary drivers of this movement. However, complicated cybersecurity issues are also brought about by the close integration of Internet of Things (IoT) sensors, automated controls, and networked management. In this study, we provide a comprehensive examination of CPS-based smart building monitoring and control technologies, exploring how state-of-the-art sensors, data analytics, and Artificial Intelligence (AI)-powered decision engines are utilized to enhance responsiveness and energy efficiency. We present a comparison between contemporary CPS-enabled SBMS and conventional building management systems, emphasizing the enhancements in security, flexibility, and energy efficiency. A thorough analysis of energy optimization processes demonstrates how machine learning algorithms and feedback loops may dynamically strike a balance between efficiency and comfort. We also examine new security models being developed to defend these cyber-physical infrastructures against attacks. This survey is unique because it comprehensively covers recent CPS developments and identifies emerging trends that will influence next-generation smart building management, including blockchain, Decentralized Autonomous Organization (DAO)based decentralized management architectures, and federated learning for collaborative optimization. In addition to outlining substantial obstacles and future research opportunities, our findings highlight the crucial role that CPS plays in enabling safe, self-sufficient, and sustainable buildings.

Waqas Amin, Qi Huang, Jianping Li, Abdullah Aman Khan · 6 authors

An increase in the popularity of peer-to-peer energy trading in smart grids due to the massive integration of renewable energy sources demands effective and competitive pricing and energy allocation policies to ensure fairness within the market framework. Considering the scalability issues, technical complexity, and operational costs of distributed ledger technology such as blockchain, the reputation of the participants becomes a prominent factor to ensure trustworthiness, reduce risk, and increase market efficiency. This paper proposes a novel method to determine the reputation of participants within the energy market. Based on the evaluated reputation of the participants, an effective pricing method along with an energy distribution technique is devised by considering several market dynamics that significantly affect the pricing and energy allocation method. Extensive experiments have been conducted to validate the effectiveness of the proposed model. The results demonstrate that through the proposed model, the energy bills of the buyers can be reduced by 44%. This highlights the tangible benefits and practical applicability of the proposed approach in optimizing energy costs for consumers in the P2P energy trading ecosystem.

Farid Hamzeh Aghdam, Aleksandr Zavodovski, Mehdi Rasti, Éva Pongrácz

The energy domain worldwide is experiencing high transformative pressure due to the imperative of climate change and new opportunities brought by various rapidly evolving digital technologies. Particularly, this change is affecting smart grids (SGs), which are increasingly shifting toward utilizing renewable and distributed energy sources. The natural intermittency of these energy sources increases the complexity of SG operations, such as ensuring continuity of energy supply and demand response balancing. In mitigation of these challenges, the tools and complex approaches that digitalization can provide have shown themselves particularly advantageous. There is a solid body of work showing how technologies like the Internet of Things (IoT), distributed ledgers, edge and cloud computing, machine learning (ML), etc., can be applied to address a variety of technical and economic problems in the energy sector, emphasizing SGs. This paper presents the most comprehensive literature review to date on digitalization in renewable energy source-based SGs, synthesizing over 200 studies across data analytics, artificial intelligence and ML, digital twins, edge–fog–cloud computing, the IoT, advanced metering infrastructure, and distributed ledger technologies. Unlike previous reviews, which are often limited to a single technology or narrow application, this work provides a cross-technology synthesis linking technical and financial aspects, identifies consolidated research gaps, and proposes a unified research agenda. The review further highlights future trends, including large language models, 6G communications, and distributed autonomous organizations, and discusses their implications for both industry practice and academic research.

