Andrei Ionita, René Chester Goduscheit, Hessellund Lauritsen, Per, Wolfgang Prinz · 6 authors
The wind energy sector is undergoing digitalization processes that span multi-tier supply chains of turbine components and wind farm maintenance, amongst others. In an industrial use case that includes Siemens Gamesa Renewable Energy, Vestas and APQP4Wind, the processes of producing, fastening, and servicing bolts in turbines are mapped to a digital model. The model follows the lifetime of turbine bolts from the manufacturing phase, to fastening in turbines and maintenance, until their replacement and recycling. The development of the digital model is iteratively addressed in a design science research approach, as the authors actively contribute to the project. Distributed ledgers (DLs) support the notary documentation of the bolts and turbines, from their registration phase to the assembly-, technical service verification- and recycling phases. The immutable and decentralized nature of DLs secures the data against tampering and prevents any changes taken unilaterally by engaging the service stakeholders and component providers in a blockchain consortium.
A smart electric vehicle (EV) charging station energy management system (CSMS) based on blockchain technology, which aims to protect privacy of EV users, ensure fairness of power transactions, and meet charging demands for large numbers of EVs, is proposed in this study. EV charging pile is designed as a local blockchain distributed ledger node, which operates synchronously with blockchain system and blockchain distributed ledger in cloud server. This paper integrates CSMS through smart contracts, providing EV users that ability to conduct power transactions and perform optimal charging and discharging control in real-time. The distributed ledger is in charge of recording all the EV charging and discharging data to maintain fairness of power transactions, protects data from being maliciously tampered, and enables the EV user to monitor status of the EV participating in power transactions and dispatching. The intelligent CSMS consists of an artificial intelligence (AI) module, centralized optimal scheduling module, and decentralized optimal control module. The AI module is responsible for forecasting renewable energy generation and load consumption. There is a two-layer architecture consisting of centralized and decentralized optimal control modules; the upper layer performs optimal charging and discharging scheduling of the entire EV charging station at time 15-min time segments, the bottom layer performs distributed optimal scheduling control in each EV charging pile at 5 min time interval. Proposed system in this paper can deal with feeder congestion and real-time power supply and grid demand imbalance, which are caused by high numbers of EVs.
Leonardo Weber Stringini, Héricles Eduardo Oliveira Farias, Camilo Alberto Sepúlveda Rangel, Luciane Neves Canha · 6 authors
This paper presents a methodology for optimal energy management of battery energy storage systems for aggregators use in distribution systems considering photovoltaic generation, demand contracts, and lifetime degradation. The methodology sets the optimum operation of the battery, define a trade-off between profit/lifetime of the battery dispatch and reduce the aggregator tariff bill. The dispatch optimization is carried out on a 48h forecasting model, where the best strategy is the one that guarantees a good operation for the day n+1 and day n+2. A nonlinear optimization approach sets battery dispatch, under operational constraints given by the Distribution System Operator contract and the battery state of charge constraint. Three types of battery chemistry are used, the lead acid, lithium ion and vanadium redox. Also, for each battery type the best methodology strategy is defined. Regarding the methodology, a neural network is used for forecasting of demand values, PV generation and tariff prices. Battery degradation cost is controlled in daily operation based on cycles and cost. Moreover, for total lifetime estimation, the Rainflow Counting technique is used through the depth of discharge. The results define an operation for the battery that allows economic profit, without compromising the lifetime.
The grid connected photovoltaic (PV) power plants (PVPPs) are booming nowadays. The main problem facing the PV power plants deployment is the intermittency which leads to instability of the grid. In order to stabilize the grid, either energy storage device - mainly batteries - or a power curtailment technique can be used. The additional cost on utilizing batteries make it not preferred solution, because it leads to a drop in the return on investment (ROI) of the project. A good alternative, is using a customized load (such as; cryptocurrency-based loads) which consumes the surplus energy. This paper investigating the usage of a customized load - cryptocurrency mining rig - to create an added value for the owner of the plant and increase the ROI of the project. These devices are widely used to perform the required calculations for validating the transactions on the network of the Blockchain. A comparison between the ROI of the mining rig and the battery have been conducted in this study. Based on this study the mining rig has superior ROI of 7.7% - in the case with the lowest ROI - compared to 4.5% for battery. Moreover, an improved controlling strategy is developed to combine both the battery and mining rig in the same system. The developed strategy is able to keep the profitability as high as possible during the fluctuation of the mining network.
