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.
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.
This chapter investigates the creative uses and underlying difficulties of integrating blockchain and artificial intelligence (AI) technology in electric vehicle (EV) charging systems. It thoroughly examines the industry's state today, highlighting AI-driven advancements like dynamic pricing, predictive maintenance, and user behaviour monitoring for better charging station operations. The chapter also examines how smart contracts and decentralised processes in blockchain provide safe and effective transactions in the EV charging infrastructure. Real-life case studies demonstrate effective deployments worldwide and provide insights into the advantages and practical problems. The conversation ends with a critical analysis of the issues, such as legislative barriers and data privacy concerns, and a look ahead, highlighting the revolutionary potential of blockchain and artificial intelligence in reshaping the landscape of sustainable mobility.
Dynamic energy contracts, offering hourly varying day-ahead prices for electricity, create opportunities for a residential Battery Energy Storage System (BESS) to not just optimize the self-consumption of solar energy but also capitalize on price differences. This work examines the financial potential and impact on the self-consumption of a residential BESS that is controlled based on these dynamic energy prices for PV-equipped households in the Netherlands, where this novel type of contract is available. Currently, due to the Dutch Net Metering arrangement (NM) for PV panels, there is no financial incentive to increase self-consumption, but policy shifts are debated, affecting the potential profitability of a BESS. In the current situation, the recently proposed NM phase-out and the general case without NM are studied using linear programming to derive optimal control strategies for these scenarios. These are used to assess BESS profitability in the latter cases combined with 15 min smart meter data of 225 Dutch households to study variations in profitability between households. It follows that these variations are linked to annual electricity demand and feed-in pre-BESS-installation. A residential BESS that is controlled based on day-ahead prices is currently not generally profitable under any of these circumstances: Under NM, the maximum possible annual yield for a 5 kWh/3.68 kW BESS with day-ahead prices as in 2023 is EUR 190, while in the absence of NM, the annual yield per household ranges from EUR 93 to EUR 300. The proposed NM phase-out limits the BESS’s profitability compared to the removal of NM.
The scientific community has recently focused on intelligent models for predicting and optimizing EV energy management. Despite numerous studies in energy management optimization, there’s a critical need to address the trade-off between energy consumption and occupant comfort. Existing IoT systems face challenges in data analytics security and authenticity, highlighting the need for contemporary models to overcome data privacy and cost-related issues. This study introduces a smart contract model based on optimization and control modules, aiming to manage energy consumption while satisfying user comfort requirements intelligently. Introducing a smart contract model with hierarchical layers—prediction, optimization, control, and Blockchain—the proposed approach intelligently manages energy consumption while meeting user comfort requirements. Utilizing a Kalman filter for prediction and the BAT algorithm for optimization, the model integrates modules to tailor user preferences and enhance comfort. The synergy between the optimization module and a convolutional FLC enhances system performance, ensuring minimized energy usage and elevated user comfort levels. The study also evaluates the model’s implementation of the Hyperledger Fabric network, assessing outcomes regarding caliper, latency, throughput, and resource utilization.
It is established that based on the industrial revolutions towards Industry 5.0, the population of the Earth and its well-being are increasing. To preserve and improve living conditions the development in all spheres of life is by the paradigm of sustainable development. Through the prism of the mining industry, one step could be the introduction of circular economy measures for digitized tracking of materials, repairs, consumed electricity, safety, and finances. Implementing of electric cars is an option to achieve this goal through automation, manageability, and data traceability via Industry 4.0 technologies. Such are blockchain technologies, IoT, V2V, and others. For this purpose, the appropriate types of power supplies for electric vehicles for the mining sector have been identified and information flows have been defined. They are quantity of material, consumed electricity, state of the fleet, charging of batteries and operation of charging stations, and finances. For their implementation, Hyperledger Fabric was chosen as a suitable DLT platform ([1], [2]). Based on Hyperledger Fabric, a conceptual model for tracking material quantities as a step of the circular economy is proposed. A method of communication is shown in the presence of two channels - material and repairs for an electric car.
