Isolated grids, with large-scale intermittent renewable energy sources (RESs), face more severe frequency stability issues. Fortunately, grid-connected electric vehicles (EVs) present an opportunity to provide frequen...
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Isolated grids, with large-scale intermittent renewable energy sources (RESs), face more severe frequency stability issues. Fortunately, grid-connected electric vehicles (EVs) present an opportunity to provide frequency services. In this paper, a two-stage frequency regulation strategy, in which EVs participate in the form of a virtual synchronous machine (VSM), is proposed. First, a frequency response (FR) model is established for both charging stations (CSs) and battery swapping stations (BSSs) using VSM control. On this basis, a two-stage strategy is proposed to consider both frequency regulation performance and system economy. Specifically, in the day-ahead stage (DAS), a multi-unit economic dispatch (ED) model is designed to formulate the operation plan;in the real-time stage (RTS), a consensus-based power allocation strategy is designed for multi-units, responsive to real-time market prices. Case studies involving real-world data of load, RES, and CS illustrate the key benefits of the proposed method, including (i) decreasing frequency deviation, (ii) providing extra rotational inertia, and (iii) reducing dispatch costs.
Exploring diverse education data applications through blockchain technology can offer innovative methods for smart education. Among them, storing multi-platform and multi-dimensional education data on the blockchain c...
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Exploring diverse education data applications through blockchain technology can offer innovative methods for smart education. Among them, storing multi-platform and multi-dimensional education data on the blockchain can enhance the system's ability to integrate and manage the data effectively. However, the system involves a large number of stakeholders. Furthermore, because the data are stored chronologically, relevant information may be distributed across multiple blocks. They will lead to security issues related to access and inefficient queries. We innovatively design an education data management system that combines access-control views with a consensus algorithm, effectively addressing the issue of low query performance for security data. Additionally, we propose a method that integrates main chain blocks and side blocks within a chained storage structure to recycle view blocks, effectively addressing the issue of block redundancy caused by non-periodic changes in the utilization of education data. For the proposed method, experiments are conducted on two education datasets to validate the efficiency of the proposed access-control view in query performance and the effectiveness of the view maintenance consensus algorithm.
The consensus algorithm is the core technology of blockchain systems to maintain data consistency, and its performance directly affects the efficiency and security of the whole system. Practical Byzantine Fault Tolera...
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The consensus algorithm is the core technology of blockchain systems to maintain data consistency, and its performance directly affects the efficiency and security of the whole system. Practical Byzantine Fault Tolerance (PBFT) plays a crucial role in blockchain consensus algorithms by providing a robust mechanism to achieve fault-tolerant and deterministic consensus in distributed networks. With the development of 5G network technology, its features of high bandwidth, low latency, and high reliability provide a new approach for consensus algorithm optimization. To take advantage of the features of the 5G network, this paper proposes 5G-PBFT, which is an improved practical Byzantine fault-tolerant consensus algorithm with three ways to improve PBFT. Firstly, 5G-PBFT constructed the reputation model based on node performance and behavior. The model dynamically selected consensus nodes based on the reputation value to ensure the reliability of the consensus node selection. Next, the algorithm selected the primary node using the reputation model and verifiable random function, giving consideration to the reliability of the primary node and the randomness of the selection process. Finally, we take advantage of the low latency feature of the 5G network to omit the submission stage to reduce the communication complexity from ON2 to ON, where N denotes the number of nodes. The simulation results show that 5G-PBFT achieves a 26% increase in throughput and a 63.6% reduction in transaction latency compared to the PBFT, demonstrating significant performance improvements.
The emergence of malicious nodes in blockchain networks poses a serious threat to the integrity and security of these systems. Malicious activities can disrupt the consensus process and compromise the overall security...
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The emergence of malicious nodes in blockchain networks poses a serious threat to the integrity and security of these systems. Malicious activities can disrupt the consensus process and compromise the overall security of the network. Although traditional consensus mechanisms have proven effective to some extent, they often struggle to tolerate many malicious nodes, which can lead to network instability or even failure. In response to these challenges, this paper presents a novel blockchain sharding consensus algorithm designed to withstand an unlimited scale of malicious nodes (USMN-SCA). Our approach leverages a dynamic credit mechanism to evaluate node behavior and categorize nodes into different credit levels. By dividing the blockchain network into credit-based shards and isolating low-credit nodes, we mitigate the impact of malicious activities and improve the network's resilience. USMN-SCA employs a two-stage consensus process: first, within each shard, and then between shards. This ensures that consensus is reached efficiently while maintaining a high level of security. We implement the USMN-SCA algorithm in a prototype via blockchain sharding and deploy it on the Alibaba Cloud. The experimental results show that our protocol significantly outperforms existing methods in terms of security, with a success probability of 100% in a real-world Web environment, even more then 50% of the nodes are malicious. Additionally, the consensus delay and throughput performance are comparable to those of other state-of-the-art consensus algorithms. These findings establish the USMN-SCA as a cutting-edge solution with high applicability, scalability, and compatibility across various blockchain platforms. This work represents a significant advancement in blockchain security and performance optimization, paving the way for more secure and efficient blockchain applications.
