Blockchain Papers

Weijia Jin, Chenhui Li, Min Zheng

No abstract is available for this record.

Junxiang Li, Xuan Liu, Xinping Shao

The task of carbon emission reduction is severe in the power industry in China under the national goal of “carbon peaking and carbon neutrality”. The current carbon reduction is mainly based on supply side, but the effect is limited. To solve this problem, this paper proposed a coordinated supply–demand carbon emission reduction strategy based on blockchain technology. Based on the carbon emission reduction of complementary thermal power and renewable energy under the carbon trading mechanism of power supply side, users are made to participate in the individual level carbon trading mechanism with the help of blockchain technology, and the carbon emission reduction in power demand side is guided through the market mechanism, thus forming a supply–demand collaborative carbon emission reduction strategy of source side control and terminal inhibition. By analyzing the decision changes of both the supply and demand sides of electricity before and after the introduction of blockchain, quantifying the influence of blockchain on electricity quantity, electricity price and users’ utility in turn, and establishing the personal carbon trading mechanism supported by blockchain, a game model of two-side interaction between supply and demand was constructed. The simulation results show that the collaborative carbon emission reduction strategy based on blockchain gives full play to the potential of carbon reduction in power demand side, and the personal carbon trading mechanism can better inhibit terminal carbon emissions, which is conducive to the deep carbon emission reduction of the power industry.

Kuo-Yang Wu, Tzu-Ching Tai, Bo-Hong Li, Cheng‐Chien Kuo

Under net-zero objectives, the development of electric vehicle (EV) charging infrastructure on a densely populated island can be achieved by repurposing existing facilities, such as rooftops of wholesale stores and parking areas, into charging stations to accelerate transport electrification. For facility owners, this transformation could enable the showcasing of carbon reduction efforts through the self-use of renewable energy while simultaneously gaining charging revenue. In this paper, we propose a dynamic energy management system (EMS) for a solar-and-energy storage-integrated charging station, taking into consideration EV charging demand, solar power generation, status of energy storage system (ESS), contract capacity, and the electricity price of EV charging in real-time to optimize economic efficiency, based on a real-world situation in Taiwan. This study confirms the benefits of ESS in contracted capacity management, peak shaving, valley filling, and price arbitrage. The result shows that the incorporation of dynamic EMS with solar-and-energy storage-integrated charging stations effectively reduces electricity costs and the required electricity contract capacity. Moreover, it leads to an augmentation in the overall operational profitability of the charging station. This increase contains not only the revenue generated from electricity sales at the charging station but also the additional income from surplus solar energy sales. From a comprehensive cost–benefit perspective, introducing this solar-and-energy storage-integrated EMS can increase facility owners’ net income by 1.25 times compared to merely installing charging infrastructure.

Madhusudan Naik, Akhilendra Pratap Singh, Nihar Ranjan Pradhan, Neeraj Kumar · 6 authors

The rapid increase in the adoption of Electric Vehicles (EVs) and the installation of Charging Stations (CSs) are key components for bidirectional energy transfer between EVs and CSs. However, the traditional techniques of energy trading have issues of trust, scalability, traceability, provenance, and authenticity among energy prosumers. To address these challenges, particularly information imbalances between energy buyers and sellers, we propose TokenGreen, a novel framework that leverages blockchain and Non Fungible Tokens (NFTs) to enable participants to have ownership of energy assets through investments in distributed energy generation, distribution, and clean energy infrastructure, leading to trust and transparency management among the participants. The proposed framework uses Ethereum Virtual Machine (EVM), ERC-721 NFT, Inter Planatery File System (IPFS), and Solidity smart contracts to develop an NFT based energy marketplace. Various smart contracts, contract events, functions, algorithms, have been designed and integrated into the energy marketplace to facilitate the minting, creation, purchase, and resale of NFT tokens, including energy trading. To assess the performance of the proposal, experiments are performed using tools such as Geth, Hyperledger Caliper, and the Ethereum SDK. The obtained results indicate that the average maximum latency for CreateToken reached 12.39s, while BuyToken and ResellToken reached 11.02s. Additionally, the average minimum latency for CreateToken, BuyToken, and ResellToken reached 10.46s, 10.03s, and 9.14s, respectively. On average, memory consumption ranged from 640 to 775 MB, while CPU usage averaged between 30% and 55% for each function. The performance analysis indicate CreateToken has low throughput, while BuyToken shows higher, and ResellToken exhibits the highest throughput due to fewer write operations. TokenGreen demonstrates superior performance compared to the existing state-of-the-art, considering the mentioned parameters.