Suraphan Chantanasut

This study investigates the relationship between gas consumption and value transferred in Ethereum smart contracts, offering insights into resource utilization and efficiency within the blockchain ecosystem. Analyzing a dataset of 1,000 smart contracts, a moderate positive correlation r=0.45,p<0.05 was observed, indicating that higher gas consumption generally corresponds to larger financial transactions. The average gas consumption per contract was found to be 58,451,329.47 units, with a standard deviation of 20,123,456.89, highlighting significant variability in computational resource usage. Similarly, the average value transferred was 7,851.47 ETH, ranging from 0.001 ETH to over 100,000 ETH, showcasing the diverse financial applications of smart contracts. Efficiency analysis, measured as the ratio of value transferred to gas consumed, revealed an average efficiency of 0.00013 ETH per unit of gas, with some contracts achieving up to 0.01 ETH per unit of gas and others as low as 0.000007 ETH per unit of gas, reflecting varying levels of optimization. Outliers with disproportionately high gas consumption relative to value transferred were identified, suggesting inefficiencies or unique use cases. These findings underscore the importance of optimizing smart contract design to minimize gas costs and improve performance. Future research directions include functionality-specific analyses, anomaly detection, comparative studies across blockchain platforms, and exploring the economic implications of gas consumption. This work provides actionable insights for developers, researchers, and policymakers aiming to enhance the efficiency and sustainability of decentralized systems.

Ziyi Meng, Jing Li, Ming Zhu, Yuhong Yan

No abstract is available for this record.

Omidreza Heydaritafreshi, Mehran Hajiaghapour‐Moghimi, Ehsan Hajipour

No abstract is available for this record.

Mayank Arora, M V Gururaj, Ankush Sharma, Naveen Chilamkurti

The transition towards decentralized energy systems has spurred the need for innovative consensus mechanisms to facilitate efficient and transparent energy trading among prosumers. In response to this challenge, we propose a novel Proof of Energy Authentication and Contribution (PoEAC) consensus mechanism tailored for decentralized energy trading systems. PoEAC integrates cryptographic authentication and contribution verification to empower authenticated prosumers in the energy market. Prosumers authenticate themselves by proving ownership of energy-producing assets or storage devices, while demonstrating their contribution to the energy system through verifiable evidence of energy production or storage capacity. Leveraging cryptographic techniques such as zero-knowledge proofs and digital signatures, prosumers generate proofs of their authenticated status and contribution, which are evaluated by the consensus algorithm to validate energy transactions. The proposed model was simulated in MATLAB, with four prosumers over a 24hour horizon. Simulation results confirm that PoEAC successfully validates all legitimate energy transactions while rejecting 100 % of invalid or unauthorized trades. This paper presents the design and implementation of PoEAC, highlighting its advantages in enhancing trust, transparency, and incentivized participation in decentralized energy trading systems.

Norchene Moumni, Faten Chaabane, Fadoua Drira

This paper proposes a blockchain framework integrating smart contracts and machine learning to enable secure, decentralized anomaly detection in energy grids. We deploy Ethereum-based smart contracts to trigger localized alerts by postcode, validated on the Ausgrid dataset. Experimental results demonstrate the framework’s ability to achieve 94.5% anomaly detection accuracy while reducing false alerts by 30% through a two-stage machine learning pipeline. First, the MeanShift clustering algorithm identifies irregular consumption patterns using adaptive interquartile range thresholds, followed by supervised classification. Various algorithms are investigated, with and without SMOTE, to tackle the problem of dataset imbalance. The Proof-of-Stake (PoS) consensus mechanism reduces energy overhead by 99% compared to traditional Proof-of-Work (PoW), ensuring scalability for real-time grid management. By automating postcode-specific alerts and leveraging blockchain’s tamper-proof data storage, the framework enhances operational responsiveness and transparency for decentralized energy systems. This work bridges the gap between decentralized ledger technology and AI-driven analytics, offering a practical solution for secure, low-latency anomaly management in modern smart grids.

Jayesh Vijay Patil, Hanumantha Rao Bokkisam

This paper presents a blockchain-enabled decentralized autonomous organization (DAO) framework that leverages interconnected multilateral smart contracts to create revenue streams for decentralized token holders. The framework facilitates participation in energy arbitrage mechanisms using a battery energy storage system (BESS), enabling efficient and transparent value generation. In this framework, each token holder (shareholder) exercises their voting rights to manage the operation of the battery energy storage system (BESS) within the energy arbitrage mechanism. Decision-making is informed by historical electricity prices, forecasted prices, real-time market price, and the battery’s current state of charge. Token holders collectively control the battery through a consensus-based decision-making algorithm, determining its operational mode (charge, discharge, or float). This process is seamlessly facilitated by smart contracts, ensuring transparency and efficiency.

