Tianfeng Chu, Xingchen An, Wuyang Zhang, Yan Lu · 5 authors
Virtual power plants can aggregate distributed energy resources and interruptible loads in a region for coordinated regulation and unified transaction. However, with the diversification of competition in the electricity market, the distributed operation mechanism between multiple virtual power plants (multi-VPPs) has gradually become a research focus. Based on this, this paper proposes a new type of distributed transactions strategy between multi-VPPs, i.e., the transaction matching mechanism. A two-stage transaction model based on the transaction matching is constructed for multi-VPPs to participate in the day-ahead and intraday electricity trading markets. In the first stage, each VPP optimizes its own internal units’ output and external interaction power through a cooperative game; in the second stage, it is the transaction matching among multi-VPPs that can match the most suitable counterpart by flexible price setting to increase the benefits of all the VPPs. Considering the efficiency and security of blockchain technology, we choose to complete the transaction matching between multi-VPPs with the support of alliance blockchain technology to improve the speed of system solution.
Rihab Jmal, Walid Ghabri, Ramzi Guesmi, Badr M. Alshammari · 6 authors
By bringing smart and advanced solutions, the Internet of Things (IoT) has opened up new dimensions of innovative services and processing power for contemporary living standards. IoT has a wide range of devices and communication entities as a result of the widespread applications of these services, making network management a challenging task. Therefore, it is critical to redesign the IoT network’s management. The inherent programmability and centralized capabilities of software-defined networking (SDN) make network management simpler, enable network abstraction, make network evolution easier, and have the potential to handle the IoT network. However, security issues still present the IoT dilemma. Distributed Denial of Service (DDoS) attacks are among the most significant security threats in IoT systems. This paper studies in-depth DDoS attacks in IoT and in SDN. A review of different detection and mitigation techniques based on SDN, blockchain and machine learning models is conducted. A holistic, secure IoT system is proposed on the basis of SDN with multicontrollers. Blockchain is considered to guarantee security in distributed SDN-IoT networks and ANN to improve the detection and mitigation process.
Fernando Richter Vidal, Naghmeh Ivaki, Nuno Laranjeiro
Abstract Smart contracts are nowadays at the core of most blockchain systems. Like all computer programs, smart contracts are subject to the presence of residual faults, including severe security vulnerabilities. However, the key distinction lies in how these vulnerabilities are addressed. In smart contracts, when a vulnerability is identified, the affected contract must be terminated within the blockchain, as due to the immutable nature of blockchains, it is impossible to patch a contract once deployed. In this context, research efforts have been focused on proactively preventing the deployment of smart contracts containing vulnerabilities, mainly through the development of vulnerability detection tools. Along with these efforts, several heterogeneous vulnerability classification schemes appeared (e.g., most notably DASP and SWC). At the time of writing, these are mostly outdated initiatives, even though new smart contract vulnerabilities are consistently uncovered. In this paper, we propose OpenSCV, a new and Open hierarchical taxonomy for Smart Contract vulnerabilities, which is open to community contributions and matches the current state of the practice while being prepared to handle future modifications and evolution. The taxonomy was built based on the analysis of the existing research on vulnerability classification, community-maintained classification schemes, and research on smart contract vulnerability detection. We show how OpenSCV covers the announced detection ability of the current vulnerability detection tools and highlight its usefulness in smart contract vulnerability research. To validate OpenSCV, we performed an expert-based analysis wherein we invited multiple experts engaged in smart contract security research to participate in a questionnaire. The feedback from these experts indicated that the categories in OpenSCV are representative, clear, easily understandable, comprehensive, and highly useful. Regarding the vulnerabilities, the experts confirmed that they are easily understandable.
Blockchain is the fundamental component of smart contract applications. Testing technology plays a special and irreplaceable role in the development of smart contract applications in blockchain-based applications, especially in distributed renewable energy transaction scenarios in the energy industry. In practice, the formulation of blockchain technology as a standard infrastructure is an essential means to improve the reliability of blockchain-based applications in the energy industry. However, the quality of the organization-level blockchain still encounters many challenges, such as password attacks, and double spending attacks, which attract much attention from both research and academic area. Much research has focused on quality improvement through testing to fulfill the requirement toward functional, performance, and security requirements of the industry. However, the framework to accomplish the specific testing task was not present comprehensively yet. In This paper, an investigation was given on the supervision and testing of blockchain-based applications in the energy industry after its operation online. The existing testing indicator, model, and application scenario combined with the practice in the state grid industry were illustrated, in which the process, models, and methods were shown, and also suggestions were given on promoting the blockchain-based smart contract testing evaluation in the energy industry.
