The world's need for energy is rising due to factors like population growth, economic expansion, and technological breakthroughs. However, there are major consequences when gas and coal are burnt to meet this surge in energy needs. Although these fossil fuels are still essential for meeting energy demands, their combustion releases a large amount of carbon dioxide and other pollutants into the atmosphere. This significantly jeopardizes community health in addition to exacerbating climate change, thus it is essential need to move swiftly to incorporate renewable energy sources by employing advanced information and communication technologies. However, this change brings up several security issues emphasizing the need for innovative cyber threats detection and prevention solutions. Consequently, this study presents bigdata sets obtained from the solar and wind powered distributed energy systems through the blockchain-based energy networks in the smart grid (SG). A hybrid machine learning (HML) model that combines both the Deep Learning (DL) and Long-Short-Term-Memory (LSTM) models characteristics is developed and applied to identify the unique patterns of Denial of Service (DoS) and Distributed Denial of Service (DDoS) cyberattacks in the power generation, transmission, and distribution processes. The presented big datasets are essential and significantly helps in identifying and classifying cyberattacks, leading to predicting the accurate energy systems behavior in the SG.
The integration of blockchain technology into smart grids represents a transformative approach to addressing key challenges in modern energy systems, particularly focusing on enhancing security, efficiency, and resilience. Smart grids, enabled by advanced communication and control technologies, aim to revolutionize the traditional energy grid by facilitating real-time monitoring, automated control, and optimized energy distribution. However, these systems are susceptible to various vulnerabilities, including centralized control points, data manipulation, and cyberattacks, which threaten the security and reliability of energy supply. Blockchain technology offers a decentralized, immutable, and transparent framework that can significantly enhance the security, efficiency, and resilience of smart grids. By leveraging blockchain's cryptographic mechanisms and distributed ledger technology, smart grids can ensure secure authentication, authorization, and transaction management, mitigating risks associated with unauthorized access and data manipulation. Moreover, blockchain enables peer-to-peer energy trading, allowing consumers to directly exchange energy with each other, thereby enhancing efficiency by optimizing energy utilization and reducing transmission losses. Furthermore, blockchain's decentralized nature decentralizes control and data management functions, enhancing the resilience of smart grids against single points of failure and malicious attacks. This work presents an overview of the integration of blockchain technology in smart grids and its potential to enhance security, efficiency, and resilience in modern energy systems. Through a comprehensive exploration of blockchain-based solutions, this paper aims to provide insights into the transformative impact of blockchain technology on the future of energy grids and pave the way for a more secure, efficient, and resilient energy infrastructure.
Paul Michael Custodio, Made Adi Paramartha Putra, Jae‐Min Lee, Dong‐Seong Kim
Transmission lines experience the most faults out of all elements in the smart grid. Identifying the type of fault and where it occurs allow for faster response time and higher reliability for the overall system, however smart grids also experience cyber-physical attacks on data security. This study develops TLFed, a federated learning-based fault location and classification algorithm, utilizing 1-dimensional convolutional neural network (1D-CNN) and long-short term memory (LSTM) for the local client system architecture. With the use of TLFed, the system data are decentralized increasing security. The performance of TLFed is evaluated on accuracy, precision, recall, f1-score, and time-cost and is compared to a centralized set-up. The results of the evaluation show that TLFed's fault location and detection inference have relatively high performance with relatively cheap time-cost. Future works of this research aims for blockchain integration and smart contract deployment.
Palarapu Saket, P. Jyothi, Arasada B Venkata Ayush Patnaik, Nagidi Chaithanya Vardhan Reddy · 5 authors
Ethereum has become one of the most popular blockchains in the world ever since its inception. There are now over 207 million Ethereum accounts and more than 6000 blocks are mined every day. Its fame also attracts various kinds of frauds so it's crucial to detect these frauds to keep Ethereum network sustainable and healthy. The main aim of the paper is to compare various fraud detection methods, besides trying to minimize false positives, and finally suggest the model best suitable for the task of fraud detection in Ethereum transactions by using various evaluation metrics.