Syed Muhammad Danish, Aroosa Hameed, Ali Ranjha, Gautam Srivastava · 5 authors
The increased charging demand resulting from the rapid development of electric vehicles (EVs) poses various challenges to the stable operation of the distribution network and smart grid. Due to the stochastic EV charging behaviour, the high charging demand at the charging stations (CSs) elevates the load curve which may lead to a spatially imbalanced load demand. As such, forecasting the highly stochastic EV charging load considering an individual EV's unique charging behaviour can result in maintaining the safe operation of the grid and distribution network. Therefore, in this work, we propose Block-FeDL, a blockchain-based Federated Learning (FL) approach for EV charging load forecasting considering the private and sensitive charging information of each EV user. Thereafter, we use a Bidirectional Long Short Term Memory (BiLSTM) model within the FeDL for predicting the EV charging load patterns at each client. Moreover, instead of using a centralized server for global model aggregation, we use blockchain technology, where the model aggregation is performed in a decentralized manner and the local model parameters shared by the FL clients can be validated and securely recorded. Lastly, the results show that the Block-FeDL outperform the second-best baseline method by 95%, 96% and 77% in terms of mean square error (MSE), mean absolute error (MAE), and root mean square error (RMSE) for forecasting the EV charging load.
Peer-to-peer (P2P) energy trading has attracted a lot of attention and the number of electric vehicles (EVs) has increased in the past couple of years. Toward sustainable mobility, EVs meet the standard development goals (SDGs) for attaining a sustainable future in the transport sector. This development and increasing number of EVs creates an opportunity for prosumers to trade electricity. Considering this opportunity, this review article aims to provide an in-depth analysis of P2P energy trading of EVs using blockchain in centralized and decentralized networks, which enables prosumers to exchange energy directly with one another. The paper is aimed to provide the reader with a state-of-the-art review on the P2P energy trading for EVs, considering different blockchain algorithms that are practically implemented or still in the research phase. Moreover, the paper presents blockchain applications, current trends, and future challenges of EVs’ energy trading. P2P energy trading for EVs using blockchain algorithms can be successfully implemented considering real-time scenarios and economically benefits smart sustainable societies.
Carbon footprint reduction can be achieved through various methods, including the adoption of renewable energy sources. The installation of such sources, like photovoltaic panels, while environmentally beneficial, is cost-prohibitive for many. Those lacking photovoltaic solutions typically resort to purchasing energy from utility grids that often rely on fossil fuels. Moreover, when users produce their own energy, they may generate excess that goes unused, leading to inefficiencies. To address these challenges, this paper proposes innovative blockchain-enabled energy-sharing algorithms that allow consumers -- without financial means -- to access energy through the use of their own energy storage units. We explore two sharing models: a centralized method and a peer-to-peer (P2P) one. Our analysis reveals that the P2P model is more effective, enhancing the sharing process significantly compared to the centralized method. We also demonstrate that, when contrasted with traditional battery-supported trading algorithm, the P2P sharing algorithm substantially reduces wasted energy and energy purchases from the grid by 73.6%, and 12.3% respectively. The proposed system utilizes smart contracts to decentralize its structure, address the single point of failure concern, improve overall system transparency, and facilitate peer-to-peer payments.
The penetration of electric vehicles (EVs) in the energy market has become a immersive paradigm for facilitating greener environment by mitigating the disadvantages of the fossil-fuel vehicles. Nevertheless, it becomes critical for charging station (CS) to handle huge number of EVs further leading to the uncoordinated and inefficient charging. Moreover, none of the authors have considered the possible EV charging scenarios for allocation at the CS. Thus, we have designed an Ethereum blockchain-based decentralized application for EV charging at the CS along with the energy trading between prosumer and consumer EVs. Further, we have formulated charging scenarios based on the energy demand and type of EV (emergency and high authority). We have deployed the smart contract in Remix Integrated Development Environment (IDE) and further built a decentralized application using Web3 to made charging allocation accessible to the EVs. Finally, the simulation results of the proposed smart contract for the application is evaluated in terms of gas consumption and cost analysis with the help of deployed smart contract in the Remix IDE.
