The International Energy Agency has projected that the total energy demand for electricity in sub-Saharan Africa (SSA) is expected to rise by an average of 4% per year up to 2040. It implies that ~620 million people are living without electricity in SSA. Going with the 2030 vision of the United Nations that electricity should be accessible to all, it is important that new technology and methods are provided. In comparison to other nations worldwide, smart grid (SG) is an emerging technology in SSA. SG is an information technology-enhanced power grid, which provides a two-way communication network between energy producers and customers. Also, it includes renewable energy, smart meters, and smart devices that help to manage energy demands and reduce energy generation costs. However, SG is facing inherent difficulties, such as energy theft, lack of trust, security, and privacy issues. Therefore, this paper proposes a blockchain-based decentralized energy system (BDES) to accelerate rural and urban electrification by improving service delivery while minimizing the cost of generation and addressing historical antipathy and cybersecurity risk within SSA. Additionally, energy insufficiency and fixed pricing schemes may raise concerns in SG, such as the imbalance of order. The paper also introduces a blockchain-based energy trading system, which includes price negotiation and incentive mechanisms to address the imbalance of order. Moreover, existing models for energy planning do not consider the effect of fill rate (FR) and service level (SL). A blockchain levelized cost of energy (BLCOE) is proposed as the least-cost solution that measures the impact of energy reliability on generation cost using FR and SL. Simulation results are presented to show the performance of the proposed model and the least-cost option varies with relative energy generation cost of centralized, decentralized and BDES infrastructure. Case studies of Burkina Faso, Cote d'Ivoire, Gambia, Liberia, Mali, and Senegal illustrate situations that are more suitable for BDES. For other SSA countries, BDES can cost-effectively service a large population and regions. Additionally, BLCOE reduces energy costs by approximately 95% for battery and 75% for the solar modules. The future BLCOE varies across SSA on an average of about 0.049 $/kWh as compared to 0.15 $/kWh of an existing system in the literature.
Md. Mainul Islam, Md. Shahjalal, Moh. Khalid Hasan, Yeong Min Jang
Electric vehicles (EVs) have been gaining remarkable popularity throughout the world over the past few decades as they produce lower emissions by the efficient utilization of renewable energy and pollute less than conventional vehicles. They have emerged as a promising solution of climate change and energy crisis issues. It is an urgent need to develop a secure and reliable energy transaction model for electric vehicles in vehicle-to-grid (V2G) network. In order to solve the problem of energy shortage during peak hours and keep the balance of electricity supply, in this paper, we propose a blockchain-based energy transaction model for EVs in V2G network, which enables peer-to-peer energy transactions between EVs and power grid without need of trusted third party.
The Vehicle-to-Grid (V2G) network is, where the battery-powered vehicles provide energy to the power grid, is highly emerging. A robust, scalable, and cost-optimal mechanism that can support the increasing number of transactions in a V2G network is required. Existing studies use traditional blockchain as to achieve this requirement. Blockchain-enabled V2G networks require a high computation power and are not suitable for micro-transactions due to the mining reward being higher than the transaction value itself. Moreover, the transaction throughput in the generic blockchain is too low to support the increasing number of frequent transactions in V2G networks. To address these challenges, in this paper, a lightweight blockchain-based protocol called Directed Acyclic Graph-based V2G network (DV2G) is proposed. Here blockchain refers to any Distributed Ledger Technology (DLT) and not just the bitcoin chain of blocks. A tangle data structure is used to record the transactions in the network in a secure and scalable manner. A game theory model is used to perform negotiation between the grid and vehicles at an optimized cost. The proposed model does not require the heavy computation associated to the addition of the transactions to the data structure and does not require any fees to post the transaction. The proposed model is shown to be highly scalable and supports the micro-transactions required in V2G networks.
To promote coordinated development of electric vehicles (EVs) and power grid under open power selling, a bidding mechanism using blockchain smart contract technology was proposed. By demand respone management (DRM) on and off the blockchain, based on different driving characteristics of EV subgroups, various charging–discharging demands and constraints were fully considered between EV user subgroups and agent. Purchase–sale transaction relationship and unit commitment plan were fully considered between the EV agent and power dispatching center under economic dispatching. Aiming at the lowest power purchase cost of EV users, the highest profit of EV agent and the lowest cost of power economic dispatching, smart contract models with optimal benefits were established among the three. The smart contract models were solved by combining the internal and external optimization relationship of particle swarm and genetic algorithms. The charging–discharging price was optimized by DRM to realize the reasonable allocation of charging–discharging resources of EVs. An example analysis shows that this bidding mechanism can achieve peak–cutting and valley–filling for power load. At the same time, it can effectively protect the benefits of EV users, agent, and power dispatching center. This result can provide a reference for the application of smart contract in bidding of EVs to the power grid.