Ruochen Jin, Bo Wei, Yongmei Luo, Tao Ren · 5 authors
The number of electric vehicles in various countries has shown exponential growth so that the related industries to face the tremendous pressure of power batteries disposal. Efficient secondary use and recycling of power batteries require effective collection of battery data and reasonable estimation of battery state-of-health (SOH). In this paper, we propose a framework to collect battery charging data from different stakeholders with an anomaly detection method based on Isolation Forest with two features. Besides a score-based mechanism is adopted to do data screening and capture the data with good quality. Unlike prior works, our proposed method can exploit crowdsourced data to reduce the significant effort of battery data sensing and provide a data source scoring mechanism based on blockchain to improve the data quality and meet the requirement of reasonable estimation. In order to verify the effectiveness of the proposed collection method, a charge data test set is constructed based on the NASA battery data set. The simulation results indicate that the method increases the F-measure criteria up to 25.65% compared to the well-known anomaly detection algorithms. In addition, the proposed collection method outperforms the traditional method up to 10.9% in reducing the relative error when being used for SOH estimation.
Shashank Narayana Gowda, Basem A. Eraqi, Hamidreza Nazaripouya, Rajit Gadh
This paper proposes a blockchain-based method for assessment and tracking of electric vehicle battery degradation costs. Vehicle-to-Grid (V2G) technology allows the bidirectional flow of electric power between the electric vehicle (EV) and the electric grid. However, for making optimal charging/discharging decisions, it is essential to precisely evaluate the battery degradation. In the proposed method, the initial degradation cost is estimated based on the present status of the EV battery in terms of range and age. Following this, a degradation cost of the battery is obtained from battery specifications and continuously tracking the variables that affect battery energy capacity, which will determine the economic loss to EV users for participating in V2G programs. A Mixed Integer Linear Program to minimize cost includes this degradation cost in its objective function to make the optimal decision for an EV's interaction with the grid. At the end of each 24-hour cycle, the battery degradation cost is updated based on the charging/discharging transactions performed during the cycle and the temperature conditions. These transactions and battery degradation costs are stored in a consortium blockchain that is shared among the relevant actors.
Vehicle-to-grid (V2G) technology is used in the modern eco-friendly environment for demand response management. It helps in reducing the carbon footprints in the environment. However, security and privacy of the information exchange between different entities are significant concerns keeping in view of the information exchange via an open channel, i.e., Internet among different entities such as plug-in hybrid electric vehicles (PHEVs), charging stations (CSs), and controllers in V2G environment. With an exponential rise in Electric vehicles (EVs) usage across the globe, there is a requirement of developing a seamless charging infrastructure for charging and billing. Moreover, secure information flow needs to be maintained at different levels in such an environment. Hence, this paper proposes a blockchain-based demand response management for efficient energy trading between EVs and CSs. In this proposal, miner nodes and block verifiers are selected using their power consumption and processing power. These nodes are responsible for the authentication of various transactions in the proposal. We also proposed a game theory-based solution to support energy management and peak load control off-peak and peak conditions. The proposed scheme has been evaluated using various performance evaluation metrics where its performance is found superior in comparison to the existing solutions in the literature.
Increasing electric vehicle (EV) penetration in distribution networks necessitate EV charging coordination. This paper proposes a two-stage EV charging coordination mechanism that frees the distribution system operator (DSO) from extra burdens of EV charging coordination. The first stage ensures that the total charging demand meets facility constraints, and the second stage ensures fair charging welfare allocation while maximizing the total charging welfare via Nash-bargaining trading. A decentralized algorithm based on the alternating direction method of multipliers (ADMM) is proposed to protect individual privacy. The proposed mechanism is implemented on the blockchain to enable trustworthy EV charging coordination in case a third-party coordinator is absent. Simulation results demonstrate the effectiveness and efficiency of the proposed approach.