Jens Malmodin, Nina Lövehagen, Pernilla Bergmark, Dag Lundén

No abstract is available for this record.

Charithri Yapa, Chamitha de Alwis, Uditha Wijewardhana, Madhusanka Liyanage

Integrating renewable energy generation in the consumer end has transformed users acting as both buyers and sellers. Uncoordinated interconnections lead to degraded power quality, which demands for continuous network monitoring. This study evaluates the applicability of the network monitoring process to develop a novel consensus protocol, customized for blockchain platforms integrated with smart grids. The motivation for integrating grid monitoring with the blockchain consensus mechanism lies in the significance of decentralized architectures such as distributed ledger technologies for future energy grids. Existing blockchain consensus mechanisms have exhibited excessive energy usage and low scalability due to the additional workload associated. Hence, the study proposes a customised solution, which has the advantage of combining grid monitoring with the blockchain consensus protocol. This eliminates the additional computation burden, reduces the cost of execution, and improves the transaction throughput of the blockchain consensus mechanism.

Sachi Chaudhary, Rajesh Gupta, Riya Kakkar, Sudeep Tanwar · 7 authors

No abstract is available for this record.

Yuxiao Liang, Zhishang Wang, Abderazek Ben Abdallah

In the present era, energy issues are a significant concern, and the energy trading market is the crucial sector to facilitate supply-demand balance and sustainable development. For better demand response and grid balancing, vehicle-to-grid (V2G) technology is rapidly gaining importance in energy markets. To narrow the gap between ideal V2G goals and actual applications needs, energy trading system has to overcome the challenges of over-centralized structure, inflexible timeline adaptation, limited market scale and energy efficiency, excessive feedback time costs, and low rate of economic return. To address these issues and ensure a secure energy market, we propose a decentralized intelligent V2G system called V2G Forecasting and Trading Network (V2GFTN) to achieve efficient and robust energy trading in campus EV networks. A multiple blockchain structure is proposed in V2GFTN to ensure trading security and data privacy between energy requests and offers. V2GFTN also integrates energy forecasting functions for EVs with a smart energy trading and EV allocation mechanism called SRET so that the EVs with driving tasks can supply their extra power back to the grid and achieve higher energy efficiency and economic profit. Through rigorous experimentation and compared with equivalent studies, V2GFTN system has demonstrated higher economic profit and energy demand fill rate by up to 1.6 times and 1.9 times than the state-of-the-art V2G approaches.

Firdous Kausar, Rami Al-Hamouz, Sajid Hussain

The widespread adoption of electric cars (EVs) can be attributed to their many advantages over conventional gas-powered automobiles. However, there may be difficulties in incorporating EVs into the grid due to increased energy demand and peak load. We propose a blockchain-based federated learning scheme using different linear regression algorithms for energy demand prediction for EVs. The information gathered from EVs is stored on the blockchain network. Only those with the proper credentials can decrypt the data from its encrypted storage. Data from EVs is utilized to train a machine learning model with the use of a federated learning algorithm. Each EV is used to train a model, and then the models’ parameters are distributed throughout the blockchain. Our approach is innovative in analyzing of BCFL communications overhead and latency issues, while delving deeper into its dynamics to measure and reduce communication delays to maximize system efficiency. The implementation results verify the effectiveness of our system in anticipating EVs’ energy requirements. For the training of the BCFL model, a huge real-world dataset was used from over 60,000 transactions at EV charging stations in Boulder city, Colorado. The results show that the framework is reliable, since all the models have R2values above 0.91, which indicates a high degree of accuracy in predicting energy use.

Ameni Boumaiza, Antonio Sanfilippo

Distributed energy generation disrupts traditional energy markets by blurring the line between producers and consumers and enabling the emerging prosumers to trade energy in per-to-peer transactions. Blockchain technology automates peer-to-peer energy trades in a distributed database architecture that achieves security and cost-effectiveness using cryptographic hashing and consensus-based verification. Before its deployment, an energy blockchain trading application needs to be tested in a virtual environment that is analogous to the real-world setting to ensure correct implementation and identify potential obstacles and opportunities. This study suggests executing such a testing within a framework that integrates a Geographic Information System (GIS) environment with an Agent-Based Modeling (ABM) simulation platform. The application of this testing framework to a case study of solar Photovoltaic (PV) energy trade among household peers in in Doha, Qatar, shows how the integration of the GIS environment offers a detailed analysis of transactions in local housing community markets. The ABM simulation reveals that population density, energy market prices, and household proximity significantly influence residential PV energy trading in Qatar. The ensuing simulation environment provides a decision-support platform for designing and implementing decentralized trading systems based on blockchain technology, and high-performance computing can enhance model performance for scalable energy blockchain analysis in Qatar and beyond.