Mark Stefan, Paul Zehetbauer, Stephan Cejka, Franz Zeilinger · 5 authors
Energy communities will be an essential element of the future energy system. Especially renewable energy communities are gaining high attention in many European countries and their implementation, characteristics and use cases are elaborated in many research and development activities all around the world. Within the Austrian research project Blockchain Grid, a blockchain-based renewable energy community is implemented and field-tested in Heimschuh, Styria. It supports different technical applications like self-consumption optimisation and peer-to-peer energy trading for customers and a novel approach for grid capacity management supporting distribution system operators. These use cases have been implemented and validated in simulative studies showing promising potential for total energy costs for energy community members.
With the gradually opening of energy markets and popularization of Electric Vehicles (EVs), EVs can transmit, dispatch and recharge energy in different markets and domains dynamically. However, in Vehicular Energy Network, EVs may randomly enter and leave a market, it imposes a difficult problem in that how to schedule and distribute energy effectively. Additionally, the location of EV owners usually includes sensitive information such as home addresses, company names, hospital traces, and so on, which may be collected by attackers and may result in the privacy leakage about EV owners. In this article, we propose a decentralized blockchain-enabled energy trading scheme that can trade cross over various domains efficiently, which enables reliable transactions between EVs and energy nodes within short processing delay. It can also preserve the privacy of EV owners, by adopting the k-anonymity method in constructing a united request to hide the location information and creating a clocking area based on undirected graphs. Even though the server is maliciously attacked, the attacker cannot distinguish among EV owners, which breaks the linkage between real locations and identities to preserve EV owners' privacy. Finally, we conduct a comprehensive experimental evaluation to evaluate the trading performance and location privacy protection performance. The simulation results show that our proposed architecture outperforms over most state-of-the-art schemes in terms of processing delay and location privacy awareness.
The adoption of blockchain in the public electrical vehicle charging market has yet to be realized to its full potential, despite existing proof-of-concept. A positive outlook for blockchain is suggested by contemporary research, as well as the need for empirical studies to fully identify blockchain’s barriers to adoption. Through qualitative methods, a focused literature review, and in-depth interviews with subject matter experts, this thesis investigated which barriers to blockchain adoption exist in the public electrical vehicle charging market. The results indicated that the main barrier to blockchain adoption was the structure of the public electrical vehicle charging market itself, since it is an immature market experiencing constant change. This was followed by: coordination, norms and cultures, business process, incumbent technological solutions, regulations and legislations, shared infrastructure, and distributed ledger technology. These barriers were not shown individually, but were affected by each other. It is concluded that blockchain technology is not needed by the market in its current state, as its key defining attributes of privacy, security and decentralization are not deemed worth the cost of its own implementation. This research contributes to, and updates, the knowledge of blockchain utilization for the public electrical vehicle charging market. The results can be used by private and public organizations and scholars as reference material with regards to blockchain adoption for public electrical vehicle charging.
Godwin C. Okwuibe, Zeguang Li, Thomas Brenner, Ole Langniß
The increase in development of electric vehicle(EV) will have a strong impact on the power distribution grid if adequate care is not taken on the high power demand required for charging EV. Consequently, there is need to create a platform to enable charging point operators to effectively manage the EV user’s charging requests and ensure that there charging needs are satisfied while not exceeding the distribution grid capacity. If this is not done, there is no doubt that in few a years, EV owners will be faced with the problems of unavailability of charging stations and congestion in grid sequel to simultaneous charging of many EV’s. This work proposes a smart EV charging infrastructure based on a blockchain platform. With the charging demand (kWh) and maximum duration of the charging event provided by the EV user, the EV load flexibility is determined and utilized through smart charging to achieve a stable grid. EV owners and charging stations are linked through the platform thereby reducing the actors in EV charging ecosystem from six to four. Flexibility (power and time) in charging of EV is traded within the blockchain platform. By this, additional investors will be attracted into the business of EV charging station and through flexible offers, EV loads are shifted from the peak load hours. Consequently, the simulations shows that the acceptance rate of EV users increased by more than 50% when our smart charging system was adopted compared to the normal charging scenario.