Yu Jiang, Yingchun Feng, Jie Fan, Bo Gao · 6 authors
Decentralized peer-to-peer Local Energy Markets (LEMs) are gaining popularity as local power production from Renewable Energy Sources (RESs) increases. The study investigates a blockchain-driven LEM in which prosumers and consumers buy and sell energy independently of the involvement of a third party. The suggested scheme involves Home Energy Management (HEM) and demurrage mechanisms that enable both consumers and prosumers to reduce their power prices and improve their power usage. The end-user can likewise move the load to off-peak periods and benefit from lower energy costs from the LEM through the approach. In this solution, HEM and demurrage mechanisms are used to optimize power usage as well as energy costs. As well as providing adequate power for the LEM, it is economically beneficial for end users and the community. The proposed system in the study utilizes the Deep Deterministic Policy Gradient (DDPG) algorithm and demurrage mechanisms to optimize electricity usage and energy costs. Meanwhile, smart contract on the Ethereum blockchain regulate and safeguard the electricity trading process.
The transformative potential of blockchain technology in the renewable energy sector is increasingly gaining recognition for its capacity to enhance energy efficiency, enable decentralized trading, and ensure transaction transparency. However, despite its growing importance, there exists a significant knowledge gap in the holistic understanding of its integration and impact within this sector. Addressing this gap, the current study employs a pioneering approach, marking it as the first comprehensive bibliometric analysis in this field. We have systematically examined 390 journal articles from the Web of Science database, covering the period from 2017 through the end of February 2024, to map the current landscape and thematic trajectories of blockchain technology in renewable energy. The findings highlight several critical thematic areas, including blockchain's integration with smart grids, its role in electric vehicle integration, and its application in sustainable urban energy systems. These themes not only illustrate the diverse applications of blockchain but also its substantial potential to revolutionize energy systems. This study not only fills a crucial gap in existing literature but also sets a precedent for future interdisciplinary research in this domain, bridging theoretical insights with practical applications to fully harness the potential of blockchain in the renewable energy sector.
This paper investigates a double auction-based peer-to-peer (P2P) energy trading market for a community of renewable prosumers with private information on reservation price and quantity of energy to be traded. A novel competition padding auction (CPA) mechanism for P2P energy trading is proposed to address the budget deficit problem while holding the advantages of the widely-used Vickrey-Clarke-Groves mechanism. To illustrate the theoretical properties of the CPA mechanism, the sufficient conditions are identified for a truth-telling equilibrium with a budget surplus to exist, while further proving its asymptotical economic efficiency. In addition, the CPA mechanism is implemented through consortium blockchain smart contracts to create safer, faster, and larger P2P energy trading markets. The proposed mechanism is embedded into blockchain consensus protocols for high consensus efficiency, and the budget surplus of the CPA mechanism motivates the prosumers to manage the blockchain. Case studies are carried out to show the effectiveness of the proposed method.
Climate change persists as a pressing global issue due to high greenhouse gas emissions from fossil fuel-based energy sources. A transition to a greener energy matrix combined with carbon offsetting is imperative to mitigate the rate at which global temperature ascends. While countries have deployed faith in green hydrogen to accelerate worldwide decarbonization efforts, the concurrent rise of blockchain-operated crypto-applications, such as bitcoin, has exacerbated climate change concerns. In this study, we propose technological solutions that combine the green hydrogen infrastructure with bitcoin mining operations to catalyze environmental and socioeconomic sustainability in climate change mitigation strategies. Since the present state of crypto-operations undeniably contributes to worldwide carbon emissions, it becomes vital to explore opportunities for harnessing the widespread enthusiasm for bitcoin as an aid toward a sustainable and climate-friendly future. Our findings reveal that green hydrogen production, paired with crypto-operations, can accelerate the deployment of solar and wind power capacities to boost conventional mitigation frameworks. Specifically, leveraging the economic potential derived from green hydrogen and bitcoin for incremental investment in renewable energy penetration, this dynamic duo can enable capacity expansions of up to 25.5% and 73.2% for solar and wind power installations. Therefore, the proposed technological solutions that leverage green hydrogen and bitcoin mining, bolstered with appropriate policy interventions, can not only strengthen renewable power generation and carbon offsetting capacities but also contribute significantly to achieving climate sustainability.