This proceeding volume has been retracted from the publication because we found some solid reasons to believe that it has infringed our integrity criteria and now presents a risk for our journal and scholarly science in general. Different types of malpractice are involved, in particular citation manipulation and inappropriate references. We are extremely concerned by such malpractice which considerably impacts the image of our title and our Publisher’s reputation. For further details, please refer to our publishing ethics policies . If you have any questions, please contact us at contact@webofconferences.org See the retraction notice E3S Web of Conferences 505, 00001 (2024), https://doi.org/10.1051/e3sconf/202450500001
In Peer-to-Peer (P2P) energy trading for the smart grid, secure and efficient information exchange is essential to protect against privacy risks and cyber threats. This paper introduces a multi-stage information protection scheme that safeguards data privacy, message authentication, and confidentiality in a continuous double auction (CDA)-based trading environment. The scheme functions across three phases: (1) In the home energy data collection stage, short-key homomorphic encryption within a decentralized framework secures user data. (2) During trading, an encryption-signature (E-S) model ensures secure transmission of sensitive bidding information from prosumers. (3) In the implementation phase, a decentralized monitoring system detects and prevents node compromise attacks on power measurements. Evaluations highlight the scheme’s computational feasibility, low time costs, and resilience against cyber-attacks, with tests on the IEEE 39-bus distribution network confirming its security. Furthermore, this scheme addresses limitations of traditional, operator-reliant methods in microgrids. With zero-knowledge proof-based authentication and homomorphic encryption for private energy pricing, the framework uses a lightweight, tree-chained transaction ledger to ensure data integrity. Tests confirm the framework’s support for secure, private energy trading with high accuracy and minimal delays. Lastly, the scheme addresses security and privacy challenges of IoT-integrated smart meters, critical for global energy management but vulnerable to data breaches. Through differential privacy-based aggregation and distributed data validation, the IoT model protects consumer privacy and ensures data integrity. In conclusion, this multi-faceted protection scheme strengthens privacy and security in P2P energy trading for the smart grid, enhancing data protection, system reliability, and user confidence in a decentralized energy landscape.
Aakanksha Bedi, J. Ramprabhakar, R. S. Anand, U Kumaran · 6 authors
Smart grids (SGs) are technology-powered electricity networks that support bidirectional power and data flows. This allows real-time monitoring of demand and enhances the grid’s capability to dynamically adjust the generation and reduce the gap between supply and demand. However, implementing a smart grid in the power network comes with its own set of security challenges, such as cyber-security, distrust in participants, and lack of customer engagement due to various cyber-attacks. Such cyber-attacks will create distrust among consumers/prosumers to adopt the smart grid and distributed energy resources (DER) framework. To circumvent this, a blockchain-supported hybrid authentication and handshake algorithm (BSHAHA) for smart grids is proposed in this work, which authenticates data communication between peer-to-peer, aggregators, virtual power plants, and the grid. The algorithm was developed incorporating elliptic-curve cryptography (ECC) and advanced encryption standards (AES) to enhance privacy and session security. The proposed algorithms are verified and tested using formal cyber-security tools, such as the Random oracle model and AVISPA as well as by informal security analysis. Furthermore, to simulate a real-time test environment, this paper utilized ns-3 network simulator to simulate different smart meter scenarios, and the proposed algorithms are tested for power consumption and scalability, and results are presented. Moreover, blockchain simulation was first done in the local blockchain using Ganache and Truffle IDE and later using the Holesky Ethereum test network and remix-IDE. Lastly, this paper presented a comparison analysis of power consumption for different consensus mechanisms.
Jan 1, 2024·Proceedings of the ... Annual Hawaii International Conference on System Sciences/Proceedings of the Annual Hawaii International Conference on System Sciences
Ali Menati, Yuting Cai, Rayan El Helou, Chao Tian · 5 authors
We model the operation of a cryptocurrency mining facility with heterogeneous mining devices participating in ancillary services as an optimization problem. We propose a general formulation for the cryptominers to maximize their profit by strategically participating in ancillary services and controlling the loss of mining revenue, which requires taking into account the disparity in the efficiency of the mining machines. The optimization formulation is considered for both offline and online scenarios, and optimal algorithms are proposed to solve these problems. As a special case of our problem, we investigate cryptominers' participation in frequency regulation, where the miners benefit from their fast-responding devices and contribute to grid stability. Simulation results based on real-world Electric Reliability Council of Texas (ERCOT) traces show more than 20\\% gain in profit, highlighting the advantage of our proposed algorithms.
