With the rapid emergence of smart grids, charging coordination is considered the intrinsic actor that merges energy storage units (ESUs) into the grid in addition to its substantial role in boosting the resiliency and efficiency of the grid. However, it suffers from several challenges beginning with dependency on the energy service provider (ESP) as a single entity to manage the charging process, which makes the grid susceptible to several types of attacks such as a single point of failure or a denial-of-service attack (DoS). In addition, to schedule charging, the ESUs should submit charging requests including time to complete charging (TCC) and battery state of charge (SoC), which may disclose serious information relevant to the consumers. The analysis of this data could reveal the daily activities of those consumers. In this paper, we propose a privacy-preservation charging coordination scheme using a blockchain. The blockchain achieves decentralization and transparency to defeat the security issues related to centralized architectures. The privacy preservation will be fulfilled using a verifiable aggregation mechanism integrated with an aggregated signing technique to identify the untrusted aggregator and assure the data source and the identity of the sender. Security and performance evaluations are performed, including off-chain and on-chain experiments and simulations, to assess the security and efficiency of the scheme.
A. F. M. Suaib Akhter, Tawsif Zaman Arnob, Ekra Binta Noor, Selman Hızal · 5 authors
The popularity of electric vehicles (EVs) is constantly increasing, as they use relatively greener, sustainable energy. However, it is a fact that the charging stations for EVs are yet to meet the demand. It could be a great solution if a peer-to-peer (P2P) charging system could be initiated by anyone who wants to make their garage's charge points publicly available for commercial purposes, named a home charging station (HCS). In this work, our idea is to bring interested charging stations under a network of nodes and a blockchain-based management system, where the blockchain is responsible for ensuring the authenticity of both the charging stations and charge receiver. A cryptocurrency-based payment system has also been proposed to ensure transactions' security, integrity, transparency, and immutability. A reputation management system is applied to maintain the quality of service. Miners with high processing power are used to alleviate lagging during block creation, supported by edge servers. The proposed system has been implemented by using virtual machines. A theoretical analysis is presented to assess the compatibility and possible cost requirements to implement the system in a real-world scenario.
M R Jivtesh, Rohit Mathew Samuel, M R Gaushik, Siddhi Menon · 6 authors
Blockchain is the underlying technology for cryptocurrencies. Reliable machine-to-machine automatic transactions, such as auctions, bidding, and payments, utilise the immense potential of blockchain technology. Researchers are exploring blockchain-based applications for automobiles and transportation, such as electric vehicle (EV) charging and highway user fee payment. The use of blockchain eliminates the need for third parties in transactions. This paper presents a proof of concept for using EVs as energy storage in a smart grid system. Generators, consumers, and distributed energy resources (DER), such as solar and wind, make up the elements of a smart grid. We propose storing the surplus power generated by DER in the electric vehicle's battery. When the generation is less, or there is high demand, these EVs can supply the stored energy back to the grid. We use blockchain smart contracts and Ethereum cryptocurrency to monitor and monetise the process. We also make a cost comparison of conventional internal combustion engine (ICE) vehicles and EVs, analysing the financial benefits of employing the suggested method in EV charging instead of more conventional charging methods.