Exchanging information and data within smart grids is crucial to improve interoperability among system users. Traditional cloud-based data exchange schemes are centralized on a single trusted third-party platform. The schemes consequently suffer from single-point failure, a lack of data protection, and uncontrolled access. Blockchain enables data exchange in a decentralised and secure manner. A new platform is proposed in this work for exchanging data within smart grids using blockchain. It allows users to securely exchange data without losing ownership. This platform provides solutions to three critical problems: privacy, scalability, and user ownership. Particularly, the blockchain-based smart contract technology gives participants the programmability to access data. All interactions are authenticated and recorded by the other participants in the tamper-resistant blockchain network. Furthermore, the performance of the proposed blockchain platform is enhanced by integrating it with an artificial neural network (ANN). The proposed method is used to predict the network’s throughput and latency, and the network administrator uses these predicted values to change the network’s settings for a high throughput and low latency. Throughout the results, the proposed model achieves performance improvements in blockchain-enabled information and data exchange and adapts well to the dynamics of smart grids.
Ali Menati, Yuting Cai, Rayan El Helou, Chao Tian · 5 authors
Proof-of-work computation used in cryptocurrencies has witnessed significant growth in the U.S. and many other regions around the world. One of the most significant bottlenecks for the scalable deployment of such computation is its energy demand. On the other hand, the electric energy system is increasing the need for flexibility for energy balancing and ancillary services due to the intermittent nature of many new energy resources such as wind and solar. In this work, we model the operation of a cryptomining facility with heterogeneous mining devices participating in ancillary services. 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. In the second special setting, a risk-aware algorithm is proposed to jointly minimize the cost and the risk of participating in ancillary services with homogeneous mining devices. 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.
Ömer Aslan, Semih Serkant Aktuğ, Merve Ozkan-Okay, Abdullah Asım Yılmaz · 5 authors
Internet usage has grown exponentially, with individuals and companies performing multiple daily transactions in cyberspace rather than in the real world. The coronavirus (COVID-19) pandemic has accelerated this process. As a result of the widespread usage of the digital environment, traditional crimes have also shifted to the digital space. Emerging technologies such as cloud computing, the Internet of Things (IoT), social media, wireless communication, and cryptocurrencies are raising security concerns in cyberspace. Recently, cyber criminals have started to use cyber attacks as a service to automate attacks and leverage their impact. Attackers exploit vulnerabilities that exist in hardware, software, and communication layers. Various types of cyber attacks include distributed denial of service (DDoS), phishing, man-in-the-middle, password, remote, privilege escalation, and malware. Due to new-generation attacks and evasion techniques, traditional protection systems such as firewalls, intrusion detection systems, antivirus software, access control lists, etc., are no longer effective in detecting these sophisticated attacks. Therefore, there is an urgent need to find innovative and more feasible solutions to prevent cyber attacks. The paper first extensively explains the main reasons for cyber attacks. Then, it reviews the most recent attacks, attack patterns, and detection techniques. Thirdly, the article discusses contemporary technical and nontechnical solutions for recognizing attacks in advance. Using trending technologies such as machine learning, deep learning, cloud platforms, big data, and blockchain can be a promising solution for current and future cyber attacks. These technological solutions may assist in detecting malware, intrusion detection, spam identification, DNS attack classification, fraud detection, recognizing hidden channels, and distinguishing advanced persistent threats. However, some promising solutions, especially machine learning and deep learning, are not resistant to evasion techniques, which must be considered when proposing solutions against intelligent cyber attacks.