Droop control is a typical method for achieving power-voltage control in DC systems. However, the movement of traction trains causes real-time changes in the resistance of the traction network, leading to variations i...
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Droop control is a typical method for achieving power-voltage control in DC systems. However, the movement of traction trains causes real-time changes in the resistance of the traction network, leading to variations in power sharing at traction substations (TSSs) determined by droop control, thereby impacting the voltage operation quality of the DC traction power supply system (TPSS). In this paper, an adaptive power-voltage hierarchical control strategy considering rational traction power sharing and voltage compensation based on the consensus algorithm is proposed to mitigate the impact of train movement. Firstly, to enhance the convergence speed of inter-station communication algorithms in the system layer control, an improved consensus algorithm with a convergence factor is proposed to calculate the average values of TSS state variables needed for the local layer control. Secondly, in the local layer control, the per-unit average power of TSSs is introduced to compensate for the impact of train movement on the droop coefficient. Furthermore, to reduce power loss in the traction network, a base quantity for virtual power is proposed for further compensation of the droop coefficient. Through dynamic compensation of the droop coefficient, a rational sharing of traction power according to rated capacity and power supply distance at TSSs is achieved. Moreover, the voltage average is utilized for secondary compensation of voltage deviations at TSSs. Finally, simulations based on a four-terminal DC TPSS have been established to validate the effectiveness of the proposed method in terms of power sharing and voltage control.
Recent years have seen extensive adoption of blockchain technology across a variety of application domains, all with the goal of enhancing data privacy, system trustworthiness, and security. One of the biggest problem...
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Recent years have seen extensive adoption of blockchain technology across a variety of application domains, all with the goal of enhancing data privacy, system trustworthiness, and security. One of the biggest problems with blockchain is its inability to scale;other problems include energy consumption, latency, throughput, and the ever-increasing volume of daily transactions. The consensus technique relies on hash functions, which are important to highlight. Thus, such development is fundamental to blockchain advances in terms of structure. This study introduces a revolutionary change to the Proof-of-Stake (POS) consensus methods by suggesting the replacement of the commonly used SHA256 hash function with the extremely efficient Blake3. Many blockchain-based systems, including POS algorithms, still employ the widely used SHA256 algorithm for cryptographic hashing. Nevertheless, fresh research has shown that SHA256 has performance and security flaws. We show that the Blake3 hash function, is better than the SHA256 hash in many respects, including latency, throughput, and energy, via rigorous testing and functional analysis. Diverse parameters were utilized, including the quantity of blocks and validators. Seen cases are taken into account for performance evaluation. In the initial scenario, utilizing 500 blocks and 4 validators, our proposed methodology has surpassed the benchmark by achieving a 66% reduction in latency, over 50% in throughput, and a 55% decrease in energy consumption. The rate of enhancement is nearly uniform across all other instances, indicating that the implementation of Blake3 within the conventional POS consensus mechanism has demonstrated its advantages.
As the number of data providers and the volume of data in flight data sharing networks continue to grow, achieving secure and efficient sharing of flight data across multiple institutions faces significant challenges....
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As the number of data providers and the volume of data in flight data sharing networks continue to grow, achieving secure and efficient sharing of flight data across multiple institutions faces significant challenges. The phenomenon of data silos is prevalent, severely hindering the flow and utilization of information. To address these issues, this paper proposes a flight data sharing scheme (FDSS) that integrates cloud computing and blockchain. In this scheme, we propose a separation mechanism of metadata on-chain storage and entity data off-chain storage, which effectively improves the data storage efficiency. At the same time, we also offload the complex computation tasks during data access to the edge servers for processing, which realizes the refinement of data access and reduces the computation burden on the user side. Given that all information exchanges between data requesters and data owners are conducted via the blockchain, the block generation speed becomes critical to ensure the efficient operation of the scheme. To this end, we also make significant improvements to traditional consensus algorithms, aiming to comprehensively enhance the overall system efficiency. In the end, through in-depth theoretical analysis and experimental verification, the FDSS scheme demonstrates excellent performance and high feasibility, fully proving its great potential and value in the field of flight data sharing.
