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439 results · page 3 of 19
Brijmohan Lal Sahu, Preeti Chandrakar
No abstract is available for this record.
Ishmeen Kaur Garewal, Shruti Rajeev Jha, Prashansa Subhash Erande, Nimisha Yogesh Gharat · 5 authors
This paper proposes a blockchain-based smart contract system for decentralized Vehicle-to-Grid (V2G) load management. The system incorporates a dynamic algorithm to balance grid demand by automating secure energy transfers from Electric Vehicles (EVs) and ensuring fair, real-time compensation for EV owners. Developed in Solidity on the Ethereum blockchain, the solution includes features such as dynamic load adjustment, emergency protocols for grid stability, and transparent transaction management. Simulation results show that the system effectively handles varying grid demands while maintaining scalability and operational efficiency. A case study in rural and semi-urban regions highlights its potential to mitigate power outages by using EVs as decentralized energy contributors. The primary research contribution lies in designing a decentralized framework that integrates blockchain and V2G technologies to optimize grid performance, ensure system resilience, and promote sustainable energy practices,
Madhusudan Naik, Akhilendra Pratap Singh, Nihar Ranjan Pradhan, Abdullah M. Almuhaideb · 5 authors
Electric vehicle (EV) charging stations (CSs) are increasingly prevalent due to the growing adoption of renewable energy. Solar CSs’ main difficulties are energy efficiency, security, traceability, and sustainability. This article presents a novel blockchain-enabled EV charging framework that addresses these challenges using the Ethereum virtual machine (EVM), the Metamask wallet, and smart contracts (SCs). This article introduces solarcoins, a digital currency for trading solar energy, which reduces human intervention while fostering trust, transparency, and privacy among EV users. The proposed solution ensures secure communication between CS operators and EV users, enhancing both security and traceability. The proposed solution ensures secure communication between CS operators and EV users, enhancing both security and traceability. To quantify the sustainability and efficiency of the proposed system, the framework performances are tested and evaluated by varying numbers and types (Read, Write, and Transfer) of transactions using Hyperledger caliper and Go Ethereum. The overhaul Performance metrics were measured under varied transaction rates and control parameters by varying the number of validator nodes (1 node to 5 nodes), such as transaction latency, throughput, resource utilization, and so on. The performance of three major functions—open, query, and transfer—was recorded and analyzed. The results show that the query transaction is faster than open and transfer and the latency increases linearly with increased transaction rate. At 1000 transaction per second, the open function has a latency of 260.22 s, whereas the query function has a latency of 104.12 s and the transfer function has a latency of 345.73 s. The average memory usage for 1node-clique is 1224.0 MB, while it is 76.8 MB for 5node-clique. Results reveal that with an increase in the number of cliques (Validator CSs), memory utilization decreased linearly. This happens because all framework transactions are distributed across each EV CS network. The SCs deployment and operational costs were measured. Complexity analysis reveals that functions, such as getStation, getUser, getStationState, etc., exhibit constant time complexity O(1), while the registerUser and addStation functions have linear space and time complexity O(n).
Ardavan Babaei, Erfan Babaee Tırkolaee, Esra Boz
No abstract is available for this record.
Shruthi Devadhas, Rathi Devadhas, R. Rengaraj, Mary Neebha
No abstract is available for this record.
P. H. T. Trung, L. K. Bang
No abstract is available for this record.
H. Miri, Rajaa Naji El Idrissi, Mehdi Najib, A. NAIT SIDI MOH · 5 authors
The electrification of the transportation sector, via the integration of battery electric-powered vehicles (BEV), is one of the solutions, which could help in reducing greenhouse gas (GHG) emission. Smart charging techniques with bidirectional flow, in which the electric power can flow back and forth (i.e., V2G and G2V) from/into the grid according the peak hours have been recently proposed for improving power quality and regulating frequency/voltage of the utility grid. In this paper, we aim to develop a blockchain-based IoT platform for peer-to-peer energy trading between BEV and smart buildings management systems in the context of home healthcare by using Hyperledger Besu; a private network based on Ethereum with the use of its consensus algorithm Clique. The developed platform's prototype made a success transactions of energy trading which makes renewable energy available to everyone. Moreover, the concrete implementation of consensus, transaction record layout, and self-implemented smart contracts make Hyperledger Besu a green framework for implementing the proposed blockchain-IoT system.