B. T. King, Srijib Mukherjee

Over the past few years, a strange industrial electricity customer has taken the industry by storm: Bitcoin mining. In 2021, the nascent Bitcoin mining industry, which had primarily been in China, shipped massive amounts of hardware and opportunity to capture global market share to the United States.

Antar Kumar Biswas, Masoud H. Nazari

This paper presents an optimal peer-to-peer (P2P) energy transaction mechanism leveraging decentralized blockchain technology to enable a secure and scalable retail electricity market for the increasing penetration of distributed energy resources (DERs). A decentralized bidding strategy is proposed to maximize individual profits while collectively enhancing social welfare. The market design and transaction processes are simulated using the Ethereum testnet, demonstrating the blockchain network's capability to ensure secure, transparent, and sustainable P2P energy trading among DER participants.

Nitima Malsa, Vimal Gupta, Rachna Jain, Sur Singh Rawat · 5 authors

The increasing global reliance on renewable energy, coupled with the strain on traditional electricity grids and limited access to power in rural areas, underscores the need for innovative solutions like Peer-to-Peer (P2P) energy trading platforms. This paper presents a hybrid Internet of Things (IoT) system designed for energy trading between prosumers (entities that both produce and consume energy), leveraging blockchain technology alongside AWS cloud infrastructure to ensure scalable and secure energy transactions. Our system integrates environmental sensors (solar, air) connected to microcontroller platforms like ESP32, facilitating real-time monitoring and management of energy production and consumption. Data from these devices is transmitted to AWS cloud architecture via IoT protocols such as MQTT and HTTP, ensuring secure, scalable storage, and reliable analysis. This robust architecture enhances real-time energy management, allowing prosumers to optimize energy usage. A key feature is the hybrid architecture combining decentralized Ethereum blockchain, which enables tamper-proof energy trading via smart contracts, and AWS cloud, which handles large-scale data processing. This dual system reduces reliance on centralized power grids, promotes energy independence, and supports decentralized energy markets. By using this platform, prosumers gain greater control over energy resources, promoting efficiency and sustainability while contributing to the future of decentralized energy economies.

Christoph Groß, Oliver Bringmann

The energy sector is experiencing a paradigm shift toward decentralized, renewable sources, necessitating efficient energy and data management solutions. In this paper, we propose methods to improve both scalability and storage efficiency within a Distributed Ledger Technology (DLT) based local energy trading framework. Our contributions include the improved use of directed acyclic graphs (DAGs) to manage Smart Contracts (SCs) separately, reducing the data retention burden on individual nodes, and implementing time based data pruning to enhance storage efficiency. We also demonstrate the scalability of our energy trading platform. Our results indicate significant improvements in storage usage and scalability, thereby supporting the long term viability and scalability of decentralized energy trading platforms in prosumer communities.

Heba Abdul-Jaleel Al-Asady, K. Priyanka, V. Vennila, M. Murali · 5 authors

In modern supply chains, visibility and sustainability is becoming dependent on energy-efficient and auditable data management frameworks. The use of blockchainbased auditing methods can yield transparent visibility and mechanized auditing capabilities. However, typical auditing solutions using blockchain come with significant energy resource-consuming overheads that are not viable in Industrial IoT (IIoT). In contrast, traditional routing methods do not concurrently account for energy consumption at multiple layers of complexity. In this paper, a novel framework consisting of Fuzzy Logic-Based Energy Aware Routing (FLEA-RPL) combined with the lightweight Internet of Things Application (IOTA) Tangle is proposed, for green supply chain auditing. This is done by first collecting the sensor data (temperature, location, and, residual energy) from the IIoT nodes. The data is preprocessed to receive a similar distribution for incoming sensor data and to filter out inconsistent anomalies. Moreover, FLEA-RPL uses fuzzy inference to assess and choose optimal parent nodes to route the data to nodes on the routing tree, for minimizing energy consumption, according to residual energy and, load to send the data. The routed data is then permanently logged onto a Tangle so that the route is immutable and, therefore, low power and energy data is permanently attached to the distributed ledger. The final step is that the intelligent compliance auditing module monitors the contents of the distributed ledger for violations of a certain Service Level Agreement (SLA) from the ledger. The proposed FLEA-RPLIOTA attained better results, when compared FLEA-RPL in terms of Residual Energy (97.74 %), Packet Loss Ratio (2.2 %) respectively.

