A Blockchain-based Decentralized Low-carbon Electric Vehicle Charging System

Aiming at the characteristic that electric vehicles can be used as a distributed power source, we study the mutual sales mechanism of electric vehicles to realize the sales of electricity based on blockchain technology with the participation of electric power companies as the weak center. Although electric vehicles can be used as a power source to charge other electric vehicles, market realization is rarely considered. Firstly, transaction willingness is achieved among electric vehicles through a multilateral game of electric vehicle charging and discharging electricity prices. Then, the transaction content containing the charge and discharge contract power and electricity price information is spread to the entire network through the P2P network in the form of smart contracts with a consensus. In the process, power companies manage the security of transactions. Safety management includes safety check work and congestion management work. The distributed algorithms can be used by the security check in every node of the network without a central organization. However, in the absence of a centralized organization, congestion management is difficult for each node to carry out spontaneously. Therefore, power companies are required to perform weakly centralized congestion management on transactions. In the weakly centralized mode, the power company only needs to know the information about the line violation without the specific transaction information. The privacy of users is better protected. Finally, when the transaction clearing time arrives, the smart contract will automatically complete the transfer of funds based on the user's actual electricity consumption data and prior agreement. Through the research in this paper, direct power transactions between electric vehicle owners can be effectively guaranteed and realized under the condition of weak centralization of electric power companies.

Social welfare-based charging of electric vehicles in the microgrids fed by renewables

Many EU countries have used financial incentives to promote electric light commercial vehicles and decarbonise urban freight transport. However, the high costs of electric light commercial vehicles still pose a significant adoption barrier. This paper evaluates the impact of financial incentives on the total cost of ownership of electric light commercial vehicles in the European Union and their role in achieving the cost-competitiveness of electric vehicles. A pairwise comparison is performed for three weight categories of electric and diesel vehicles in twelve countries. Our analysis shows that financial incentives have a high impact on the total cost of ownership and have proven necessary to achieve electric vehicles' cost-competitiveness in most cases. However, in specific cases, financial incentives may no longer be needed as the cost of electric vehicles' ownership would have been lower than diesel vehicles even without them. This paper demonstrates the importance of adjusting government incentives to avoid unnecessary funding allocations while promoting the decarbonisation of light commercial vehicles, particularly as the number of incentives does not directly correlate with electric vehicles penetration.

The increasing trend of transportation electrification presents investors the opportunity to provide charging services to Electric Vehicle (EV) owners via the energy purchased from the wholesale electricity market. This will benefit EV owners with the availability of competitive rates compared to the regulated utility time-of-use (TOU) rates. The fundamental questions addressed in this paper are 1) will EV owners benefit from the additional choice of Electric Vehicle Charging Stations (EVCSs) compared to home charging? 2) is there any profitable market opportunity for charging stations while the retail electricity market is regulated? To this end, the strategic bidding problem for EVCSs which purchase electricity from the Day-Ahead Electricity Market (DAM) and sell it to EV owners is presented. The strategic bidding problem is constrained by the market-clearing problem within the DAM as well as EVs' charging cost minimization problem. A bi-level optimization problem formulation and a solution method are presented to address this work's research questions. The effectiveness of the proposed structure in gaining profit for EVCSs is illustrated, and it is shown that EV owners also save on their charging cost with the presence of EVCSs as a choice.

<div class="section abstract"><div class="htmlview paragraph">As electric vehicles adoption becomes more common, power grid operators are facing new challenges in managing the unpredictable and varying energy demands in the existing electrical infrastructure. Moreover, the cost of Electric vehicle is high when compared to fuel vehicle it has limited access to charging infrastructure along with the driving range that act as a key barrier preventing the drivers from making shift to EVs. When the EV usage integrates with blockchain, it mitigates the limitation in charging station infrastructure along with the former problem discussed. The lack of trust exists between EV owners and charging station providers can be solved through secure and transparent payment processing possible by blockchain based smart contract. Building charging station on blockchain will ease the automated payment through the use of smart contract and create more efficient EV charging network. Also, the blockchain-based charging system would enable EV owners know if they are being charged in excess and Prosumer know if they are being underpaid. The high initial cost is another prominent issue within the market place. To address this issue the introduction of sharing economy to the EV industry showcases another innovative solution that blockchain offers. The blockchain enabled sharing economy platform allows individuals to access collaboratively with the prosumer and the consumer. This provides alternative to traditional ownership while reduces individual financial barriers and maximizing electric vehicle utilization across the network. The EV users have great opportunity worldwide to take a stake in the future of EV adoption on blockchain. Therefore, this work demonstrates the sharing economy while designing, building, and customizing smart contracts for prosumers and consumers by enabling decentralized payment systems. Our research aims to develop decentralized charging electronic payment systems using blockchain and customized smart contracts to build and design the application. For blockchain Solidity programming language is used. The application displays the charging process, payment system, and charging history information.</div></div>