The Internet of Things (IoT) is composed of smart devices connected to a network that can send and receive large amounts of data with other devices, generating a lot of data for processing and analysis. Due to the fac...
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The Internet of Things (IoT) is composed of smart devices connected to a network that can send and receive large amounts of data with other devices, generating a lot of data for processing and analysis. Due to the fact that every transaction in blockchain is recorded, placed in a data block, and added to an immutable and secure data chain, blockchain is becoming one of the most promising solutions for enhancing IoT security issues. As more devices become intelligent, the scale of IoT systems, including residential IoT and industrial IoT, is on the rise. Consequently, the issue of resource consumption, stemming from the escalating system communication overhead, is becoming more pronounced. In order to improve the efficiency of the consensus process for residential IoT and reduce the overhead caused by the consensus process, this paper proposes a hierarchical PBFT consensus algorithm With Dual Blockchain for IoT (DBPBFT). Compared to industrial IoT, DBPBFT is more suitable for residential IoT with small scope and clear data classification. DBPBFT separates the responsibilities of dual chains, improving system scalability while also enhancing blockchain security. A chain is divided into several small groups, each responsible for a type of data, reducing system overhead and communication overhead. To avoid unnecessary view-change as much as possible, before consensus begins, each group will select the current view primary node based on reputation values. The simulation results show that the DBPBFT algorithm is superior to traditional algorithms. In terms of reducing communication overhead, compared with EPBFT and DPNPBFT, DBPBFT has increased by 73.8% and 53.1%, respectively. In terms of consensus efficiency, DBPBFT has improved by 34% compared to DPNPBFT.
Energy blockchain applications are becoming inevitable with the transformation of electricity distribution networks into the decentralized Smart Grid 2.0 architecture. The scalability of the blockchain platform plays ...
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Energy blockchain applications are becoming inevitable with the transformation of electricity distribution networks into the decentralized Smart Grid 2.0 architecture. The scalability of the blockchain platform plays a key role in catering to the increasing number of nodes connected due to consumer-turned-prosumers being integrated into the distribution grid in a distributed manner. Hence, this study aims to optimize blockchain utilization for Smart Grid 2.0 applications through a novel consensus mechanism, which eliminates the requirement for performing additional complex computations to mine a new block. The algorithm utilizes the grid monitoring process through the existing smart meters, and thus has been capable of reducing the energy footprint for block mining to a fraction of that of the legacy Proof-of-Work algorithm, and reducing the block creation time by similar to 60%. The proposed Power Line Monitoring-based consensus Mechanism (PLMC) algorithm is validated using the Process Analysis Toolkit (PAT). In addition, data collected while monitoring the network for block mining is utilized for power quality measurement purposes.
Traditional intellectual property authentication relies on centralized intermediaries, which makes it difficult to address issues such as forgery, lack of trust, and opaque information. Combined with the characteristi...
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Traditional intellectual property authentication relies on centralized intermediaries, which makes it difficult to address issues such as forgery, lack of trust, and opaque information. Combined with the characteristics of blockchain, such as decentralization, tampering, and traceability, these challenges can be effectively dealt with. Aiming at the shortcomings of traditional consensus algorithms in intellectual property authentication, such as high communication overhead and low efficiency, the improved PBFT (Practical Byzantine Fault Tolerance) algorithm (MBFT algorithm) is proposed and combined with the distributed database IPFS (Inter Planetary File System) to alleviate the pressure of blockchain data storage and enhance operational efficiency. The algorithm first adopts the evaluation system in the hierarchical mechanism, invokes the Fibonacci series incremental law to update the Score value of the nodes and sort them, and divides the nodes into the classification consensus layer, the consensus confirmation layer, and the supervision layer. Secondly, the Maglev algorithm is used to generate a lookup table and design a classification consensus strategy, which is divided into four consensus groups based on the characteristics of intellectual property categories, namely, the patent authentication consensus group, the trademark authentication consensus group, the copyright authentication consensus group, and the other types of authentication consensus group. Then, the algorithm optimizes the consistency protocol, carries out PBFT consensus once in each of the classification consensus layers and consensus confirmation layers, according to the consensus situation, and realizes the nodes' dynamic update to ensure the consensus's accuracy and reliability. The experiments show that the MBFT algorithm performs better in terms of communication complexity and throughput. As the number and size of files increase, the execution time of IPFS progressively lengthens. However,
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