By leveraging the charging and discharging capabilities of Internet of electric vehicles (IoEV), demand response (DR) can be implemented in smart cities to enable intelligent energy scheduling and trading. However, IoEV-based DR confronts many challenges, such as a lack of incentive mechanism, privacy leakage, and security threats. This motivates us to develop a distributed, privacy-preserved, and incentive-compatible DR mechanism for IoEV. Specifically, we propose a consortium blockchain-enabled secure energy trading framework for electric vehicles (EVs) with moderate cost. To incentivize more EVs to participate in DR, a contract theory-based incentive mechanism is proposed, in which various contract items are tailored for the unique characteristics of EV types. The contract optimization problem falls into the category of difference of convex programing, and is solved by using the iterative convex-concave procedure algorithm. Furthermore, we consider the scenario where the statistical knowledge of the EV type is unknown. In such a case, we demonstrate how to derive the probability distribution of the EV type by exploring computational intelligence-based state of charge estimation techniques, e.g., Gaussian process regression. Finally, the security and efficiency performance of the proposed scheme is analyzed and validated.
With the increasing electric vehicle (EV) integration, challenges arise in the operation of a distribution network in that charging numerous EVs at the same time may overload distribution facilities. The charging power should be distributed among the charging stations in such a way that both individual EV charging demands and security constraints are met. Meanwhile, there usually does not exist a coordinator over all EV charging stations. This paper proposes an EV charging coordination method by designing a charging power quota (permissible charging power of a charging station) trading platform on blockchain. After collecting the future charging demands from charging stations, the proposed platform distributes initial charging power quotas in an equitable and secure manner while considering facility ratings. Then, considering the elasticity of different charging stations, the platform allows EV charging stations to trade the initially-allocated charging power quota via a double auction. By matching the submitted offers and bids from charging stations, the optimal allocation of charging power quotas is realized. By designing corresponding smart contracts, a charging power quota allocation and trading platform is established based on the Ethereum blockchain, ensuring the transparency, trustfulness, and intelligence of the charging power quota trading. A case study based on an Ethereum private blockchain shows the fairness and efficiency of the proposed mechanism and the effectiveness of the method.
The massive adoption of Electric Vehicles (EVs) requires the grid system to coordinate with a large number of energy transactions, where the current grid network poses vulnerability against the excessive power loads and attacks. The difficulty of an efficient charging/discharging control mechanism lies on the randomness of future events and scalability of the transaction platform. In this paper, a Proof-of-Benefit consensus mechanism with Online benefit generating (ONPoB) algorithm is proposed on the blockchain platform to handle the EV charging/discharging loads to flatten the overall power load fluctuation. It is demonstrated that all EVs can be charged and achieves a best-known competitive ratio of 2.39. The ONPoB consensus mechanism is approved to better accommodate the EV scenario compared with other mechanisms. And the ONPoB algorithm is able to substantially reduce the Power Fluctuation Level (PFL) in comparison with popular scheduling algorithms.
This paper deals with the problems of the Plug-in Electric Vehicles charging costs in housing sector. A review of the optimal strategies is proposed and as such six algorithms are presented: three smart unidirectional and three smart bidirectional charging algorithms where the Vehicle-to-Grid (V2G) and the Vehicle-to-Home (V2H) concepts were exploited. In addition an innovative V2G algorithm named Optimal Logical Control (V2G-OLC) is introduced in this paper. This latter is dedicated to the French energy billing system within the peak/base hour's contract. All the algorithms are tested over a set of 1000 data composed of real elements with four different daily energy price profiles. The results show a great efficiency of the V2G-OLC algorithm compared to the traditional optimal charging strategies. Indeed, the results show a reduction of 47.94% of the average charging cost with a unitary selling/buying price ratio in comparison to the simple charging at 230V-32A.