F. A. Samiul Islam

Urban areas in the Global South are at the forefront of the climate crisis, contributing over 70% of global CO2 emissions while lacking access to intelligent, transparent, and equitable carbon governance systems. Existing carbon markets, plagued by opacity, centralization, and static MRV (Monitoring, Reporting, and Verification) practices, are inadequate for dynamically managing decentralized, sectoral emissions in rapidly evolving megacities. This research proposes a novel, AI-powered carbon market intelligence framework that integrates cutting-edge technologies: Long Short-Term Memory (LSTM) networks, Graph Neural Networks (GNNs), Deep Reinforcement Learning (DRL), blockchain-enabled smart contracts, federated learning (FL), digital twins, and explainable AI (SHAP, LIME). The system is modular, privacy-preserving, and designed for real-time urban-scale decarbonization, adaptive policymaking, and citizen-level participation. Using Dhaka, Bangladesh, a climate-vulnerable megacity, as the primary use case, and Nairobi as a secondary scalability testbed, this study simulates a comprehensive pipeline: IoT sensors stream data to digital twins; AI models forecast emissions and carbon prices; smart contracts trigger transparent offset issuance; and federated models ensure localized learning without compromising data sovereignty. The system achieves high predictive accuracy (R2 > 0.92), 27.6% emission reductions in waste-energy sectors, and 12.3% gains in offset ROI over static baselines. Smart contract execution remains under 4.5 seconds, with negligible energy use under Proof-of-Stake blockchain. The explainability layer enhances stakeholder trust and policy interpretability, while gamified P2P carbon trading and participatory digital twins democratize climate action. The framework aligns with global instruments, including the UNFCCC Enhanced Transparency Framework, Article 6 mechanisms, Verra and Gold Standard protocols, and ICAO’s CORSIA, positioning it for integration into national and voluntary carbon markets. Ethical safeguards address algorithmic bias, data privacy, system resilience, and governance decentralization via DAOs. A full AI sustainability audit quantifies environmental trade-offs, demonstrating that avoided emissions exceed compute footprints by orders of magnitude. This paper delivers the first end-to-end, federated-AI and blockchain-driven carbon governance system for urban infrastructures in the Global South. It enables a paradigm shift toward real-time, transparent, and just carbon markets, offering a scalable blueprint for Net Zero-aligned smart cities worldwide. The proposed architecture not only advances scientific frontiers but also lays the groundwork for high-impact funding, policy integration, and global replication.

Yiting Xiao, Md Moniruzzaman, Abdulsalam Yassine

The adoption of distributed energy resources (e.g., solar panels) is reshaping the energy landscape by enabling participants to trade energy efficiently. Electric vehicles (EVs) further improve this ecosystem by acting as mobile energy storage units that are capable of supplying power back to the grid. However, existing energy transaction systems heavily rely on centralized intermediaries which may lead to insecure trading transactions and limited transparency. To address these challenges, this study proposes a blockchain-based Peer-to-Peer (P2P) energy trading system that uses smart contracts for secure and automated transactions between participants. In this system, the blockchain ensures tamper-proof records, while smart contracts automate key processes such as verifying energy availability, executing payments, and enforcing agreements by eliminating trusted intermediaries. Furthermore, we introduce a penalty mechanism to prevent fraudulent claims and ensure sellers meet their commitments. We evaluated the scalability, security, and economic feasibility of the proposed system for decentralized energy trading using the Ethereum local blockchain network.