Currently, there is an active use of distributed registry technology in various sectors of the economy by providing transparency, improving tracking of actions within processes, and ensuring trust in open systems. There is a need to evaluate the performance of distributed registries based on measurable indicators. The article presents an overview of distributed registries performance indicators, methods to improve the efficiency and evaluation of distributed registries.
The DLT Regulation aims to introduce a pilot regime for the practical application of distributed ledger technology (DLT) in post-trade services. The DLT Regulation seeks to provide a regulatory framework for the development of DLT multilateral trading facilities (DLT MTFs) and DLT securities settlement systems (DLT SSS), including for the granting and withdrawal of specific permissions (that is, permissions granted under this new regulation would allow market participants to operate a DLT market infrastructure and provide their services across all Member States). It aims at providing a mechanism, procedures and rules for allowing market infrastructures to experiment DLT with legal certainty and flexibility.
Sahar Yousif Mohammed, Thaar Kh. Asman, Hadeel M Salih, Alaa Mohammed Mahmood
These days, we are observing a very rapid spread of the electric vehicleindustry. This means a significant increase in the data and energy exchanged betweenthese vehicles. The existing centralized approach is less secure and more vulnerableto data destruction and manipulation by intruders. Therefore, it became necessary tosearch for an alternative that provides excellent protection for this massive amountof data and energy. Although blockchain technology and cryptocurrencies are closelyassociated, they also have many other potential applications in fields including energyand sustainability, the Internet of Things (IoT), smart cities, smart mobility, andmore. In the Internet of Vehicles (IoV) idea, blockchain can provide security forelectric vehicle (EV) transactions, enabling electricity trading to be carried out ina decentralized, transparent, and secure manner. . This paper will explain the use ofblockchain in this field and how it can handle the trade of transmitted and receivedenergy between electric vehicles. The advantages of using blockchain with electriccars and how it can secure the transactions of energy trading will be shown too. Agroup of researchers in this field and the challenges that face this technology in energytrading will be discussed too; the studies will be looked at, and recommendations forinvestments and security will be made. Additionally, the future implications of variousblockchain technologies will be highlighted.
Purpose Presently, existing electric car sharing platforms are based on a centralized architecture which are faced with inadequate trust and pricing issues as these platforms requires an intermediary to maintain users’ data and handle transactions between participants. Therefore, this article aims to develop a decentralized peer-to-peer electric car sharing prototype framework that offers trustable and cost transparency. Design/methodology/approach This study employs a systematic review and data were collected from the literature and existing technical report documents after which content analysis is carried out to identify current problems and state-of-the-art electric car sharing. A use case scenario was then presented to preliminarily validate and show how the developed prototype framework addresses the trust-lessness in electric car sharing via distributed ledger technologies (DLTs). Findings Findings from this study present a use case scenario that depicts how businesses can design and implement a distributed peer-to-peer electric car sharing platforms based on IOTA technology, smart contracts and IOTA eWallet. Main findings from this study unlock the tremendous potential of DLT to foster sustainable road transportation. By employing a token-based approach this study enables electric car sharing that promotes sustainable road transportation. Practical implications Practically the developed decentralized prototype framework provides improved cost transparency and fairness guarantees as it is not based on a centralized price management system. The DLT based decentralized prototype framework aids to orchestrate the incentivize monetization and rewarding mechanisms among participants that share their electric cars enabling them to collaborate towards lessening CO 2 emissions. Social implications The findings advocate that electric vehicle sharing has become an essential component of sustainable road transportation by increasing electric car utilization and decreasing the number of vehicles on the road. Originality/value The key novelty of the article is introducing a decentralized prototype framework to be employed to develop an electric car sharing solution without a central control or governance, which improves cost transparency. As compared to prior centralized platforms, the prototype framework employs IOTA technology smart contracts and IOTA eWallet to improve mobility related services.