Decentralized energy management can preserve the privacy of individual energy systems while mitigating computational and communication burdens. However, most decentralized energy management methods are partially decentralized and cannot ensure information exchange security. Therefore, this paper provides a secure fully decentralized energy management by using blockchain. First, a fully decentralized energy management framework using the optimality condition decomposition (OCD) is provided, in which individual energy system operators only exchange the boundary information with their peers rather than submitting proprietary information to a centralized system operator. Then, an asynchronous mechanism is proposed for updating the information exchange in OCD, enabling the proposed decentralized management to work under potential communication latency or interruption. Furthermore, the blockchain-based framework with state machine replication (SMR) based consensus algorithm is provided to safeguard the information exchange among individual energy systems in a secure and tamper-proof manner. The proposed decentralized energy management is tested on a multi-energy system with seven subsystems and a real-world multi-energy system in North China. The numerical results demonstrate the effectiveness of the proposed method in privacy protection and data security enhancement. The proposed method can prevent the cost increase caused by cheating activities, which in some subsystems can reach 17.6%. Additionally, the proposed fully decentralized method outperforms the partially decentralized method by 37.7% in reducing computation time. Also demonstrated are the computational precision, scalability and adaptability of the proposed method.1
Prince Silas Kwesi Oberko Prince Silas Kwesi Oberko, Tianang Yao Prince Silas Kwesi Oberko, Hu Xiong Tianang Yao, Saru Kumari Hu Xiong · 5 authors
<p>The smart energy system (SES) encourages data administration and information services developments, particularly smart grids. Presently, numerous SESs cloud environments are accessible to smart grids. Nonetheless, because of the semi-credible character of the SES cloud environments, achieving secured access, information storage, updates, deletion, tracing, and revocation of ill-disposed clients is a genuine concern. In this publication, an Ethereum blockchain-oriented secured access regulation design upholding traceability and revocability is offered for smart grids to resolve these problems. The blockchain implements unified identity verification and saves all public-keys, users&rsquo; attribute sets, and revocable lists. The system administrator creates system parameters and sends private-keys to users. The domain administrator prepares the domain&rsquo;s security and privacy-preservation policies and executes encryption procedures. If the attributes correspond with the access policy and the user&rsquo;s ID is unrevoked, they could acquire interim-decryption capabilities from the edge/cloud servers. Tracking malevolent users for revocation is applicable throughout all stages, ensuring the system is secured under Decisional-Bilinear-Diffie-Hellman (DBDH) complex theory and can withstand multi-attacks. Analysis revealed the size of the public/private keys to be shorter, contrary to relevant schemes. The overhead duration is less for generating the public-key, data encryption, and decryption phases. </p> <p>&nbsp;</p>
Bin Qian Bin Qian, Yi Luo Bin Qian, Jiaxiang Ou Yi Luo, Yong Xiao Jiaxiang Ou · 5 authors
<p>As a new-style smart grid, Internet of Energy (IoE) is important and how to provide its trusted time-stamping service becomes a hit. For example, an energy provider needs to prove he/she transferred some energy to a consumer at some time. Nevertheless, traditional trusted time-stamping scheme with a central service provider is not suitable for IoE. Some researchers try to solve this problem via blockchain, due to its decentralization, traceability and tamper-proof. However, there are still chal&shy;lenges when using blockchain. Some have to introduce another kind of central participant. Some have to face the problem of accuracy and availability when using the Bitcoin blockchain. Some have to generate too many extra transactions. To address the aforementioned problems, we propose a fully decentralized trusted time-stamping scheme without any central participant and fulfill six design goals. Compared with the state-of-the-art blockchain-based time-stamping scheme named Chronos, our scheme enjoys less cryptographic operations. We then tested our scheme in the development (local) network and two live networks of the Ethereum. The experiment shows that we have implemented a simple, effective, accurate and low-cost decentralized trusted time-stamping scheme.</p> <p>&nbsp;</p>
This research paper reviews the potential of smart contracts for responsible AI with a focus on frameworks, hardware, energy efficiency, and cyberattacks. Smart contracts are digital agreements that are executed by a blockchain, and they have the potential to revolutionize the way we conduct business by increasing transparency and trust. When it comes to responsible AI systems, smart contracts can play a crucial role in ensuring that the terms and conditions of the contract are fair and transparent as well as that any automated decision-making is explainable and auditable. Furthermore, the energy consumption of blockchain networks has been a matter of concern; this article explores the energy efficiency element of smart contracts. Energy efficiency in smart contracts may be enhanced by the use of techniques such as off-chain processing and sharding. The study emphasises the need for careful auditing and testing of smart contract code in order to protect against cyberattacks along with the use of secure libraries and frameworks to lessen the likelihood of smart contract vulnerabilities.