With the development and expansion of smart grid systems, vehicle-to-grid (V2G) has become a new type of energy interaction based on Internet of Electric Vehicles (IoEVs). By leveraging the charging/discharging capabilities of EVs, V2G can be implemented in smart grid to enable intelligent energy transactions and reduce the unbalance of supply and demand. However, the implementation of interaction between the existing V2G technology and IoEVs faces the problems of high-complexity energy transaction management, insufficient computing capability, poor scalability, and lack of incentive mechanisms. The three-tier bi-directional energy transaction management strategies based on game and contract theory have been proposed. Firstly, the optimal pricing and EV discharging strategy is obtained based on the non-cooperative Stackelberg game and the energy-price equilibrium. Secondly, in order to optimize the utility of EAG, the information asymmetry incentive mechanism based on contract theory is proposed. This mechanism can effectively stimulate EVs to contribute to V2G energy transaction and further improve social benefits considering the energy transmission loss and battery life cycle degradation. To reduce the communication as well as processing latency and improve the efficiency of energy transaction management, edge computing has been incorporated. Simulation results show that the performance of the proposed scheme significantly outperforms other existing schemes under various scenarios.
Eduardo Francisco, Luís Tiago Ferreira, Carlos Silva, Joaquim Braga
The electric vehicle (EV) market is evolving fast with an expected high penetration of EV in the coming years. These EVs are dependent on charging infrastructure and since most charging will happen at home this will bring challenges to the low-voltage distribution network. The main challenge addressed in this study is the available grid capacity and what could be done to prevent the massive request of residential buildings grid connection reinforcements, which represents significant costs to consumers, large waiting times, which are not compatible with the rising necessities for charging EV and a general oversizing of the distribution network, which will drive the already low utilisation factors even lower. The presented solution for this challenge is to introduce a flexible power grid connection, which takes advantage of smart charging technology and the applications of flexible power contracts to allow the charging of 5–7 times more EV in the common garages of residential buildings without any building grid connection reinforcement and for a fraction of the cost. The distribution system operator (DSO) will represent a key role in the implementation of this solution, not only regarding the technical aspects but also regarding the onboarding of the consumers.
A Virtual Power Plant (VPP) is a network of distributed power generating units, flexible power consumers, and storage systems. A VPP balances the load on the grid by allocating the power generated by different linked units during periods of peak load. Demand-side energy equipment, such as Electric Vehicles (EVs) and mobile robots, can also balance the energy supply-demand when effectively deployed. However, fluctuation of the power generated by the various power units makes the supply power balance a challenging goal. Moreover, the communication security between a VPP aggregator and end facilities is critical and has not been carefully investigated. This paper proposes an AI-enabled, blockchain-based electric vehicle integration system, named AEBIS for power management in a smart grid platform. The system is based on an artificial neural-network and federated learning approaches for EV charge prediction, in which the EV fleet is employed as a consumer and as a supplier of electrical energy within a VPP platform. The evaluation results show that the proposed approach achieved high power consumption forecast with R2score of 0.938 in the conventional training scenario. When applying a federated learning approach, the accuracy decreased by only 1.7%. Therefore, with the accurate prediction of power consumption, the proposed system produces reliable and timely service to supply extra electricity from the vehicular network, decreasing the power fluctuation level. Also, the employment of AI-chip ensures a cost-efficient performance. Moreover, introducing blockchain technology in the system further achieves a secure and transparent service at the expense of an acceptable memory and latency cost.
The increasing electric vehicle (EV) penetration in a distribution network triggers the need for EV charging coordination. This paper firstly proposes a hierarchical EV charging coordination model and an algorithm based on Lagrangian relaxation. A barrier to the implementation of the coordination algorithm is that there usually does not exist a reliable coordinator of charging stations. This paper shows that an unreliable coordinator may collude with some charging stations and behave dishonestly by disobeying the coordination algorithm. Thus, the collusion coalition can gain more profits while lowering the profits of others and the total social welfare. To provide reliable coordination of charging stations, a novel blockchain-based coordination platform via Ethereum is established, including a coordination structure and a smart contract. A mathematical analysis is given to show that the proposed platform can mitigate the collusion behaviors in the coordination. Simulation results show the consequence of collusion and how blockchain can prevent the collusion.