N. B. Sai Shibu, Aryadevi Remanidevi Devidas, S. Balamurugan, Seshaiah Ponnekanti · 5 authors
Power outages can severely affect individuals, businesses, and communities, leading to disruptions, economic losses, and safety risks. The existing power recovery strategies often fail to adequately address the challenges associated with such outages. These challenges encompass a range of complexities, including resource allocation disparities, efficient prosumer integration, energy demand variability, and isolated generators. This paper presents a microgrid-centric power recovery strategy that leverages IoT, blockchain, smart contracts, and optimisation techniques for peer-to-peer energy sharing within the microgrid. The proposed strategy comprehensively addresses the challenges associated with the existing power recovery strategies. The paper outlines the system architecture for IoT and blockchain-enabled microgrids, discusses the mathematical modelling for energy sharing, and explores cost-optimal power restoration strategies. An incentive mechanism motivates prosumers to support restoration strategies during outages. Furthermore, the paper describes a blockchain smart contract facilitating peer-to-peer energy exchange in regions affected by power outages. This approach can mitigate the disruptive impact of power outages by providing reliable and community-centric power recovery solutions. Through validation with real-world data from our university’s distribution grid test bed, Mean Time To Recover (MTTR) analysis and performance evaluations using the Hyperledger Caliper benchmark tool, this paper demonstrates its feasibility and effectiveness, paving the way for enhanced power recovery strategies and increased resilience in the face of energy disruptions.
The massive installation of smart meters on the customer side plays an important role in the collection and analysis of multi-user data. However, the current way of power grid collecting electricity data is consistent with the centralized grid control, and this way cannot cope with the new demand of multiparty data interaction and integration in the future. Blockchain technology integrates cryptography, distributed ledger technology and data sharing, which can enhance the security of power measurement data. To improve the performance of power data transmission and transaction, this paper combines blockchain smart contracts with the practicality in the field of power measurement, and proposes a smart contract based on the identification of hydrogen energy users, which analyzes the nodes containing hydrogen energy and identifies different nodes to complete the contract.
Amir-Saeed Es’Haghi, Ebrahim Afjei, Abbas Marini, Maziar Karimi
In recent years, the mining of cryptocurrencies has raised concerns due to its high profitability and secure environment, especially in countries with low energy prices. These concerns have resulted in a range of problems, including increased network load, electricity theft, harmonic distortion in the network, and a degradation in power quality, as well as an inaccurate estimation of load behaviors. This article presents a new approach that utilizes the concept of harmonic state estimation and unique characteristics of mining loads to identify unauthorized mining farms at the distribution network levels. Since miners are based on electronic power switching devices, they are recognized as harmonic-polluting loads. Using measurements and harmonic state estimation, it becomes possible to identify the potential locations of these loads. The proposed approach was implemented in DigSILENT software and tested on an 18-bus IEEE network. The results demonstrate the effectiveness of the proposed method in identifying the locations of harmonic loads from mining operations, detecting unauthorized energy consumption.
Marco Gerardi, Francesca Fallucchi, Fabio Orecchini
The growing adoption of renewable energy sources and the need for more efficient and secure energy grids are revolutionizing the energy sector. Electricity monitoring becomes an issue of utmost importance, as current traditional energy meters have several problems in terms of lack of transparency, very high operational costs, and the possibility of being easily tampered with. This paper proposes a new system for electricity production metering that leverages blockchain and IoT for decentralized and secure data recording while protecting user privacy and reducing operational costs. The architecture results in improvements over the traditional energy meter. The system also contributes to the generation of big data that is reliable, traceable, error-proof, and highly resistant to cyber attacks. The architectural project outputs are a smart energy meter, a smart contract on the Ethereum blockchain, and a decentralized application to manage the information recording. The experimental prototype outcomes confirm the use of these new technologies to improve energy metering, enhancing efficiency, transparency, and traceability, with reduced costs and increased user privacy.