Soojin Lee, Seung-Hyun Seo, Kyubyung Kang, Qin Hu
Due to the rising number of Electric Vehicles (EV), the subsequent increase in demand for charging, as well as the long charging time, will make it difficult for drivers to charge their vehicles. Current charging service platforms inform their customers of the charging station information for the network to which they belong. However, they do not ensure the reliability and credibility of information and do not share the charging information of other charging stations. To address this issue, a model in which CSs collaborate for information sharing and charging must be developed. In this paper, we propose a blockchain-based integrated charging platform for charging cooperation. Verifier groups for each CS verify the reliability of shared information. We applied the concept of Mobile Charging Stations (MCSs) to help busy CSs, reducing EV charging latency. We also designed a contribution-based incentive distribution process to elicit active CSs' cooperation. We performed a charging scenario simulation and blockchain implementation to demonstrate the proposed model's efficacy. The simulation results showed that the proposed charging scenario with MCS application showed a 46.9 % reduction in waiting time. Also, when the number of verifier members equals the global average of EVs per charging spot, the verification time is approximately 547 ms, demonstrating that the proposed model is effective.
Abdul Haseeb Tariq, Uzma Amin
Peer-to-peer (P2P) electricity trading has received a lot of attention in the last decade and recently there has been growing interest in the evaluation of market design, classical methods, and novel approaches for multi-energy trading. The existing literature only focused on electricity/electric-gas/electric-heat networks. Therefore, a comprehensive analysis of P2P multi-energy trading (P2P-MET) in a decentralized network is required for the multi-energy like electricity, hydrogen gas, and heat all in one framework for a sustainable future. This review study aims to provide an in-depth understanding of P2P-MET in a decentralized network including layers-defined multi-source network configurations, trading platforms, classical methods, novel approaches, and mechanisms. Considering MET, the rising number of prosumers take advantage of the opportunity and make this complicated decentralized network more complex. To handle the network complexities, smart contracts using distributed ledger-based blockchain, novel algorithm-based game theory, and some other approaches are reviewed. Furthermore, this review study covers the limitations, challenges, opportunities, and benefits of P2P-MET as well as current trends and future directions for a better understanding of the readers. It concludes that P2P-MET using blockchain/game theory in decentralized networks is alternatively better and more secure. • An overview of P2P multi-energy trading (MET) reviewed in a decentralized network. • This paper presents classical methods and core approaches for P2P-MET. • Numerous pilot and under-developed projects implemented globally are reviewed. • Simulating tools commonly used by researchers for P2P-MET are briefly discussed. • Current trends and future directions are reviewed for P2P-MET sustainable future.
Alberto Butera, Valentina Gatteschi
In response to concerns about climate change and environmental sustainability, there is a global emphasis on innovative solutions to reduce emissions and optimize resource use. A key initiative is the introduction of digital passports for batteries, with the primary goal of improving the circular economy. The European Commission has taken a pioneering role by publishing regulations, laying the groundwork for digital passports and standardization. This article has a twofold aim: first, with the aim of supporting the adoption of batteries passports, it provides an overview of current initiatives and regulations in the context of electric vehicle batteries; secondly, it examines the potential of blockchain technology in implementing digital passports, in order to demonstrate its compatibility with recent regulations, such as the one proposed by the European Commission.