In 2008, bitcoin disrupted the transactional ecosystem with its value propositions. However, sustaining autonomous, deregulated systems in markets filled with laws and regulations has had its challenges. There are also open questions of scalability, resilience, availability, speed and finality of transactions. Sound technical components have emerged but we need to take this one step further and integrate the units to provide an accepted packaged solution. Using a game application as an entry point, we propose a simple, inclusive asset transfer system which will stimulate adoption and create traction in the distributed ledger universe.
Yuta Susowake, Hasan Masrur, Tetsuya Yabiku, Tomonobu Senjyu · 7 authors
In Japan, residents of apartments are generally contracted to receive low voltage electricity from electric utilities. In recent years, there has been an increasing number of high voltage batch power receiving contracts for condominiums. In this research, a high voltage batch receiving contractor introduces a demand–response in a low voltage power receiving contract, which maximizes the profit of a high voltage batch receiving contractor and minimizes the electricity charge of residents by utilizing battery storage, electric vehicles (EV), and heat pumps. A multi-objective optimization algorithm calculates a Pareto solution for the relationship between two objective trade-offs in the MATLAB ® environment.
The stability and economy of the electronic vehicle distribution network system is increasingly important as the number of electric vehicles in use continues to rise. An electric vehicle (EV) and Internet of things (IoT) charge scheduling method is proposed in this paper which uses smart contract in the distribution network (DN) with uncertain renewable energy output. Based on user charging demand and power grid load level, this paper explores peak load shifting, guiding EV charging options by electricity price to change the demand response of each node, thereby regulating the DN power quality. A smart contract is created between the user and the charging station to realize the electricity price renewal in the power flow calculation cycle. This enhances the rationality of electricity price formulation and reduces deviation between the forecast load and the actual load, ensuring the validity of the method to a certain extent. According to the achievement of the smart contracts signed with the charging station, users are given rewards or fines, which reduces the default rate of the user. This decentralized transaction process improves the security and completeness of the transaction. The feasibility of utilizing this method for the distributed power grid is verified through simulation on a 34-node test system.
This paper proposes a new mechanism for forward selling renewable electricity generation. In this transactive framework, a wind or solar farm may directly sell to consumers a claim on their future power output in the form of nonfungible blockchain tokens. Using the flexibility of smart contract code, which executes irrevocably on a blockchain, the realised generation levels will offset the token holders' electricity consumption in near real-time. To elucidate the flexibility offered by such smart contracts, two ways of structuring these power delivery instruments are considered: firstly, an exotic tranched system, where more senior tokens holders enjoy priority claims on power, as compared against a simpler pro-rata scheme, where the realised output of a generator is equally apportioned between token holders. A notional market simulation is provided to explore whether, for instance, consumers could exploit the flatter power delivery profiles of more senior tranches to better schedule their responsive demands.
Felipe Condon, Mohamed A. Ahmed, José Manuel Martínez, Young-Chon Kim
This paper proposes a blockchain-based energy trading platform for electric vehicles in smart campus parking lots. Smart parking lots are smart places capable of supporting both parking and charging services for electric vehicles. The electric vehicle owner may want to charge energy at a low price and sell it during peak hours at a higher price. The proposed system architecture consists of two layers: the physical infrastructure layer and the cyber infrastructure layer. The physical infrastructure layer represents all of the physical components located in the campus distribution power system, such as electric vehicles charging stations, transformers, and electric feeders, while the cyber infrastructure layer supports the operation of the physical infrastructure layer and enables selling/buying energy among participants. Blockchain technology is a promising candidate to facilitate auditability and traceability of energy transactions among participants. A real case of a parking lot with a realistic parking pattern in a university campus is considered. The system consists of a university control center and various parking lot local controllers (PLLCs). The PLLC broadcasts the electricity demand and the grid price, and each electric vehicle owner decides whether to charge/discharge based on their benefits. The proposed system is implemented on Hyperledger Fabric. Participants, assets, transactions, and smart contracts are defined and discussed. Two scenarios are considered. The first scenario represents energy trading between electric vehicles as sellers and the PLLC as a buyer, while the second scenario involves energy trading between electric vehicles as buyers and the PLLC as a seller. The proposed platform provides profits for participants, as well as enables balancing for the university load demand locally.