: Power generation in today’s world is of utmost importance, due to which blockchain is used for the categorization and formation of decentralized structures. This paper has proposed decentralized energy generation using a nester, i.e., energy sharing without third-party intervention. Decentralized blockchain technology is applied to ensure power sharing between buyer and seller, and also to achieve efficient power transmission between prosumer and consumer. Energy management is associated with controlling and reducing energy consumption. Blockchain technology plays a major role in distributed power generation, for example, power-sharing (solar and wind energy), price fixation, energy transaction monitoring, and peer-to-peer power-sharing. These are operations performed by blockchain in renewable power generation. Solar power generation using blockchain technology can obtain an impact resting upon the power generation system. Distributed ledger is the key area of blockchain technology for recording and tracking each transaction in the distribution system to improve the efficiency of the overall transmission system. A smart contract is another important tool in the blockchain technology, which is issued to confirm an assent between buyer and seller before starting any energy transaction without external intervention and also to avoid time delay. Maximum power point tracking is conducted in PV cells using blockchain technology. Blockchain influences energy management systems to improve the utilization of energy, optimize energy usage, and also to reduce the cost.
Sama Almubarak, Hasan Ibrahim, Dev Singhania, Prasad Enjeti
This paper presents an in depth study of electric energy consumption and power quality analysis in Bitcoin mining facilities in Texas. The study includes energy consumption, voltage, current, power and current harmonics analysis from measured data on both grid connected and standalone facilities (powered by flared gas). Additionally, these results are also compared to the data gathered on an identical laboratory mining machine. Since large MW range Bitcoin mining loads are termed as "flexible loads" by the grid operators, the paper discusses examples of their potential role in participating in ancillary services to help stabilize the grid. Laboratory test results on voltage ride-through of Bitcoin machines is also presented and discussed. Analysis is also included on how large Bitcoin mining facilities can earn substantial additional revenue via their participation in ancillary services. Finally experimental data collected on a 3.5 kW S19 Pro Bitcoin miner installed in the laboratory and a 2.2 MW commercial mining facilities is tabulated and discussed.
In today’s smart communities, small-scale energy systems are essential for sustainable development and efficient resource management. However, ensuring the confidentiality, safety, and accurate prediction of energy consumption patterns in energy trading is a major challenge. To address these issues, an innovative solution that synergistically combines two cutting-edge technologies: blockchain and machine learning is proposed. This paper unveils a novel approach that harmoniously merges blockchain with the Recalling-Enhanced Recurrent Neural Network (RERNN) to revolutionize energy trading systems called ‘Blockchain-Enhanced Energy Trading with Recalling-Enhanced Recurrent Neural Network (BET-RERNN).’ Data from IoT-enabled smart devices is securely stored in blockchain blocks, ensuring data integrity and immutability. Blockchain’s decentralized nature creates a trust-less environment for energy trading, protecting the privacy and anonymity of participants while maintaining transparency. At the heart of our system lies the advanced machine-learning capabilities of the RERNN model. By processing the data stored on the blockchain, RERNN accurately predicts optimal power generation for small-scale energy systems, enabling smart communities to make informed decisions and optimize their energy consumption. The BET-RERNN scheme provides a plethora of strengths. First, participants can securely engage in energy trading without compromising sensitive information, fostering a more resilient and efficient market. Second, blockchain technology ensures that all energy-related data is protected from tampering and unauthorized access, ensuring system reliability and trust. An in-depth comparison of RERNN’s performance to traditional General Regression Neural Network (GRNN) and Gradient Boost Decision Tree (GBDT) methods is conducted. To verify the strategy’s effectiveness, MATLAB simulations are employed, demonstrating its real-world applicability and scalability. By combining blockchain and machine learning, a secure and privacy-preserving smart community is established, promoting sustainable energy practices for a greener future.