Yao Suo Yao Suo, Yingsen Wang Yao Suo, Shichao Luo Yingsen Wang, Qianqian Yang Shichao Luo · 5 authors
<p>Aiming at the problems of difficult charging, long waiting time and energy loss of IoEV (Internet of electric vehicles) during peak charging period, we design a V2V (vehicle to vehicle) energy trading model to simulate the energy trading process. Considering the problems of malicious node attacks and privacy protection, we combine the V2V energy transaction model with a federated chain and explore a distributed ledger to record the V2V energy transaction process. In addition, we design a credibility mechanism to initialize nodes according to their comprehensive strength and select master nodes based on their behavioral performance of participating in consensus, which ensures the reliability of the consensus. Based on this, we propose a more efficient and promising consensus algorithm SV-PBFT (shapley value-PBFT), which simplifies the consensus process, reduces the communication overhead, and improves the consensus efficiency. The SV-PBFT consensus algorithm is used to replace the traditional consensus algorithm in V2V energy trading. The proposed SV-PBFT algorithm is validated by extensive simulation experiments, and numerical results are provided to confirm the good performance of SV-PBFT in V2V energy trading models.</p> <p>&nbsp;</p>
Social Internet of Vehicles (SIoV) falls under the umbrella of social Internet of Things (IoT), where vehicles are socially connected to other vehicles and roadside units that can reliably share information and services with other social entities by leveraging the capabilities of 5G technology, which brings new opportunities and challenges, e.g., collaborative power trading can address the mileage anxiety of electric vehicles. However, it relies on a trusted central party for scheduling, which introduces performance bottlenecks and cannot be set up in a distributed network, in addition, the lack of transparency in state-of-the-art Vehicle-to-Vehicle (V2V) power trading schemes can introduce further trust issues. In this paper, we propose a blockchain-based trustworthy collaborative power trading scheme for 5G-enabled social vehicular networks that uses a distributed market mechanism to introduce trusted power trading and avoids the dependence on a centralized dispatch center. Based on the game theory , we design the pricing and trading matching mechanism for V2V power trading to obtain maximum social welfare. We use blockchain to record power trading data for trusted pricing and use smart contracts for transaction matching. The simulation results verify the effectiveness of the proposed scheme in improving social welfare and reducing the load on the grid.
Muhammad Awais, Ayaz Ahmad, Sadiq Ahmad, Abdullah Shoukat
Electric vehicles (EVs) are getting more importance than traditional vehicles in today's era as they may lead to significant changes in society, so more research needs to be done on electric cars for their expansion. In most EV architecture, the charging station plays an important role. Due to the growth of the extended travel range of EVs, these will travel over different networks that different utility providers might serve. To mitigate this issue, we propose a solution based on the uniform Token generation concept. The concept of blockchain technology will be utilized for Token generation, as the blockchain technique is transparent and traceable; it does not require any third party for its operation. The proposed model will get information about the battery level of each EV through a communication network and based on the battery level. The corresponding best charging station will be assigned. When the EV starts to charge from the given charging station, a certain amount of tokens is transferred from the customer's wallet to that charging station's wallet.
Maria Luisa Di Silvestre, P. Gallo, Giovani Lorenzo Restifo, Eleonora Riva Sanseverino · 6 authors
The Blorin project started at the end of 2019 to support the implementation of a blockchain platform to support the energy services provision from end users by means of Demand Response and Vehicle to Grid programs. The experimental part of the project is being carried out on two Mediterranean islands and inside the University campus in Palermo. Customized smart contracts have been designed to support the active participation of end users to regulation services for the two weak electrical grids of the islands in the view of a deep penetration of renewable energy in the two energy systems. In particular, the smart contract for remuneration accounts for the very special energy situation of islands where TSO, DSO, energy seller and aggregator collapse in a unique market actor. Moreover, in islands the electricity provision is typically still relying on diesel generators thus strongly connecting the Demand Response programs benefit to the reduction of fuel consumption, as an effect of increased efficiency of diesel generators. Due to the critical international situation and to the climate crisis, fossil fuels get more and more costly, thus a speed up of the energy transition in small islands is highly needed. This paper addresses the problem of designing a customized smart contract for remuneration of Demand Response service provision in small islands.
Nowadays, EVs are rapidly increasing in popularity, and are accepted as the vehicles of the future all over the world. The most important components are their battery and charging systems. The energy capacity of EVs’ batteries has a significant potential to supply different energy requirements. Therefore, EVs must be designed in accordance with bidirectional power flow, and Electric Vehicle Supply Equipment (EVSE) should be upgraded as Electric Vehicle Power Exchange Equipment (EVPE). This power exchange infrastructure can be called Vehicle-to-Anything (V2X). V2X will also be the key solution for energy grids of the future that will turn into a much larger and smarter system with the help of emerging digitalization technologies, such as Artificial Intelligence (AI), Distributed Ledger Technology (DLT), and the Internet of Things (IoT). This study introduces a multi-layer Cyber–Physical Power Systems (CPPS) framework to explore the potential of V2X technologies allowing bidirectional charging. In addition, the impact of e-mobility is discussed from the V2X perspective. V2X has the potential to provide more practical use of electric vehicles and to bring advantages to the user in terms of both economy and comfort, thus accelerating the transformation of e-mobility and making it easier to accept.