Seyed Amir Alavi, Mehrnaz Javadipour, Ardavan Rahimian, Kamyar Mehran
Abstract The privacy of electricity consumers has become one of the most critical subjects in designing smart meters and their proliferation. In this work, a multilayer architecture has been proposed for anonymous data collection from smart meters, which provides: (1) The anonymity of information for third‐party data consumers; (2) Secure communication to utility provider network for billing purposes; (3) Online control of data sharing for end‐users; (4) Low communication costs based on available Internet of things (IoT) communication protocols. The core elements of this architecture are, first, the digital twin equivalent of the cyber‐physical system and, second, the Tangle distributed ledger network with IOTA cryptocurrency. In this architecture, digital twin models are updated in real‐time by information received from trusted nodes of the Tangle distributed network anonymously. A small‐scale laboratory prototype based on this architecture has been developed using the dSPACE SCALEXIO real‐time simulator and open‐source software tools to prove the feasibility of the proposed solution. The numerical results confirm that after a few seconds of anomaly detection, the microgrid was fully stabilized around its operating point with less than 5% deviation during the transition time.
The power system and markets have become increasingly complex along with an effort to digitalize the energy sector. Accessing flexibility services, in particular, through digital energy platforms, has enabled communication between multiple entities within the energy system and streamlined flexibility market operations. However, digitalizing these vast and complex systems introduces new cybersecurity and privacy concerns, which must be properly addressed during the design of the digital energy platform ecosystems. In this study, the potential and operation of digital flexibility platforms are reviewed, and a generic architecture with/without a combined distributed ledger technology framework is proposed. Finally, concerns about cybersecurity and privacy on digital energy platforms are discussed.
Tehseen Mazhar, Hafiz Muhammad Irfan, Sunawar Khan, Inayatul Haq · 7 authors
Smart grids are rapidly replacing conventional networks on a worldwide scale. A smart grid has drawbacks, just like any other novel technology. A smart grid cyberattack is one of the most challenging things to stop. The biggest problem is caused by millions of sensors constantly sending and receiving data packets over the network. Cyberattacks can compromise the smart grid’s dependability, availability, and privacy. Users, the communication network of smart devices and sensors, and network administrators are the three layers of an innovative grid network vulnerable to cyberattacks. In this study, we look at the many risks and flaws that can affect the safety of critical, innovative grid network components. Then, to protect against these dangers, we offer security solutions using different methods. We also provide recommendations for reducing the chance that these three categories of cyberattacks may occur.
In the current era, the skyrocketing demand for energy necessitates a powerful mechanism to mitigate the supply–demand gap in intelligent energy infrastructure, i.e., the smart grid. To handle this issue, an intelligent and secure energy management system (EMS) could benefit end-consumers participating in the Demand–Response (DR) program. Therefore, in this paper, we proposed a real-time and secure incentive-based EMS for smart grid, i.e., RI-EMS approach using Reinforcement Learning (RL) and blockchain technology. In the RI-EMS approach, we proposed a novel reward mechanism for better convergence of the RL-based model using a Q-learning approach based on the greedy policy that guides the RL-agent for faster convergence. Then, the proposed RI-EMS approach designed a real-time incentive mechanism to minimize energy consumption in peak hours and reduce end-consumers’ energy bills to provide incentives to the end-consumers. Experimental results show that the proposed RI-EMS approach induces end-consumer participation and increases customer profitabilities compared to existing approaches considering the different performance evaluation metrics such as energy consumption for end-consumers, energy consumption reduction, and total cost comparison to end-consumers. Furthermore, blockchain-based results are simulated and analyzed with the help of deployed smart contracts in a Remix Integrated Development Environment (IDE) with the parameters such as transaction efficiency and data storage cost.
Rajeev Kumar Gupta, Vedant Chawla, R. K. Pateriya, Piyush Kumar Shukla · 6 authors
The threat of cyber-attacks is ever increasing in today’s society. There is a clear need for better and more effective defensive tools. Intrusion detection can be defined as the detection of anomalous behavior either in the host or in the network. An intrusion detection system can be used to identify the anomalous behavior of the system. The two major tasks of intrusion detection are to monitor data and raise an alert to the system administrators when an intrusion takes place. The current intrusion detection system is incapable of tackling sophisticated attacks which take place on the entire network containing large number of nodes while maintaining a low number of login attempts on each node in the system. A collaborative intrusion detection system (CIDS) was designed to remove the inefficiency of the current intrusion detection system which failed to detect coordinated distributed attacks. The main problem in the CIDS is the concept of trust. Hosts in the network need to trust the data sent by other peers in the network. To bring in the concept of trust and implement the proof-of-concept, blockchain was used. Pluggable authentication modules (PAM) were also used to track login activity securely before an intruder could modify the login activity. To implement blockchain, an Ethereum-based private blockchain was used.