Imran Hussain, Hafiz Ashiq Hussain, Nasim Ullah, Stanislav Mišák

Conventional centralized optimization and management approaches may not work well in an emerging and distributed energy system with a high penetration of electric vehicles and green energy sources. The usage of blockchain technology is growing as a strong competitor as it can provide this kind of market with a transparent, secure, and efficient transactional platform. Nevertheless, most energy systems usually depend on complex mathematical optimization, which is poorly incorporated into blockchain applications. Moreover, time-sensitive message dissemination requirements, resource-intensiveness, high computational load, and communication overhead of the traditional blockchain consensus mechanisms make it difficult to connect with real-time vehicular networks. Here, we employ Proof of Intelligence (PoI), a novel prosumer-centric blockchain consensus mechanism to develop a comprehensive model of trust based on commitments of supply and demand through the application of peer-to-peer energy exchange with effective and dynamic integration of renewable sources and electric vehicles both in the day ahead and real-time energy trading platforms. Additionally, the PoI smart contract is developed to seamlessly incorporate mathematical optimization with an increased level of security, scalability, throughput, and low confirmation latency of transactions achieved through the reduced effort involved in finding and confirming the optimal solution in comparison with conventional blockchain consensus mechanisms.

Alia Al Sadawi, Eiman ElGhanam, Mohamed S. Hassan, Ahmed Osman

With the increasing investments in on-the-move electric vehicle (EV) charging solutions and wireless charging lanes (WCLs), coordination of the energy requirements of mobile EVs becomes essential to ensure load balancing while maximizing demand coverage. This necessitates the development of online and mobility-aware algorithms for assigning EV-to-charging lanes. In this work, a decentralized, blockchain-based EV assignment and energy allocation system is presented. The objective of system is to coordinate the charging requirements of mobile EVs among the available WCLs within a network of EV chargers in an Internet of Electric Vehicles (IoEVs). This blockchain-based system offers higher security, transparency and immutability over traditional rule-based coordination schemes. It also offers an integrated end-to-end framework that handles user registration, authentication, lane activation and energy reporting. This is in addition to its main functionality of establishing a real-time and load-balanced EV-to-WCL assignment process that addresses the EV energy requirements within constraints of traveling distance and remaining EV energy. The proposed system is tested on the Ethereum blockchain and its security and transparency are both validated accordingly.

Alessandro Neri, Maria Angela Butturi, Henrique L. Sauer, Francesco Lolli · 6 authors

The growing demand for electric vehicles necessitates an efficient and sustainable life-cycle management of lithium-ion batteries. This work examines existent literature on digital battery passports, crucial for high-quality data for decision-making purposes, and distributed ledger technologies as transparent and efficient enablers. An hybrid BWM-TOPSIS approach is employed to rank various platforms for digital passport implementation in an automotive company. The analysis identifies Hedera as the most suitable ledger, followed by IOTA and EOS. Future research directions include empirical validation of the findings and exploring collaborative decision-making models to enhance the robustness of the selection process.

Liaqat Ali, M. Imran Azim, Nabin B. Ojha, Jan Peters · 8 authors

Peer-to-peer (P2P) trading in a local energy market (LEM) offers various participants the opportunity to negotiate and strike energy deals among themselves using a distributed ledger technology called blockchain. In this paper, a new local model is presented using a layer-2 scalability solution for second-generation (Gen2) blockchain technology to enable P2P trading among four types of participants: consumers, prosumers with solar photovoltaic (PV) systems, prosumers with solar PV systems and battery energy storage systems (BESSs), and electric vehicles (EVs). The proposed LEM trading platform involves several critical steps, including the creation of typical forecasting profiles for load consumption, solar generation, and battery state-of-charge (SOC) through a forecasting solution. Next, the LEM participants place their pricing bids using a trading agent service, and the trading engine collects the profiles data and bid prices, which performs matchmaking in a forward-facing market. The output of the trading engine consists of dispatch signals for prices and energy values that are sent to each participant to execute actual trading. Furthermore, the trading engines store the accepted and past bidding data and energy values of P2P trades for each participant in blockchain technology, which can be retrieved and displayed on the LEM user interface screens of participants and administrators using their blockchain addresses at any time during the trading process. This study focuses on simulating proposed LEM models, incorporating functional limitations and market rules. These rules aim to reduce energy costs, enhance margins for utilities and retailers, and mitigate grid congestion through BESSs, resulting in reduced operational and capital expenditure. LEM outcomes are analysed and compared with a Business-as-usual (BAU) model. Participants’ energy trading behaviour, cost-revenue dynamics, grid impact, and blockchain implementation costs are explored. The study highlights LEM benefits in terms of reduced CO2 emissions by 984 kg CO2, increased self-sufficiency by 2.2%, and improved financial benefits of all participants by 21.6%. The use of modern blockchain technology guarantees secure data storage and rapid, cost-effective energy trading, thereby making the proposed LEM platform a viable solution in the distribution market.