This paper introduces the concept of hierarchical and zonal scheduling and proposes an iterative two-layer model to optimize the charging and discharging trading of electric vehicles (EVs), so as to minimize the overall load variance of the distribution network under the constraints of power flow and vehicle travel demand. In order to solve the mixed-integer programming (MIP) problem that exists in this model, an improved heuristic algorithm, the adaptive inertia weight krill herd (KH) algorithm is proposed. In addition, we design a decentralized trading architecture and related electricity trading process based on the consortium blockchain to ensure the security and privacy of two-way electricity trading between EVs and the smart grid. The IEEE nodes based simulation experiment shows that our scheme can effectively smooth power load fluctuations, and the improved KH algorithm can effectively improve the efficiency of model solving. Security analysis qualitatively proves that our scheme can ensure the security and privacy-preserving of electricity trading. Finally, our scheme is implemented in the Hyperledger Fabric to evaluate the feasibility and effectiveness.
Sai Shibu N B, S. Balamurugan, D. Arjun, Nidhin Mahesh A
Electric vehicles (EV) are becoming more popular day by day and on the other side, the demand for power is growing tremendously. A consensus driven, distributed and decentralized ledger system called blockchain technology, could be employed to introduce bidirectional power trading between vehicle to building and vice versa. This paper discusses different use cases for EV enabled blockchain based energy trading in a smart community. This paper also envisions the use of electric vehicles as a mobile power bank and enables vehicle to building power trading in a blockchain energy community.
The growing demand for EVs will lead to an increase in charging systems, both to guarantee the capillarity of charging systems and to distribute the demand for energy, which will increase over time. Since it is possible to have an efficient bidirectional energy flow, in fact car batteries can be used like any other energy storage system in the grid, with the added benefit of portability. The bi-directional energy flow would allow electric vehicle owners to participate in trading in energy markets, recharge batteries when energy is available at a low cost and discharge if the smart grid rewards them for their excess energy. This type of negotiation and control sharing can allow the network to perform demand management in periods of high demand, (e.g. peak shaving) or provision of additional storage in case of excess generation from RES. Through smart charging systems, it will be possible to decide where, when and which EV to recharge, thus reducing the load. The grid can be structured differently, in networks that serve small communities, in order to better manage RES energy flows, EV recharges and smart appliances. With this paper we want to determine a model for the smart charging of EVs, through the adaptive EV charging flow chart, through which a software agent, with a specific logic, decides whether to load a machine, in which sequence or if it is better to sell energy to the retail market. The agent learns and adapts to the individual Prosumers of EV, learning the preferences and mobility habits of different users, a fundamental element of the decision- making process, so that the owners of electric vehicles (or charging systems) decide to be part of the system. Finally, the management through Blockchain, makes every transaction reliable and verifiable, with the possibility of reducing or eliminating intermediaries in energy trading, thus reducing the range of antiexity of electric vehicle drivers, will make it possible to develop a new generation concept distributed: Smart Grid Community.
Increasing penetration of electric vehicles (EVs) gives rise to the challenges in the secure operation of power systems. The EV charging loads should be distributed among charging stations in a fair and incentive-compatible manner while ensuring that power transmission and transformation facilities are not overloaded. This paper first proposes a charging right (or charging power ration) trading mechanism and model based on blockchain. Considering all kinds of random factors of charging station loads, we use Monte Carlo modeling to determine the charging demand of charging stations in the future. Based on the charging demand of charging stations, a charging station needs to submit the charging demand for a future period. The blockchain first distributes initial charging right in a just manner and ensures the security of facilities. Given that the charging urgency and elasticity differences vary by charging stations, all charging stations then proceed with double auction and peer-to-peer (P2P) transaction of charging right. Bids and offers are cleared via double auctions if bids are higher than offers. The remaining bids and offers are cleared via the P2P market. Then, this paper designs the charging right allocation and trading platform and smart contract based on the Ethernet blockchain to ensure the safety of the distribution network (DN) and the transparency and efficiency of charging right trading. Simulation results based on the Ethereum private blockchain show the fairness and efficiency of the proposed mechanism and the effectiveness of the method and the mechanism.