Abstract This research presents a decentralised incentive‐based demand response (DR) program using blockchain technology. Consumers self‐report baseline to the system operator (SO), the smart contract confirms the validity of the data to execute transactions and finally the validators record the information on the blockchain network. During the DR event, a set of consumers are randomly selected to deliver the required load reduction. The signalled consumer who delivers the load reduction is rewarded, and the non‐called consumers who diverge from their reported baseline are penalised. The randomness of choosing the consumers and penalty function restrict the baseline inflation. Here, we create a blockchain network and deploy a smart contract on the Ethereum build platform. A DR event scenario is adopted with residential houses data sets, all consumers report their baseline information to the SO through the Internet and smart meter. The SO calls four users to deliver the essential load reduction according to the probability of choosing a consumer. The smart contract verifies the received information to start transaction execution. We use proof of authority mechanism to select validation nodes from the participants using voting system. They validate each block before adding it to the blockchain. Last, the monetary transactions settle in participants' wallets. Our results confirm that decentralised systems like blockchain can significantly improve transparency, openness, and customer participation in the DR program. Also contributes to the security and privacy of user information with a minimal investment in new infrastructure.
Nihar Ranjan Pradhan, Akhilendra Pratap Singh, S. Sudha, K. Hemanth Kumar Reddy · 5 authors
With the electric power grid experiencing a rapid shift to the smart grid paradigm over a deregulated energy market, Internet of Things (IoT)-based solutions are gaining prominence, and innovative peer-to-peer (P2P) energy trading at a micro level is being deployed. Such advancement, however, leaves traditional security models vulnerable and paves the path for blockchain, a distributed ledger technology (DLT), with its decentralized, open, and transparency characteristics as a viable alternative. However, due to deregulation in energy trading markets, most of the prototype resilience regarding cybersecurity attack, performance and scalability of transaction broadcasting, and its direct impact on overall performances and attacks are required to be supported, which becomes a performance bottleneck with existing blockchain solutions such as Hyperledger, Ethereum, and so on. In this paper, we design a novel permissioned Corda framework for P2P energy trading peers that not only mitigates a new class of cyberattacks, i.e., delay trading (or discard), but also disseminates the transactions in a optimized propagation time, resulting in a fair transaction distribution. Sharing transactions in a permissioned R3 Corda blockchain framework is handled by the Advanced Message Queuing Protocol (AMQP) and transport layer security (TLS). The unique contribution of this paper lies in the use of an optimized CPU and JVM heap memory scenario analysis with P2P metric in addition to a far more realistic multihosted testbed for the performance analysis. The average latencies measured are 22 ms and 51 ms for sending and receiving messages. We compare the throughput by varying different types of flow such as energy request, request + pay, transfer, multiple notary, sender, receiver, and single notary. In the proposed framework, request is an energy asset that is based on payment state and contract in the P2P energy trading module, so in request flow, only one node with no notary appears on the vault of the node.Energy request + pay flow interaction deals with two nodes, such as producer and consumer, to deal with request and transfer of asset ownership with the help of a notary. Request + repeated pay flow request, on node A and repeatedly transfers a fraction of energy asset state to another node, B, through a notary.
Mirza Jabbar Aziz Baig, M. Tariq Iqbal, Mohsin Jamil, Jahangir Khan
Renewable energy resources have been gaining ground in recent years and we are on the verge of a decentralized energy market with consumers becoming prosumers. Platforms that facilitate peer-to-peer (P2P) sale or purchase of energy are therefore essential. This paper presents a way to trade energy across P2P networks using blockchain technology. The main server is a Raspberry Pi 4 Model B (Pi4B), on which the user interface (UI) as well as the private Ethereum blockchain are configured. The blockchain also implements a smart contract. For the purpose of developing the UI that provides assistance in conducting trading activities, an open-source Angular framework is used. Also explored in the study is the development of an Internet of Things (IoT) server using the latest ESP32-S3 microcontroller. The field instrumentation devices (FIDs) are connected to the microcontroller for the purpose of data acquisition and for subsequent transmission to an IoT server. The blockchain network maintains a record of all transactions in an immutable manner. Assuring security is achieved through a local configuration of the system, hosted on a private network with restricted access. For the purposes of information security and data integrity, additional security measures are also considered, such as a secret recovery phrase, firewalls, login credentials and private key. Among the servers and clients, there is an implementation of a Hypertext Transfer Protocol. The P2P energy trading approach involving renewable energy designed for remote communities is explained and illustrated in this paper.