Bokolo Anthony Jnr
Presently Rural Energy Communities (REC) are faced with challenges such as the inefficient distribution of energy from Renewable Energy Sources (RES), unfair pricing, and the inclusion of prosumers into the electricity market. Therefore, this article proposed an approach that employed enabling technologies such as Distributed Ledger Technologies (DLT), self-enforcing smart contracts-enabled Internet of Things (IoT), and Artificial Intelligence (AI) for sustainable energy sharing and tracking in REC. Additionally, a model is proposed based on key factors that influence the adoption of enabling technologies in REC. For the methodology qualitative data is collected from secondary sources and descriptive analysis is employed to present the key findings. Key findings from this study contributes to develop a decarbonized, decentralized, and digitized energy management approach to support the sustainability of REC. The deployment of AI can facilitate prediction short-term energy planning for RES production and consumption based on real-time data from IoT devices. More importantly, findings from this study presents use case scenarios of energy sharing and tracking, and green electric vehicle charging in REC suggesting that DLT based smart contracts, IoT, and AI offers an effective approach to accelerate the sharing and tracking of RES in REC. Besides, DLT and smart contracts enables real-time electricity consumption monitoring, energy trading management, and pricing.
Pankaj Kashyap, Upasana Dohare, Manoj Kumar, Sushil Kumar
No abstract is available for this record.
Yongxi Yi, Ao Fu, Yuqiong Li, Aoxiang Zhang
No abstract is available for this record.
Md Sahabul Hossain, Craig Rodine, Eirini Eleni Tsiropoulou
With the increasing awareness for sustainable future and green energy, the demand for electric vehicles (EVs) is growing rapidly, thus placing immense pressure on the energy grid. To alleviate this, local trading between EVs should be encouraged. In this paper, we propose a blockchain and public key infrastructure (PKI)-based secure vehicle-to-vehicle (V2V) energy-trading protocol. A permissioned blockchain utilizing the proof of authority (PoA) consensus and smart contracts is used to securely store data. Encrypted communication is ensured through transport layer security (TLS), with PKI managing the necessary digital certificates and keys. A multi-leader, multi-follower Stackelberg game-based trade algorithm is formulated to determine the optimal energy demands, supplies, and prices. Finally, we propose a detailed communication protocol that ties all the components together, enabling smooth interaction between them. Key findings, such as system behavior and performance, scalability of the trade algorithm and the blockchain, smart contract execution costs, etc., are presented through numerical results by implementing and simulating the protocol in various scenarios. This work not only enhances local energy trading among EVs, encouraging efficient energy usage and reducing burden on the power grid, but also paves a way for future research in sustainable energy management.
Taher Al‐Shehari, Mohammed Kadrie, Taha Alfakih, Hussain AlSalman · 9 authors
The rise of Electric Vehicles (EVs) has introduced significant advancement and evolution in the electricity market. In smart transportation, the EVs have earned more popularity because of its numerous benefits including lower carbon footprints, higher performance, and sophisticated energy trading mechanisms. These potential benefits have resulted in widespread EV adoption across the world. Despite its benefits, energy management remains the biggest challenge in EVs and it is mainly because of the lack of Charging Stations (CSs) near EVs. This creates a demand for an effective, secure and reliable energy management framework for EVs. This study presents a secure data and energy trade paradigm based on Blockchain (BC) in the Internet of EVs (IoEV). BC technology prepares for the high volume of EV integration that serves as the foundation for the next generation, and to assist in developing unique privacy-protected BC-based D-Trading and storage Models. Entities evaluated for the proposed model include Trusted Authority (TA), Vehicles, Smart Meters, Roadside Units (RSU), BC, and Inter-Planetary File System (IPFS). In addition, E-trading involves several phases, including the acquiring E-trading demand requests, E-trading response requests, request matching and token assignment. Moreover, account mapping is performed using a Mayfly Pelican Optimization Algorithm (MPOA), which is created by merging the Mayfly Algorithm (MA) and Pelican Optimization Algorithm (POA). Various security features are used to protect data and energy trade in IoEV, including encryption, hashing, polynomials, and others. The testing results revealed that the MPOA outperformed the state-of-the-art results regarding memory consumption, trading rate, transaction cost, and trading energy volume with values of 4.605 MB, 91%, 0.654, and 90 kW, respectively.