Ke Zhang, Yuming Mao, Supeng Leng, Yejun He · 8 authors
Due to their environment friendliness, electric vehicles (EVs) are anticipated to form a considerable fraction of vehicles for transportation in smart cities. It is essential to design an electricity charging scheme that takes the utilities of both the charging stations and the EVs into consideration. However, the self-interested nature of the EVs together with the information asymmetry between the energy demand and supply sides makes the design a significant challenge. In this paper, we propose a queuing network-based model to characterize the charging process of the multiple EVs in a renewable energy-aided charging station. Based on the model, we adopt a contract theoretic approach to design an optimal charging policy in an information asymmetry scenario. Furthermore, we propose the new contract-based charging rate assignment and admission control schemes that maximize the utility of the charging station under certain charging constraints. To derive the optimal contract, we present a two-step iterative algorithm and prove its convergence. We evaluate the proposed schemes based on the IEEE 69-bus distribution test system. Results indicate that the contract-based charging schemes can effectively benefit both the charging stations and the EVs and concurrently improve the load level of the smart grid.
Jelena Pajić, José Rivera, Kaiwen Zhang, Hans‐Arno Jacobsen
The recent success of electric vehicles leads to unprecedentedly high peaks of demand on the electric grid at the times when most people charge their cars. In order to avoid unreasonably rising costs due to inefficient utilization of the electricity infrastructure, we propose EVA: a scheduling system to solve the valley filling problem by distributing the electricity demand generated by electric vehicles in a geographically limited area efficiently over time spans in which the electric grid is underutilized. EVA is based on a smart contract running on the Ethereum blockchain in combination with off-chain computational nodes performing the schedule calculation using the Alternating Direction Method of Multipliers (ADMM). This allows for a high degree of transparency and verifiability in the scheduling computation results while maintaining a reasonable level of efficiency. In order to interact with the scheduling system, we developed a decentralized app with a graphical frontend, where the user can enter vehicle information and future energy requirements as well as review upcoming schedules. The calculation of the schedule is performed on a daily basis, continuously providing schedules for participating users for the following day.
Jan 1, 2018·Proceedings of the ... Annual Hawaii International Conference on System Sciences/Proceedings of the Annual Hawaii International Conference on System Sciences
Hua Song, Ence Zhou, Bingfeng Pi, Jun Sun · 6 authors
Battery swapping is a solution of electric vehicle (EV) battery refueling. For EV owners, the battery information and transaction’s correctness, openness, traceability and immutability is difficult to get guarantee in traditional centralized system. The trust lacking between EV owners and swapping station is caused, and becomes a big challenge to EV’s rapid development. An objective mechanism based on decentralized blockchain system is proposed to manage battery swapping and solve the trust lacking issue. With this solution, both battery’s life-cycle information and all operations histories are permanently saved in blockchain network. All key logics are driven by smart contracts, the battery price calculation and the digital currency exchange between EV owners and station are realized by smart contracts automatically and accurately. A primary prototype based on Ethereum is analyzed and implemented to illustrate the feasibility of managing battery swapping and refueling based on blockchain system to solve the trust lacking issue.
Chao Liu, Kok Keong Chai, Xiaoshuai Zhang, Eng Tseng Lau · 5 authors
The electric vehicle (EV) charging scheme can reduce the power generation costs and improve the smart grid resilience. However, the huge penetrations of EVs can impact the voltage stability and operating costs. In this paper, a novel EV participation charging scheme is proposed for a decentralized blockchain-enabled smart grid system. Our objectives are to minimize the power fluctuation level in the grid network and the overall charging cost for EV users. We first formulate the power fluctuation level problem of the smart grid system that take into accounts of EV battery capacities, charging rates, and EV users charging behavior. And then, we propose a novel adaptive blockchain-based electric vehicle participation (AdBEV) scheme that uses the Iceberg order execution algorithm to obtain an improved EV charging and discharging schedule. The simulation results show the proposed scheme outperforms the scheme that applying genetic algorithm approach in term of lowering the power fluctuation level and overall charging costs.