Scheduling model of electric vehicles charging considering inconvenience and dynamic electricity prices

The increasing penetration of electric vehicles (EVs) brings new flexibility in power grid operation. As EVs serve the main purpose of transportation, EV owners will charge their vehicles based on their driving patterns. Given the clustering charging behavior, uncontrolled charging can burden the distribution grid, increasing system operation costs. As a distributed energy resource (DER) with a highly mobile and distributed nature, aggregated EVs also have the capabilities to provide ancillary services to the power grid to alleviate voltage violations and/or regulate frequency. This paper proposes a new bilateral trading and auctioning mechanism between aggregators and EVs. In this environment, EVs and aggregators can trade energy and ancillary services in a decentralized manner. The proposed EV transactive energy methodology for auctioning and clearing is based on the alternating direction method of multipliers (ADMM) optimization and blockchain technology. Simulation results for the proposed EV TRADing of Energy and Services (EV-TRADES) environment are provided using the NYISO market price data. Numerical results demonstrate the capability to coordinate EV charging and incentivize EVs to provide ancillary services.

Electric vehicles (EVs) are becoming a popular mode of transportation. However, one of the main concerns for EV and CNG owners is the availability and accessibility of charging stations. In this project, we present the development and implementation of an EV and CNG charging station finder web application. The app uses the Google Maps API to display the location of nearby pay stations and provide details such as connection type, availability and price. The app also allows users to filter charging and CNG stations according to their preferences and report charging stations as false or unserviceable. User testing is done to evaluate the usability and performance of the application. The results show that the app is easy to use and provides accurate and up-to date information on payment facilities In this system, the User is able to manage All his EVs inside the app plus he has search/book as lot in advance in the charging station. The User can also search an EV station based on nearby, city or kilometers. The System also provides a Roadmap if you enter source & destination with the charging stations on the way according to the kilometers entered. Admin will manage all the stations and slots. The need for developing infrastructure such as charging stations is undeniable. This EV Charging Station web application has been developed to help EV drivers locate available charging stations near them. After locating a charging station, users can also book a slot at the station to charge their vehicle. EV owners can also use this system to plan their trips more efficiently. Users simply need to specify the source and destination. Based on these two parameters, this system prepares a roadmap with all available charging stations along the journey.

An intelligent electric vehicle charging system for new energy companies based on consortium blockchain

Due to the rapid spread of electric vehicles worldwide, the importance of building an efficient and safe electric vehicle charging system is increasing. In order to implement the decentralized vehicle network, blockchain technology is being leveraged in the electric charging system. However, since the blockchain ledger is public, the charging payment and authentication information is visible. While there have been attempts by blockchain-based charging systems to safeguard an electric vehicle’s privacy and anonymity, the electric vehicle’s identity can still be revealed by the electric vehicle service provider. Thus, we proposed a privacy-preserving payment model for electronic charging. We applied a traceable ring signature so that the electric charging station and the electric vehicle service provider cannot specify the electric vehicle within the ring group. When the EV reuses the token, it will be discovered during the tracing process. In addition, by using a blockchain-based smart contract, malicious user information can be stored and shared in a blockchain. As a result, secure token authentication and energy trading are possible.