Muhammad Muneem Shabir, Syed Muhammad Danish, Kaiwen Zhang
In future, the substantial rise in number of electric vehicles (EVs) will increase the charging-power demand significantly, placing considerable strain on existing charging stations. The adoption of renewable energy resources (RESs) is seen as a potential solution to address scalability of existing charging network, by leading the households to trade and capitalize on their surplus power. However, the centralized nature of EV charging infrastructure pose several security and privacy threats for EV owners and prosumers. Distributed ledger technologies offer a potential solution to the current privacy and security challenges. Thus, we propose a blockchain-based EV architecture that integrate prosumers into existing EV infrastructure. To begin with, we propose BlockDEV: a decentralized charging provider selection mechanism, which allows EVs to select a charging provider without sharing any personal information. A smart contract design is then proposed, allowing households with RESs to trade their surplus energy using dynamic pricing based on energy supply and demand, and, allowing EVs to make a decentralized charging slot reservation. Assessments reveal that BlockDEV provides 98% more dynamic pricing updates that accurately represent genuine energy shifts in the network. Furthermore, it incurs 50% fewer blockchain transactions compared to the baselines, and outperforms them on the effectiveness of the reputation system, and the preservation of location privacy.
Chuan Zhang, Jian-Chi Li, Yu‐Xin Tian, He-Shuang Li
No abstract is available for this record.
Desh Deepak Sharma, Shashank Singh, Jeremy Lin
In the networked enlarged electric vehicle (EV) charging infrastructures, the security and authenticity of the stakeholders involved in the EV energy market pool are prime important. This paper proposes an EV network hub (EVNH) comprising electric vehicles, electric vehicle aggregators (EVAs), and charging nodes in the networked EV energy market pool. The various EVAs implement different heterogeneous blockchains. The EV network hub facilitates blockchain-based secure and resilient energy trading under the grid to vehicle and vehicle to grid. The paper emphasizes interoperability challenges involving different blockchains to communicate and transfer assets or data between them. We suggest secure and trustworthy energy trading across various EVAs using multiple EV tokens for EV energy trading through cross-chain communications. The EVAs consider a Nash equilibrium-seeking strategy to find the Nash equilibrium in the non-cooperative game of EVAs. The effectiveness of the proposed EV network hub is tested using MATLAB, Solidity, and Python software.
Muhammad Tayyab Rana, Muhammad Numan, Muhammad Yousif, Tanveer Hussain · 6 authors
No abstract is available for this record.
Yunwang Chen, Xiang Lei, Songyan Niu, Linni Jian
The rapid growth of electric vehicles (EVs) and the deployment of vehicle-to-grid (V2G) technology pose significant challenges for distributed power grids, particularly in fostering trust and ensuring effective coordination among stakeholders. Establishing a trustworthy V2G operation environment is crucial for enabling large-scale EV user participation and realizing V2G potential in real-world applications. In this paper, an integrated scheduling and trading framework is developed to conduct transparent and efficacious coordination in V2G operations. In blockchain implementation, a cyber-physical blockchain architecture is proposed to enhance transaction efficiency and scalability by leveraging smart charging points (SCPs) for rapid transaction validation through a fast-path practical byzantine fault tolerance (fast-path PBFT) consensus mechanism. From the energy dispatching perspective, a game-theoretical pricing strategy is employed and smart contracts are utilized for autonomous decision-making between EVs and operators, aiming to optimize the trading process and maximize economic benefits. Numerical evaluation of blockchain consensus shows the effect of the fast-path PBFT consensus in improving systems scalability with a balanced trade-off in robustness. A case study, utilizing real-world data from the Southern University of Science and Technology (SUSTech), demonstrates significant reductions in EV charging costs and the framework potential to support auxiliary grid services.
Xin Chen
As electric vehicles (EV) become more prevalent and advances in electric vehicle electronics continue, vehicle-to-grid (V2G) techniques and large-scale scheduling strategies are increasingly important to promote renewable energy utilization and enhance the stability of the power grid. This study proposes a hierarchical multistakeholder V2G coordination strategy based on safe multi-agent constrained deep reinforcement learning (MCDRL) and the Proof-of-Stake algorithm to optimize benefits for all stakeholders, including the distribution system operator (DSO), electric vehicle aggregators (EVAs) and EV users. For DSO, the strategy addresses load fluctuations and the integration of renewable energy. For EVAs, energy constraints and charging costs are considered. The three critical parameters of battery conditioning, state of charge (SOC), state of power (SOP), and state of health (SOH), are crucial to the participation of EVs in V2G. Hierarchical multi-stakeholder V2G coordination significantly enhances the integration of renewable energy, mitigates load fluctuations, meets the energy demands of the EVAs, and reduces charging costs and battery degradation simultaneously.