Green transportation such as electric vehicles are emerging as an alternative to the traditional vehicles primarily due to the increasing cost and need of petroleum energy worldwide. These electric vehicle operate by using electric charging and the way to charge an electric car is to use a mobile charger or use a charging infrastructure. Therefore, when a mobile charger is used, a billing system is required through which a user is billed who has charged the electric vehicle. In this paper, we propose a mobile charger billing system that utilizes Blockchain technology. This technology has been applied to achieve more secure online transactions in a peer-to-peer manner. Moreover, we analyze the requirements of mobile charger for billing and propose a lightweight scheme that can overcome the challenge of data size in existing Blockchain.
The penetration level of the renewable energy resources (RER), such as wind power turbines and solar photovoltaic generation, in interconnected power systems has been increased in many countries. A high penetration level of RERs causes some problems to the grid operator, e.g., lack in primary reserve. Due to environmental concern and energy security risk, many countries around the world decided to increase their electric vehicles (EV) in the near future which provides a good chance to use them as a mobile battery energy storage system (BESS). This paper proposes a new scheme to provide necessary primary reserve from electric vehicles by using hierarchical control of each individual vehicle. An EV aggregator based on the vehicle's information such as the required state of charge (SOC) for the next trip, departure time, and initial SOC is proposed. The proposed aggregation scheme determines the primary reserve and contracts it with system operator based on electricity market negotiation. The effectiveness of the proposed scheme is shown by the several simulation studies in the Taiwan power (Tai-power) system to enhance frequency nadir and steady state frequency after a large disturbance.
Albert Y. S. Lam, Ka-Cheong Leung, Victor O. K. Li
Due to various green initiatives, renewable energy will be massively incorporated into the future smart grid. However, the intermittency of the renewables may result in power imbalance, thus adversely affecting the stability of a power system. Frequency regulation may be used to maintain the power balance at all times. As electric vehicles (EVs) become popular, they may be connected to the grid to form a vehicle-to-grid (V2G) system. An aggregation of EVs can be coordinated to provide frequency regulation services. However, V2G is a dynamic system where the participating EVs come and go independently. Thus, it is not easy to estimate the regulation capacities for V2G. In a preliminary study, we modeled an aggregation of EVs with a queueing network, whose structure allows us to estimate the capacities for regulation-up and regulation-down separately. The estimated capacities from the V2G system can be used for establishing a regulation contract between an aggregator and the grid operator, and facilitating a new business model for V2G. In this paper, we extend our previous development by designing a smart charging mechanism that can adapt to given characteristics of the EVs and make the performance of the actual system follow the analytical model.
Samira Rahnama, Jan Dimon Bendtsen, Jakob Stoustrup, Henrik Rasmussen
Exploitation of flexible consumption in the future smart grid requires new actors and infrastructure. In this paper, we propose a hierarchical setup in which a central controller, a so-called “aggregator,” is responsible for managing the flexibilities of industrial thermal loads via a contract-based direct control policy. The aggregator manipulates the consumption profile in an optimal and robust manner in order to provide upward and downward regulating power services. To this end, we consider a robust model predictive control design at the aggregator. The performance of the proposed controller is evaluated by simulating specific case studies involving a supermarket refrigeration system and a heating, ventilation, and air conditioning chiller in conjunction with an ice storage. In addition, we provide a comparison between heterogeneous and homogeneous aggregation of different thermal loads through simulation examples.
The important energy requirements for the desalination process impose especially in autonomous and decentralized plants supplied by Renewable Energy Sources (RES). In this paper, five alternative energy generation topologies of Reverse Osmosis desalination process are evaluated. The proposed topologies assessed in terms of economic, environmental, technological and societal indices are compared using multi-criteria analysis, namely the Analytic Hierarchy Process (AHP) and the Preference Ranking Organization Method for Enrichment of Evaluations (PROMETHEE). Ranking of topologies resulted in the selection of direct connection and hybrid configuration as optimum solutions. In case economic priorities prevail diesel generation should also be considered.