Md Moniruzzaman, Abdulsalam Yassine, M. Shamim Hossain

Next-generation consumer electronics and electric vehicle (EV) energy charging technology promise transformative advancements in the automotive industry. One of the main challenges that hinders consumers’ experience is range anxiety particularly relevant in locales where the installation of fixed charging stations (FCSs) is beset by logistical hurdles, notably in rural regions. With the advancement of consumer electronics especially in the design of Mobile Charging Stations (MCSs), EV drivers can now access these MCSs to exchange energy. However, concerns regarding data security and the best strategies to select an MCS to trade energy may negatively impact consumer experiences. This paper delves into the conception of intelligent remedies by proposing the integration of reinforcement learning and blockchain technology to empower EV drivers to access and securely exchange energy with MCSs. We design a Proof of MCSs (PoMCS) as a consensus protocol to select the winning MCSs as block miners in the blockchain. The results of our experiment show that the average gain for the MCSs increases when using the proposed model and therefore inclined to serve more EVs.

Bokolo Anthony

Presently, majority of car-pooling services depend on a central third party which makes these platforms susceptible to data privacy, security concerns, and a single point of failure. Moreover, drivers and passengers are charged with different services fees by the electric mobility service provider. The emergence of emerging technologies such as Distributed Ledger Technologies (DLT) can foster trust, boost electric car-pooling business models. Hence, DLT is utilized to store electric car-pooling trips, drivers, and passengers’ information to ensure user privacy and maintain security. Similarly, social practice theories such as Community of Practice (CoP) is progressively considered as a significant structure within societies as it aids the development and sharing of resources across groups. But very little attention has been devoted to examined how CoP can be employed to support the design of decentralized on-demand electric car-pooling. Leveraging CoP and DLT, this paper proposes a decentralized community of practice-based model that enables drivers to publish electric car-pooling services and passengers to be matched to a driver without depending on a trusted third party. A systematic literature review was adopted to collect data and a case study of a decentralized on-demand electric car-pooling was presented. Findings from this study highlights conceptualization of CoP for improving decentralized on-demand electric car-pooling and provide insights on efficient decentralized mechanisms for electric car-pooling. Theoretically, this article identifies the current problems, state-of-the-art of decentralized electric car-pooling. For policy implications this study provides guidelines to effectively govern and manage the development of on-demand electric car-pooling for sustainable public transportation.

J. Shanmugapriyan, N. Karuppiah, S. Velliangiri, S. Muthubalaji

No abstract is available for this record.

Zhongmiao Sun, Qi Xu, Jinrong Liu

Blockchain technology is very useful for combating counterfeits and verifying the authenticity of products for consumers. This paper studies blockchain adoption in a two-level supply chain consisting of a brand supplier and a retailer. Our contribution using the game-theoretic framework is to consider the various preferences that consumers may have for blockchain-supported products and to investigate the value and effects of blockchain in a traditional wholesale channel with different power structures and a platform-based-agent selling channel. We confirm that consumer aversion to blockchain will lower retailer incentive to adopt blockchain, while the opposite will occur if consumers are interested in blockchain. We find that the market leader with power advantage is more motivated to adopt blockchain while the follower has less motivation. We also find that the brand supplier will be willing to move to the agent selling channel if the unit cost of the blockchain is low and the platform commission rate is medium. Moreover, an interesting finding is that blockchain can achieve a win–win-win outcome for the brand supplier, retailer, and consumers under a certain critical threshold, which may cause unfair distribution of supply chain profit and may also be detrimental to the establishment of agent selling.