Ziqiang Xu, Ahmad Salehi Shahraki, Carsten Rudolph
The smart grid optimises energy transmission efficiency and provides practical solutions for energy saving and life convenience. Along with a decentralised, transparent and fair trading model, the smart grid attracts many users to participate. In recent years, many researchers have contributed to the development of smart grids in terms of network and information security so that the security, reliability and stability of smart grid systems can be guaranteed. However, our investigation reveals various malicious behaviours during smart grid transactions and operations, such as electricity theft, erroneous data injection, and distributed denial of service (DDoS). These malicious behaviours threaten the interests of honest suppliers and consumers. While the existing literature has employed machine learning and other methods to detect and defend against malicious behaviour, these defence mechanisms do not impose any penalties on the attackers. This paper proposes a management scheme that can handle different types of malicious behaviour in the smart grid. The scheme uses a consortium blockchain combined with the best–worst multi-criteria decision method (BWM) to accurately quantify and manage malicious behaviour. Smart contracts are used to implement a penalty mechanism that applies appropriate penalties to different malicious users. Through a detailed description of the proposed algorithm, logic model and data structure, we show the principles and workflow of this scheme for dealing with malicious behaviour. We analysed the system’s security attributes and tested the system’s performance. The results indicate that the system meets the security attributes of confidentiality and integrity. The performance results are similar to the benchmark results, demonstrating the feasibility and stability of the system.
Smart grids are suscceptible to security vulnerabilities of cyber-physical systems due to the heterogeneity of their interconnected components. There are high risks associated with potential attacks targeting the two-way communication between the smart meters and the utility servers. It is vital to ensure that data communicated between consumers and the utility is not tampered with and is authentic, private, and available. Conventional security measures in traditional communication and network systems fail to secure the data communication aspect in the complex network that composes the advanced metering infrastructure (AMI). In this work, we propose ECC: a novel prevention approach based on Ethereum smart contracts, asymmetric cryptographic functions, and cloud services for securing the two-way communication between smart meters and utility servers. Ethereum blockchain is utilized as a building block where communicated data is treated as transactions encrypted and stored in a distributed fashion to ensure data availability, confidentiality, and privacy. We also augment the Ethereum architecture with cloud services to extend the number of allowable transactions, ensure the availability of the electricity data, and reduce the cost associated with Ethereum transactions. The conducted experiments illustrate the efficacy of ECC in terms of the achieved security properties. This paper shows that the Ethereum Blockchain coupled with Cloud services can improve the efficiency of a system solely based on the Ethereum Blockchain.
The rapid adoption of hydrogen as an eco-friendly energy source has necessitated the development of intelligent power management systems capable of efficiently utilizing hydrogen resources. However, guaranteeing the security and integrity of hydrogen-related data has become a significant challenge. This paper proposes a pioneering approach to ensure secure hydrogen data analysis through the integration of blockchain technology, enhancing trust, transparency, and privacy in handling hydrogen-related information. By combining blockchain with intelligent power management systems, the efficient utilization of hydrogen resources becomes feasible. The utilization of smart contracts and distributed ledger technology facilitates secure data analysis, real-time monitoring, prediction, and optimization of hydrogen-based power systems. The effectiveness and performance of the proposed approach are demonstrated through comprehensive case studies and simulations. Notably, our prediction models, including ABiLSTM, ALSTM, and ARNN, consistently delivered high accuracy with MAE values of approximately 0.154, 0.151, and 0.151, respectively, enhancing the security and efficiency of hydrogen consumption forecasts. The blockchain-based solution offers enhanced security, integrity, and privacy for hydrogen data analysis, thus contributing to the advancement of clean and sustainable energy systems. Additionally, the research identifies existing challenges and outlines potential future directions for further enhancing the proposed system. This study adds to the growing body of research on blockchain applications in the energy sector, with a specific focus on secure hydrogen data analysis and intelligent power management systems.