This paper presents a method to implement cooperative Demand Side Management (DSM) approaches over a distributed communication network. Our method combines a decentralized DSM approach called Profile Steering with two distributed consensus mechanisms Proof of Work (PoW) and Proof of Stake (PoS). We make use of a network manager to moderate the network and a distributed ledger system to store the power profiles from each planning period.We evaluate our approach using publicly-available real data from 25 houses. We successfully implemented our distributed approach in Python using JSON files as blocks and performed time-performance evaluations of this implementation. We show that, distributed DSM for day-ahead planning using blockchain concepts is possible and adds an overhead of only 0.98 seconds and 3.99 seconds in the case of PoW and PoS respectively.
The emerging demand for electric vehicles in urban cities leads to the need to install a huge number of charging stations. With this requirement, electric vehicle coordination and scheduling at charging stations in real-time becomes highly tedious. Thus, there is a need for an efficient scheduling mechanism for electric vehicle charging at charging stations. This paper proposes a novel blockchain and Internet of Things-based consensus mechanism called COME for secure and trustable electric vehicle scheduling at charging stations. The proposed mechanism is intending to resolve conflicts at charging stations. The integrated InterPlanetary File System protocol facilitates a cost-efficient mechanism with minimized bandwidth for electric vehicle scheduling. The proposed mechanism ensures that there is no loss for either the electric vehicle or the charging station. We formulate different scenarios for electric vehicle charging and apply different scheduling algorithms, including first-come first-served, longest remaining time first, and coalition game theory. The performance of the proposed COME consensus mechanism is estimated by comparing it with the practical Byzantine Fault Tolerance consensus protocol and traditional systems based on the charging demand, wait time, conflict resolution, scalability, and InterPlanetary File System bandwidth parameters. The performance results show that the proposed COME consensus mechanism ensures that electric vehicles can have their vehicle charged without any conflict and that the charging station can be satisfied in terms of profit. Moreover, the proposed COME consensus mechanism outperforms the both practical Byzantine Fault Tolerance consensus protocol and the traditional system in terms of scalability and conflict resolution along with additional parameters such as wait time, charging demand, and bandwidth analysis.
The gradual transition from a traditional transportation system to an intelligent transportation system (ITS) has paved the way to preserve green environments in metro cities. Moreover, electric vehicles (EVs) seem to be beneficial choices for traveling purposes due to their low charging costs, low energy consumption, and reduced greenhouse gas emission. However, a single failure in an EV’s intrinsic components can worsen travel experiences due to poor charging infrastructure. As a result, we propose a deep learning and blockchain-based EV fault detection framework to identify various types of faults, such as air tire pressure, temperature, and battery faults in vehicles. Furthermore, we employed a 5G wireless network with an interplanetary file system (IPFS) protocol to execute the fault detection data transactions with high scalability and reliability for EVs. Initially, we utilized a convolutional neural network (CNN) and a long-short term memory (LSTM) model to deal with air tire pressure fault, anomaly detection for temperature fault, and battery fault detection for EVs to predict the presence of faulty data, which ensure safer journeys for users. Furthermore, the incorporated IPFS and blockchain network ensure highly secure, cost-efficient, and reliable EV fault detection. Finally, the performance evaluation for EV fault detection has been simulated, considering several performance metrics, such as accuracy, loss, and the state-of-health (SoH) prediction curve for various types of identified faults. The simulation results of EV fault detection have been estimated at an accuracy of 70% for air tire pressure fault, anomaly detection of the temperature fault, and battery fault detection, with R2 scores of 0.874 and 0.9375.