Conor Mullaney, Adnan Aijaz, Rasheed Hussain

Efficient energy management of Distributed Re-newable Energy Resources (DRER) enables a more sustainable and efficient energy ecosystem. Therefore, we propose a holistic Energy Management System (EMS), utilising the computational and energy storage capabilities of nearby Electric Vehicles (EVs), providing a low-latency and efficient management platform for DRER. Through leveraging the inherent, immutable features of Distributed Ledger Technology (DLT) and smart contracts, we create a secure management environment, facilitating interactions between multiple EVs and energy resources. Using a privacy preserving load forecasting method powered by Vehicular Fog Computing (VFC), we integrate the computational resources of the EVs. Using DLT and our forecasting framework, we accommodate efficient management algorithms in a secure and low-latency manner enabling greater utilisation of the energy storage resources. Finally, we assess our proposed EMS in terms of monetary and energy utility metrics, establishing the increased benefits of multiple interacting EVs and load forecasting. Through the proposed system, we have established the potential of our framework to create a more sustainable and efficient energy ecosystem whilst providing measurable benefits to participating agents.

Rongjing Lv, Senlai Zhu

In the rapidly evolving phase of the new energy vehicle industry, there is a shortage of charging stations for electric vehicles, leading to frequent unavailability of charging spots in parking lots. Additionally, users often have to pay high parking fees. In such a scenario, a method for sharing charging stations of multiple types is proposed. Due to the different owners of charging stations, real-time sharing of information between the charging equipment and users becomes challenging. Consequently, some charging stations remain idle for extended periods, resulting in low utilization. This paper employs blockchain technology to secure the information of both charging station owners and users. Furthermore, a multi-objective optimization algorithm is applied to consider multiple types of charging stations simultaneously, resulting in a solution that can be implemented using smart contracts.

Marco Pasetti, Salvatore Dello Iacono, Davide Astolfi, Antony Vasile

While the transition to fully electrified road mobility is expected to reduce greenhouse gas (GHG) and pollutant emissions, Electric Vehicles (EV s) still face challenges concerning infrastructure impact, installation costs, and indirect GHG emissions. Recent research has highlighted the potential benefits of optimal EV charging schedules and Vehicle-to-Grid functions in providing flexibility to power grids and global GHG emission reduction. Nevertheless, these solutions are complicated by interoperability and regulatory challenges. Distributed Ledger Technologies (DLTs) have been proposed to tackle these issues, but the lack of standardization in DLT for EV charging architectures may constrain their full potential. This study aims to establish a framework for designing DLTs in EV charging infrastructures, presenting an EV charging reference architecture and examining its characteristics and implications from the DLT perspective. The study emphasizes the impact of multiple and concurrent communication protocols on the implementation of DLTs, suggesting that further standardization must be agreed upon by DLT specialists and EV domain experts.

Saravanakumar Ramasamy, Koperundevi Ganesan, Banumalar Koodalsamy

No abstract is available for this record.

Muhammad Khalid Khan, Fadzil Hassan, Jahwan Koo, Mazin Abed Mohammed · 9 authors

No abstract is available for this record.

Sachi Chaudhary, Riya Kakkar, Mohammad S. Obaidat, Rajesh Gupta · 6 authors

The extensive deployment of electric vehicles (EVs) globally has become an alternative to fossil-fuel or gasoline vehicles to tackle harmful greenhouse gas emissions. But, huge EV charging demand can bring challenges to the charging infrastructure by destabilizing the grid stability and affecting efficient EV charging. Thus, the aforementioned challenges can be addressed by facilitating the energy trading (ET) between EVs which can act as prosumers or consumers. Thus, we have proposed a blockchain-based secure ET scheme for EVs coordination using Interplanetary File System (IPFS) protocol to mitigate the data storage cost issues of the blockchain. Opportunistically, we have considered various ET scenarios to coordinate the communication between prosumer and consumer based on the waiting time and priority levels. Moreover, the data communication between EVs is considered via a 5G communication network for highly reliable and efficient ET. Finally, the proposed scheme is evaluated by executing the smart contract using Remix Integrated Development Environment (IDE) with various performance metrics such as gas consumption (SF5 acquires maximum value of 186571 gas) and cost (execution (SF5 acquires maximum value of 120371 gas) and transaction cost (SF4 acquires maximum value of 124865 gas) ) analysis. Additionally, security analysis of the proposed scheme is tested using Echidna tool which shows the working of the smart contract without any vulnerability and bug.