Nowadays, environmental pollution and the limitation of fossil fuels are taken into consideration by many countries. Worries over the pollution from fossil fuels in the transportation sector have prompted the inclination to use electric vehicles (EVs) instead of the conventional internal combustion engines. It is predicted that at least 10% of the US transportation fleet will be changed to EVs by 2020, and they could have 50% of vehicle market share by 2050. Furthermore, by increasing the penetration of the renewable energy resources in the power system, we can use these clean energies to charge EVs; in this way, we can solve air pollution and fossil fuels problems. Implementing this procedure needs many infrastructures to handle the charging demand of the EVs properly. It should be mentioned that by increasing the penetration of the EVs in the power system, we are confronted with large load demand by sharp stochastic behavior which can have significant effects on the power system parameters such as voltage variations and power loss. To handle this problem, we need to charge EVs in smart mode by considering the power system constraints. In this way, some internal units between EV owners and power system operator, which are named as aggregators, are considered. These units buy electricity energy from the power system operator and sell it to the customers (EV owners). The main goal of these units is to find the optimal charging procedure of EVs by considering power system limitations and minimizing the EV owners charging cost. Here, the main challenge for aggregators to find the optimal charging solution is to model the EVs travel behavior and estimate the value and time of their charging demand in a precise manner. If they can estimate these parameters accurately, it is highly profitable for them and has a significant effect on their income. In this regard, we need to find the precise approach to forecast the EVs travel behavior with high accuracy which has a potential to handle large dimension data; because in the near future by increasing the penetration of the EVs in the transportation fleet, we will face big data problem. To handle the large dimension data sets, machine learning tasks, which are developed based on artificial intelligence concept, can be regarded as the best solution, and these approaches have acceptable performance on other data engineering tasks such as time series forecasting, image and voice processing, and pattern recognition. In this chapter, we introduce an artificial intelligence-based approach for modeling the EVs travel behavior and describe it in full details.

As the number of electric vehicles (EVs) continues to grow, there is an increasing need for smart charging strategies. This paper exploits the vehicle-to-vehicle (V2V) concept to leverage EVs’ diverse charging patterns and unlock the value of flexibility by enabling energy transfer among EVs. We formulate a cost minimization problem for an EV charging station to optimize the V2V schedule together with vehicle-to-grid (V2G), grid-to-vehicle (G2V) charging, as well as the use of renewable energy. When EVs perform V2V to transfer energy to charge EVs, the traditional cost-minimizing approach may overuse some EVs with lower costs to perform V2V. We address the fairness issue by developing fair V2V energy transfer strategies to avoid the excess discharge from individual EVs. We introduced three kinds of fairness metrics in the V2V optimization problem to demonstrate the fair energy transfers. In addition, we formulate baseline optimization problems without V2G or V2V and compare the results to prove the potency of V2V concept along with V2G method. The simulation results demonstrate that V2V can significantly reduce EV charging costs and highlight the trade-off between fairness enforcement and charging cost minimization.

This paper investigates the day-ahead optimal reserve management problem of electric vehicle (EV) aggregator. Geographically dispersed EVs are coordinated by the aggregator to participate in the day-ahead reserve market. A bilevel model is proposed to formulate the interaction between the aggregator and the EV owners. In the upper level, the EV aggregator aggregates the reserve capacity provided by the EV owners and then bids in the reserve market. In the lower level, the EV owners decide their optimal energy charging/discharging and reserve capacity based on the reserve price released by the aggregator. Compared with existing works, our proposed bilevel model is more practical. To be specific, we take into account the exclusive right constraint for accessing EV battery, i.e., the battery cannot be simultaneously accessed by the EV owner and the aggregator. This practical model leads to a bilevel mixed integer nonlinear program, which is difficult to solve because the lower level problem incorporates nonconvex integer variables. A novel exact algorithm is developed to solve it and the finite convergence is proved. Comprehensive case studies demonstrate the economic merits of our proposed model to both the aggregator and the EV owners. We also compare the solution optimality with the state-of-the-art approach and thus validate the effectiveness of our proposed exact algorithm.

The empirical probability of integrating CSP and its cost optimal configuration in a low carbon energy system of EUMENA

The world is moving rapidly from carbon-producing vehicles to green transportation systems. Electric vehicles (EV) are a big step towards a friendly mode of transport. With the constant rise in the number of electric vehicles, we need a widespread and seamless charging infrastructure that supports seamless charging and billing. Some users generate electricity using solar panels and charge their electric vehicles. In contrast, some use charging stations, and they pay for vehicle charging. This raises the question of trust and transparency. There are many countries where laws are not strictly enforced to prevent fraud in payment systems. One of the preeminent problems presently existing with any of the trading systems is the lack of transparency. The service provider can overcharge the customer. Blockchain is a modern-day solution that mitigates trust and privacy issues. We have proposed a peer-to-peer energy trading and charging payment system for electric vehicles based on blockchain technology. Users who have excess electricity which they can sell to the charging stations through smart contracts. Electric vehicle users can pay the charging bills through electronic wallets. We have developed the electric vehicle’s automatic-payment system using the open-source platform Hyperledger fabric. The proposed system will reduce human interaction and increase trust, transparency, and privacy among EV participants. We have analyzed the resource utilization and also performed average transaction latency and throughput evaluation. This system can be helpful for the policymakers of smart cities.