Abstract A global push to achieve universal electricity access, paired with drastic reductions in the cost of decentralized electricity technologies, has led to significant research on how best to roll out access to rural communities in sub-Saharan Africa. Various geospatial electrification models have been developed to aid the decision-making process considering decentralized grid alternatives such as mini-grids and solar home systems. Despite these tools suggesting that in many cases, decentralized systems are a more cost-effective electricity access pathway, grid extension still predominates in practice. This is due, at least in part, to institutional structures in most countries that provide significant direct and indirect subsidies to grid extension projects, commonly through publicly-owned utilities. These sources of finance are generally not available to primarily privately operated off-grid energy service providers. However, the subsidy provided for grid extension projects is not well understood. In this paper, we employ utility grid extension costs and revenue data, and geospatial grid infrastructure data to estimate the size and distribution of subsidy implicitly provided to rural grid extension projects for 129 communities in Mombasa County, Kenya. We also estimate subsidies for hypothetical off-grid electricity systems in the same communities that would deliver equivalent services to the grid. We allocate the cost of shared medium voltage (MV) distribution infrastructure using a marginal and an average cost method for grid extension and compare these with subsidies for off-grid systems. We find that the average of average subsidy per customer across communities for grid extension is US$5,118 and US$5,330 for the two MV cost allocation methods respectively, while for the off-grid systems the corresponding average of average subsidies are US$3,380, using a real discount rate of 1.3% evaluated from a nominal discount rate of 8% and inflation rate of 6.7%. Our results show that in the communities in our case study, 40% and 37% of the communities would command less subsidy while served by minigrids over the grid, and the switch would save 50% and 54% of the total cost for average and marginal cost allocation methods respectively. We also show that by using a multi-model approach to electrification and by reallocation of implicit subsidies that have been exclusive to grid extension to other technology options utilities can cast the net wider, without an increase in budgets.
Tehreem Ashfaq, Muhammad Irfan Khalid, Gauhar Ali, Mohammad El Affendi · 10 authors
In this paper, a secure energy trading mechanism based on blockchain technology is proposed. The proposed model deals with energy trading problems such as insecure energy trading and inefficient charging mechanisms for electric vehicles (EVs) in a vehicular energy network (VEN). EVs face two major problems: finding an optimal charging station and calculating the exact amount of energy required to reach the selected charging station. Moreover, in traditional trading approaches, centralized parties are involved in energy trading, which leads to various issues such as increased computational cost, increased computational delay, data tempering and a single point of failure. Furthermore, EVs face various energy challenges, such as imbalanced load supply and fluctuations in voltage level. Therefore, a demand-response (DR) pricing strategy enables EV users to flatten load curves and efficiently adjust electricity usage. In this work, communication between EVs and aggregators is efficiently performed through blockchain. Moreover, a branching concept is involved in the proposed system, which divides EV data into two different branches: a Fraud Chain (F-chain) and an Integrity Chain (I-chain). The proposed branching mechanism helps solve the storage problem and reduces computational time. Moreover, an attacker model is designed to check the robustness of the proposed system against double-spending and replay attacks. Security analysis of the proposed smart contract is also given in this paper. Simulation results show that the proposed work efficiently reduces the charging cost and time in a VEN.
Francesco Lo Franco, Vincenzo Cirimele, Mattia Ricco, Vítor Monteiro · 6 authors
Electric car-sharing (ECS) is an increasingly popular service in many European cities. The management of an ECS fleet is more complex than its thermal engine counterpart due to the longer ”refueling“ time and the limited autonomy of the vehicles. To ensure adequate autonomy, the ECS provider needs high-capacity charging hubs located in urban areas where available peak power is often limited by the system power rating. Lastly, electric vehicle (EV) charging is typically entrusted to operators who retrieve discharged EVs in the city and connect them to the charging hub. The timing of the whole charging process may strongly differ among the vehicles due to their different states of charge on arrival at the hub. This makes it difficult to plan the charging events and leads to non-optimal exploitation of charging points. This paper provides a smart charging (SC) method that aims to support the ECS operators’ activity by optimizing the charging points’ utilization. The proposed SC promotes charging duration management by differently allocating powers among vehicles as a function of their state of charge and the desired end-of-charge time. The proposed method has been evaluated by considering a real case study. The results showed the ability to decrease charging points downtime by 71.5% on average with better exploitation of the available contracted power and an increase of 18.8% in the average number of EVs processed per day.
With the increasing popularity of new energy vehicles (NEVs), a large number of automotive batteries are intensively reaching their end-of-life, which brings enormous challenges to environmental protection and sustainable development. This paper establishes a closed-loop supply chain (CLSC) model composed of a power battery manufacturer and a NEV retailer. The benchmark scenario of CLSC members without blockchain technology is analyzed, and the optimal recycling strategy of the manufacturer and retailer using traceability information based on blockchain technology is discussed. We generate our findings from three aspects, as follows: the manufacturer or retailer is more willing to take the responsibility of recycling when the proportion of retired batteries that can be used in echelons is relatively high. Meanwhile, when the recycling cost is large, both manufacturers and retailers should adopt blockchain technology to obtain greater profits. Furthermore, with the improvement of traceability information transmission efficiency, a higher profit growth rate will be achieved.