Darryl R. Biggar, Mohammad Reza Hesamzadeh
Around the world policymakers and regulators are struggling with the question of how to design retail electricity tariffs in the face of increasing penetration of local generation (e.g., solar PV), smart appliances, local storage, and electric vehicles. There is a widespread recognition that retail tariffs should vary dynamically across time and space, reflecting the changing conditions (congestion and losses) on the underlying networks. But, at the same time, there is recognition that such tariffs potentially expose retail customers to substantial risk. Risk averse retail customers desire protection against price spikes and volatile wholesale spot prices. This paper seeks to derive the optimal retail contract in the special case in which the uncertainty in the market is contractible (in the sense defined here). We show that the optimal retail contract exposes the prosumer to the wholesale spot price at the margin, but also perfectly insulates the customer from risk, achieving the first-best outcome. We show how the hedge component of this retail contract can be constructed from standard-form hedge contracts. We draw out several lessons for policymakers.
Jizi Li, Fangbing Liu, Zuopeng Zhang, Longyu Li · 5 authors
Abstract Electric vehicles (EVs) and their battery recycling have recently garnered heightened attention from both firms and consumers, primarily driven by concerns related to environmental sustainability. However, consumers often grapple with uncertainties regarding the green valuation of EVs. Integrating blockchain traceability technology presents a promising solution to mitigate these ambiguities by providing traceable, immutable, and precise information. Within this context, this research, grounded in a game-theoretical framework, delves into the strategies involving blockchain traceability in the pre-purchase and post-purchase stages of EVs. Specifically, the paper analytically studies the influence of three distinct strategies, namely, non-blockchain traceability, forward blockchain traceability, and Forward–reverse blockchain traceability, on the willingness of EV manufacturers to adopt blockchain technology. In addition, the study incorporates two prevalent government subsidies to scrutinize and contrast their implications on optimal outcomes. The findings of this study uncover the nuanced relationship between adopting blockchain traceability and its impact on EV sales. Notably, the research shows that the positive impact on consumers’ surplus from blockchain adoption depends on the cost coefficient of green low-carbon levels not exceeding a particular threshold. Moreover, regarding the use of government subsidies to enhance overall social welfare, it is shown that the forward blockchain traceability strategy should align with consumer-oriented subsidies and the Forward–reverse blockchain traceability strategy with EV maker-oriented subsidies.
Jong-Hyuk Park, Inwhee Joe
In modern society, the proliferation of electric vehicles (EVs) is continuously increasing, presenting new challenges that necessitate integration with smart grids. The operational data from electric vehicles are voluminous, and the secure storage and management of these data are crucial for the efficient operation of the power grid. This paper proposes a novel system that utilizes blockchain technology to securely store and manage the black box data of electric vehicles. By leveraging the core characteristics of blockchain—immutability and transparency—the system records the operational data of electric vehicles and uses federated learning (FL) to predict their energy consumption based on these data. This approach allows the balanced management of the power grid’s load, optimization of energy supply, and maintenance of grid stability while reducing costs. Additionally, the paper implements a searchable black box data storage system using a public blockchain, which offers cost efficiency and robust anonymity, thereby enhancing convenience for electric vehicle users and strengthening the stability of the power grid. This research presents an innovative approach to the integration of electric vehicles and smart grids, exploring ways to enhance the stability and energy efficiency of the power grid. The proposed system has been validated through real data and simulations, demonstrating its effectiveness and performance in managing black box data and predicting energy consumption, thereby improving the efficiency and stability of the power grid. This system is expected to empower electric vehicle users with data ownership and provide power suppliers with more accurate energy demand predictions, promoting sustainable energy consumption and efficient power grid operations.