Mingxing Guo, Ke Zhang, Su Wang, Jinlei Xia · 7 authors
Traditional centralized transactions require a control center for user demand matching, settlement and other processes. However, with the increase in the penetration rate of distributed energy in the community, the explosive increase in the number of transactions leads to a decrease in efficiency and it is difficult to guarantee user privacy and information security. The smart contract technology based on blockchain technology has the characteristics of decentralization, traceability and tamper resistance, and these key factors show unique advantages in distributed energy transactions. This paper explores Ethereum and smart contract technology, designs a peer-to-peer energy sharing mechanism with reward and punishment incentives and establishes a smart contract trading platform for smart community-based virtual power plant (CVPP). This paper verifies the functionality and effectiveness of smart contract. The results show that when the supply and demand ratio changes, the user can conduct energy transactions according to the contract without a third-party organization, which solves the problem of trust between the two parties and achieves the expected effect and runs successfully. In addition, the simulation results show that the peer-to-peer transaction based on smart contracts reduces the energy cost per household and increases the total benefit of CVPP.
Developments such as the increasing electrical energy demand, growth of renewable energy sources, cyber–physical security threats, increased penetration of electric vehicles (EVs), and unpredictable behavior of prosumers and EV users pose a range of challenges to the electric power system. To address these challenges, a decentralized system using blockchain technology and machine learning techniques for secure communication, distributed energy management and decentralized energy trading between prosumers is required. Blockchain enables secure distributed trust platforms, addresses optimization and reliability challenges, and allows P2P distributed energy exchange as well as flexibility services between customers. On the other hand, machine learning techniques enable intelligent smart grid operations by using prediction models and big data analysis. Motivated from these facts, in this review, we examine the potential of combining blockchain technology and machine learning techniques in the development of smart grid and investigate the benefits achieved by using both techniques for the future smart grid scenario. Further, we discuss research challenges and future research directions of applying blockchain and machine learning techniques for smart grids both individually as well as combining them together. The identified areas that require significant research are demand management in power grids, improving the security of grids with better consensus mechanisms, electric vehicle charging systems, scheduling of the entire grid system, designing secure microgrids, and the interconnection of different blockchain networks.
A flexible and adaptable market procurement of reactive power has the potential to improve network efficiency, voltage stability, and operational costs. In Europe, such a dynamic procurement must be in accordance with the European Union directive EU 2019/944 on non-frequency ancillary services. In accordance with this situation, a blockchain-based framework of market procurement of reactive power is proposed and presented in this paper. The devised framework is in alignment with the European Union’s directive to establish a non-discriminatory, transparent, and free market. Moreover, the blockchain-based framework is applicable at all network levels and allows for the variety of different distributed resources to participate. A two-layer blockchain topology is proposed to overcome scalability and transaction time issues. The first main-layer blockchain acts as the agent for trust and guarantees the immutability of data as well as the remuneration of participating market players. The second-layer blockchain facilitates direct access to tendering processes or auctions, fast transactions, and low transaction fees for involved stakeholders. Additionally, a decentralized oracle network is proposed to integrate external data into the second-layer blockchain. Data required for verifying the physical reactive power transactions are delivered by smart meters. The entire procurement process is automated by deploying smart contracts at the various blockchain layers. Thus, in principle, the involved stakeholders are the system operators and market players. For the purpose of validation, the holistic market procurement process is demonstrated and analyzed in a hardware-in-the-loop environment involving reactive power procurement at the distribution network level.
The construction of smart grids provides many benefits. Computational cost, however, drastically grows with an increase in scale since a large amount of data is generated, transmitted, collected, and treated. Although data aggregation technology is helpful when adopting smart grid applications, corresponding security and performance issues should be considered while implementing the mechanism. In this paper, a blockchain-enabled authenticated conserved data aggregation scheme is proposed to balance security concerns and the computational cost of the smart grid. Furthermore, several functions are developed in our scheme to highlight the contributions. First, efficient cryptographic algorithms are integrated instead of computationally-expensive ones. Second, the proposed scheme seamlessly incorporates a blockchain system into a smart grid for better decentralization which can avoid the possible threats and high cost of a centralized system. Third, the scheme is scalable, which can be adapted to manage a great number of metering devices. Fourth, the aggregational operations in our design combine power data and signature, which is more practical. Finally, the proposed scheme covers a one-time key pair and signature mechanism, thus upgrading the privacy protection of blockchain applications in the smart grid.