M. Zulfiqar, Muhammad Babar Rasheed, Daniel Rodríguez, María D. R‐Moreno

Contemporary power grid systems increasingly rely on sophisticated energy trading mechanisms to optimize resource allocation and operational performance. While prior studies have examined the coordination roles of energy intermediaries and utility operators, particularly through distributed ledger technologies that ensure data provenance and transaction verifiability in decentralized energy marketplaces, significant security vulnerabilities persist. Notably, fraudulent practices by energy suppliers characterized by payment collection without corresponding energy delivery pose substantial risks to market integrity and participant confidence. This research presents the Blockchain-based Energy Trading with Multi-Factor Trust Framework (BC-ET-MF), a novel architecture that addresses critical security deficiencies through advanced cryptographic protocols and consensus mechanisms. The framework utilizes anonymous credential systems to safeguard participant privacy while implementing time-locked commitment schemes that ensure transaction fairness and verifiability. The architecture incorporates granular access control mechanisms for secure service orchestration and establishes a consortium blockchain infrastructure among energy intermediaries to facilitate distributed transaction validation and immutable record-keeping. To mitigate computational overhead associated with conventional consensus algorithms, we introduce a Proof-of-Verifiability protocol that dynamically calibrates to real-time energy production and consumption patterns. This adaptive mechanism reduces system resource requirements while maintaining security guarantees. Experimental evaluation demonstrates that BC-ET-MF achieves substantial performance improvements: energy consumption reduction of 43.0 %, peak-to-average ratio optimization from 8.27 to 3.21 and 5.88 under 25 % and 50 % demand reduction scenarios respectively, and establishment of 92.5 % participant trust levels. The framework additionally yields 37.6 % transaction latency reduction while preserving user anonymity and enabling comprehensive audit capabilities, thus establishing a secure, efficient, and trustworthy energy trading ecosystem.

K Sujit, Komala Chowdenahally Ramaswamy, Siva Ramkumar M, Jayant Giri · 5 authors

Research and development in the vehicle industry have emphasized the potential for advancing electric transportation that is highly efficient, secure, and sustainable. The electric vehicle (EV), powered by renewable energy sources and equipped with high-efficiency electric motors and controls, offers a practical, dependable, and ecologically friendly urban transportation system. EVs operate using a battery that is equipped onboard. Practical and dependable system operation relies heavily on managing and monitoring batteries. Nevertheless, the market for electric vehicles has experienced a decline in growth due to their limited lifespan and high price. To enhance the system's efficiency and lifespan, substantially improving the battery management aspect is imperative. In this research, the Internet of Things (IoT), machine learning (ML), and Blockchain (BC) technologies are used to develop an energy-efficient EV battery management system (BMS). The IoT sensors are attached to the electric vehicles to collect data such as the charging level, the distance that must be driven, and the position of the electric vehicles. This information was saved and processed by a database, then inputted to the LightGBM classifier to determine the cost of charging. After that, it was processed by the power scheduling approach (PSA) to determine the space and time of charging that is closest to a particular electric vehicle and the charging site. At last, this information is saved in blocks to prevent electric vehicles from being misrouted and ensure that pricing transactions between users and charging stations are conducted securely using BC. The results demonstrate that the research model provided enhanced EV-BMS with an accuracy rate of 96.52% and that it retains a communication overhead that is 12% lower compared to the other models.

Oluwaseun O. Tooki, Olawale Popoola

The current hike in electricity demand, deterioration of electrical grids, and climatic conditions have necessitated the push for technology to enhance energy efficiency, optimize energy usage, and minimize greenhouse gas emissions. The Transactive Energy System (TES) is a highly favoured technology designed to provide solutions for optimizing energy usage since it incorporates economic and dynamic control mechanisms to balance the amount of energy generated and supplied. Cost savings present a clear advantage of TES for consumers, translating to reduced bills, and the platform enables customers with Distributed Energy Resources to trade their excess energy, transforming consumers into prosumers. However, energy trading in TES comes with challenges such as maintaining a dynamic balance between supply and demand, as well as issues of privacy, trust, and resilience. Blockchain Technology (BT)-based TES can address these challenges due to its reliability, transaction transparency, and robust encryption methods. However, BT has its shortcomings that need to be addressed. Therefore, this research analyzes the opportunities, limitations, challenges, and complexities of implementing blockchain-based energy trading platforms within a decentralized TES. This review adopted a systematic approach, known as the Preferred Reporting Items for Systematic reviews and Meta-Analyses, to provide in-depth insights into the review purpose, methodology, findings, recommendations, and future research directions. It was observed from the review that certain challenges underscore the necessity for standardization in BT-based TES implementation. Moreover, it was discovered that decentralizing the TES energy trading infrastructure promotes energy democracy and that adopting fast computing techniques will facilitate digital and intelligent operations in TES. It was also found that the Directed Acyclic Graph-based distributed ledger may soon replace generic blockchain, as it can simultaneously process large micro-transactions in P2P networks. It is observed that implementing a peer rating mechanism in the energy trading network will enhance participants' commitment to their reputational standing in the market, while adapting analytical modelling for performance evaluation of this energy solution could equally be encouraged.