Feng Xue, Kang Chang, Wei Li, Qin Wang · 8 authors
In this paper, a blockchain-enabled energy trading method is proposed to deal with the inefficiency and security issues in energy trading for electric vehicles in smart grids. It includes the design of a smart contract and the excitation mechanism of energy sharing. The credit points of each vehicle as a node are considered in the design of the smart contract, which is used to supervise the process of energy trading. A strategy to estimate the credit points of each node and describe the excitation mechanism is illustrated. The connection between the credit points and the probability that a node would be accepted for energy trading has been established. To control the energy trading access, a double auction method is used to choose the part of the nodes participating in energy trading. Only selected nodes with winning bids can supply or request energy from the blockchain-based platform. Then it reaches the conclusion that the higher the credit points they have, the more trading initiative they would have during the energy transaction and transmission. The smart contract design and the excitation mechanism proposed in this paper would reward the vehicles that perform well and punish the beguiling vehicles for regulating the trading process.
Syed Muhammad Ahsan, Hassan Abbas Khan, and Naveed-ul-Hassan
Smart buildings are being built as a synergetic deployment of electric vehicles (EVs) and renewable energy sources. Smart charging of EVs and vehicle-to-everything (V2X) technologies are seen as way forward in this context in terms of achieving economic, technological, and environmental advantages. This paper proposes a framework for multi-objective techno-economic optimization for profit maximization of multiple inter-connected buildings (with bilateral contracts) and scheduling of EVs. The optimization problem is modeled as mixed integer linear programming problem, which is solved using CPLEX solver in ILOG optimization studio. The primary building owns the photovoltaic system coupled with storage and charging infrastructure for the fleet of EVs. The optimized charging of EVs at affordable rates using local resources at primary building assists the grid in managing the EVs’ load during peak hours. Results indicate that the primary building gains up to 62% daily profit after factoring in solar, storage, and charging station deployment costs. Additionally, secondary buildings (without solar, storage and charging facilities) earn up to 20% cost savings depending upon the nature of bilateral contracts with primary building. The results further suggest that fleet of EVs gains 35%–65% savings in charging cost based on lower charging rates and V2X operations with primary and secondary buildings.
The energy sector is undergoing a vast transformation. Innovations in renewable energy production, electric vehicles (EVs) and smart meters are pushing the energy sector towards decentralisation. In this context, determining the potential of distributed ledger technology (DLT) through smart contracts and interoperability between different sections of the grid is an open point. Implementation of blockchain as a DLT into the electricity distribution network with the combination of multiple components, assists decentralisation and the connection of end-users directly to the grid. In this paper, a new method is proposed to charge EVs based on fuzzy logic and distributed ledger using a proof of stake algorithm. In this way, the risk of manipulation and loss of data, which could be detrimental to the energy sector, is reduced. The decentralisation of controlling EV's charging is achieved using this technique and the data floating inside the network is immutable and protected by the consensus mechanism of blockchain.
Electric vehicles (EVs) have gained prominence in smart transportation due to their unparalleled benefits of reduced carbon footprints, improved performance, and intelligent energy trading mechanisms. These potential benefits have increased EV adoption at massive scales, but energy management in EVs is a critical study problem. The problem is further intensified due to the scarcity of charging stations (CSs) in near EV proximity. Moreover, as energy transactions occur over open channels, it presents critical security, privacy, and trust issues among decentralized channels. To address the open limitations of trusted energy management and optimize the pricing control among EV entities (i.e., prosumers and consumers), the paper proposes a scheme that integrates blockchain and a truthful double auction strategy for trustful EV trading. To address the transaction scalability, we integrate an Interplanetary File System (IPFS) with a double auction mechanism handled through the Remix Smart Contract environment. The double auction leverages an optimal payoff condition between peer EVs. To address the communication latency, we present the scheme at the backdrop of Fifth Generation (5G) networks that minimizes the optimal payoff response time. The scheme is simulated against parameters such as convergence, profit for consumers, computation time, and blockchain analysis regarding node commit latency, collusion attacks, and EV energy consumption. The results indicate the scheme’s viability against traditional (non-blockchain) approaches with high reliability, scalability, and improved cost-efficiency.