Guoshu Huang, Tingting Han, Dongsheng Li, Chenchen Han
As the power consumption increases year by year, the traditional power network can no longer meet the new demands of power grid development. In this context, smart grid is proposed as the next-generation grid development direction. However, the informationization of power grid will certainly bring the explosive growth of customers' power consumption data, which brings challenges to the security and management of power data. Blockchain, as a distributed cryptographic ledger, is considered as a powerful tool to ensure data security. This paper first analyses the current risks and problems of electricity customers data security in smart grids and proposes to solve them with blockchain. Then, this paper proposes a secure blockchain-based electricity customers data storage scheme (BECDS) and gives its framework. Finally, this paper uses cryptographic vector commitment to construct a distributed and verifiable data storage scheme based on blockchain, and proves that the scheme proposed in this paper is secure in the scheme evaluation.
Xiaole Su, Yuanchao Hu, Liu Wei, Zhipeng Jiang · 7 authors
Abstract The extension of emerging renewable energy sources such as wind and water turbines, solar panels, and the increasing usage of electric vehicles requires the supply and distribution of energy in a small device on local scale and it has created new methods of supplying and selling electricity. Middle buyers and end users can obtain the local energy with the peer‐to‐peer trading method in this large and hierarchical market. This method enables market to manage and exchange the electricity between major suppliers and medium and local levels. Blockchain technology is developing in peer‐to‐peer exchange of electricity and acts as a reliable, efficient, and safe technology in the electricity trading market. In this method, while preserving the privacy of electricity users, by using smart contracts and by removing intermediaries in the energy supply and demand market, direct commercial interactions between energy suppliers and consumers are done. The blockchain technology, while creating trust between the parties in the energy market, reduces the cost of electricity trading and increases its scalability with using the intermediate energy aggregators. In this research, the blockchain‐based model, is presented for distribution and peer‐to‐peer transactions in the energy market. The suggested model provides the possibility of registration low‐cost instant transactions at the power grid in any specific period of time. The above method, unlike periodic payments, provides immediate access to bills and small payments. Since the transactions outside the blockchain chain are not recorded, this system guarantees its honest and independent operation without fraud and failure. The smart contract method based on blockchain, reduces the transaction fees and speeds up electricity trading. Also, the experimental investigation in 20 nodes shows the time required to determine the exchange contract in the blockchain method. The average is improved by 49.7% in this method. Also, the negotiation convergence time has become 47% faster.
Gehui Li, Jing Yang, Tao Yu, Fuquan Yang · 6 authors
In China, the promulgation of a green power identification system has gradually shifted from electricity power generation to consumption. However, there is no mature digital identification system for green power consumption enterprises. Exploiting the open, transparent, and immutable characteristics of blockchains, this study establishes a digital identification system for green power consumption based on blockchain technology. This system uses expert scoring and the entropy weight method as the evaluation algorithm for the green power consumption chain, issues non-fungible tokens as digital identification for consumption enterprises, and realizes the automatic generation of identification through smart contracts. These functions guarantee the credibility of the certification process and the uniqueness of the generated identification. The results of the experiments show that, in the case of multi-user concurrent requests, the number of concurrent users that the system could handle at optimal processing efficiency was 500, and block generation was stable. The proposed system has high practicability and stability.
Emilio C. Piesciorovsky, Gary Hahn, Raymond Borges Hink, Aaron Werth · 5 authors
Electrical utilities continue to deploy more intelligent electronic devices (IEDs) inside and outside electrical substation, and are associated with customer-owned distributed energy resources (DERs). The integrity and confidentiality of data from these IEDs, like power meters and protective relays, is crucial. Blockchain technology could improve the resilience of microgrids by improving the security of data sharing. The penetration of customer-owned DERs (renewable energy sources) and the increasing deployment of IEDs can lead to integrate power system applications with Distributed Ledger Technology (DLT). In this study, we implemented the electrical faulted phase detection and power quality monitoring algorithms with a Cyber Grid Guard (CGG) system using DLT. In addition, the DERs (wind turbine farms) use case and protective relay cyber-event tests were assessed, by using the CGG system with DLT. In the experimental model, the testbed was created by using a real-time simulator and CGG system with power meters/ protective relays in-the-loop. The data collected from the CGG system and IEDs were compared with the same time stamp source. These results had shown the successful assessment of protection, control and monitoring applications using a CGG system with DLT. In the future, the ESGT with DERs and the CGG system will be used in other power system applications, based on implementing smart contracts between electrical utilities with customer-owned DERs.