Wenpeng Luan, Longfei Tian, Bochao Zhao, Qian Ai

No abstract is available for this record.

Ala’a Shamaseen, Mohammad Qatawneh, Basima Elshqeirat

Traditional systems in real life lack transparency and ease of use due to their reliance on centralization and large infrastructure. Furthermore, many sectors that rely on information technology face major challenges related to data integrity, trust, and counterfeiting, limiting scalability and acceptance in the community. With the decentralization and digitization of energy transactions in smart grids, security, integrity, and fraud prevention concerns have increased. The main problem addressed in this study is the lack of a secure, tamper-resistant, and decentralized mechanism to facilitate direct consumer-to-prosumer energy transactions. Thus, this is a major challenge in the smart grid. In the blockchain, current consensus algorithms may limit the scalability of smart grids, especially when depending on popular algorithms such as Proof of Work, due to their high energy consumption, which is incompatible with the characteristics of the smart grid. Meanwhile, Proof of Stake algorithms rely on energy or cryptocurrency stake ownership, which may make the smart grid environment in blockchain technology vulnerable to control by the many owning nodes, which is incompatible with the purpose and objective of this study. This study addresses these issues by proposing and implementing a hybrid framework that combines the features of private and public blockchains across three integrated layers: user interface, application, and blockchain. A key contribution of the system is the design of a novel consensus algorithm, Proof of Energy, which selects validators based on node roles and randomized assignment, rather than computational power or stake ownership. This makes it more suitable for smart grid environments. The entire framework was developed without relying on existing decentralized platforms such as Ethereum. The system was evaluated through comprehensive experiments on performance and security. Performance results show a throughput of up to 60.86 transactions per second and an average latency of 3.40 s under a load of 10,000 transactions. Security validation confirmed resistance against digital signature forgery, invalid smart contracts, race conditions, and double-spending attacks. Despite the promising performance, several limitations remain. The current system was developed and tested on a single machine as a simulation-based study using transaction logs without integration of real smart meters or actual energy tokenization in real-time scenarios. In future work, we will focus on integrating real-time smart meters and implementing full energy tokenization to achieve a complete and autonomous smart grid platform. Overall, the proposed system significantly enhances data integrity, trust, and resistance to counterfeiting in smart grids.

Arvind Singh, Rahul Kumar, Mohit Bajaj, B. Hemanth Kumar · 5 authors

The rapid advancement of smart grids, propelled by the integration of distributed energy resources (DERs) and renewable energy technologies, has exposed key challenges such as interoperability, standardization, and data security. These issues impede the efficient operation and scalability of smart grid applications, particularly in enabling decentralized, real-time energy trading and demand response management. Effective management of DERs and demand response systems relies heavily on seamless information exchange, data-driven decision-making, and robust digital communication frameworks to maintain system stability and operational efficiency. To address these challenges, this study presents the Blockchain Consortium-Based Demand Energy Trading System (BC-DETS), a blockchain-powered framework designed to enhance interoperability, security, and standardized energy trading mechanisms within smart grid ecosystems. Comprehensive simulations have validated the effectiveness of BC-DETS using Key Performance Indicators (KPIs) such as transaction latency, demand response participation rate, operational cost reductions, and overall grid efficiency under diverse scenarios. Findings reveal a 35% boost in grid efficiency through optimized energy distribution and minimized energy losses, alongside a 15% decrease in operational costs due to reduced transaction overhead and improved energy allocation. Moreover, demand response participation rates increased by 40%, facilitated by secure and transparent blockchain-enabled real-time energy transactions. These numerical findings underscore blockchain’s transformative potential in enhancing the scalability, security, and inclusivity of smart grids, establishing a foundational platform for future advancements in blockchain standardization and sustainable energy management solutions.