Yuris Mulya Saputra, Diep N. Nguyen, Dinh Thai Hoang, Thang X. Vu · 6 authors
In this paper, we propose a novel economic-efficiency framework for an electric vehicle (EV) network to maximize the profits (i.e., the amount of money that can be earned) for charging stations (CSs). To that end, we first introduce an energy demand prediction method for CSs leveraging federated learning approaches, in which each CS can train its own energy transactions locally and exchange its learned model with other CSs to improve the learning quality while protecting the CS's information privacy. Based on the predicted energy demands, each CS can reserve energy from the smart grid provider (SGP) in advance to optimize its profit. Nonetheless, due to the competition among the CSs as well as unknown information from the SGP, i.e., the willingness to transfer energy, we develop a multi-principal one-agent (MPOA) contract-based method to address these issues. In particular, we formulate the CSs’ profit maximization as a non-collaborative energy contract problem under the SGP's unknown information and common constraints as well as other CSs’ contracts. To solve this problem, we transform it into an equivalent low-complexity optimization problem and develop an iterative algorithm to find the optimal contracts for the CSs. Through simulation results using a real CS dataset, we demonstrate that our proposed framework can enhance energy demand prediction accuracy up to 24.63 percent compared with other machine learning algorithms. Furthermore, our proposed framework can outperform other economic models by 48 and 36 percent in terms of the CSs’ utilities and social welfare (i.e., the total profits of all participating entities) of the network, respectively.
Indrasena R. Aenugu, Gomanth Bere, Justin J. Ochoa, Taesic Kim · 6 authors
This paper proposes a blockchain-powered battery data management and analytics platform which fully utilizes blockchain technology for battery health monitoring in battery energy storage systems (e.g., electric vehicles) and accelerating battery cell development. The proposed platform consists of five distinct components: 1) blockchain clients using application SDK such as battery energy storage systems and a battery tester; 2) a multichannel blockchain network for enhanced data security, privacy, and management; 3) data preprocessing; 4) data analytics engine executing analytics tools and health monitoring algorithms; and 5) user-friendly service visualization. The proposed platform is implemented in an AWS cloud and tested using real-time battery data from a battery energy storage system (BESS) client and batch data from a battery cell tester client. The results show that each blockchain channels can independently manage and analyze data sources from two clients in a blockchain network. The proposed platform will enable a new level of data security and privacy preserved battery intelligence system used for both battery product development and lifetime battery health monitoring.
Gomanth Bere, Justin J. Ochoa, Taesic Kim, Indrasena R. Aenugu
Blockchain technology has many beneficial properties that can advance electric vehicles in cyber-physical environments, especially for security-related purposes for EV battery management systems (BMSs). This paper explores firmware security vulnerabilities of a current BMS through reverse engineering and how the blockchain technology can be applied toward a next-generation BMS by managing critical activities and tasks including BMS firmware security check, recovery, and patch generation. A breakthrough method for blockchain-based automated detection of the firmware vulnerabilities and a patch generation is implemented in Internet-of-Thing (IoT) security modules as nodes of a blockchain network and validated by experiments. The proposed methods transformative to other cyber-physical system applications.
Xi Chen, Tianyang Zhang, Wenxing Ye, Zhiwei Wang · 5 authors
The rising proportion of renewable energy (RE) penetration with high variability introduces immense pressure on the stability of power grids. At the same time, a rapid increase in electric vehicle (EV) penetration level leads to uncoordinated charging loads, which poses significant challenges to operators. By properly guiding and scheduling the charging behaviors, EV may no longer be a burden, but a valuable asset to mitigate the RE integration problem. In this brief, we first propose a prioritization ranking algorithm of EV drivers based on their driving and charging behaviors, and then we propose a blockchain-based EV incentive system to maximize the utilization of RE. The proposed system is secure, anonymous, and decentralized. By incorporating the utilities, EV drivers, EV charging service providers, and RE providers into the proposed incentive system, this brief provides a plan to guide the EV users to charge at the desired time frames with higher RE generation. The market mechanism of the incentive system is discussed. The effectiveness of the system is verified by simulation.
Electric Vehicles (EVs) have generated a lot of interest in recent years, due to the advances in battery life and low pollution. Similarly, the expansion of the Internet of Things (IoT) allowed more and more devices to be interconnected. One major problem EVs face today is the limited range of the battery and the limited number of charging or battery swapping stations. A solution is to not only build the necessary infrastructure, but also to be able to correctly estimate the remaining power using an efficient battery management system (BMS). For some EVs, battery swapping can also be an option, either at registered stations, or even directly from other EV drivers. Thus, a network of EV information is required, so that a successful battery charge or swap can be made available for drivers. In this paper two blockchain implementations for an EV BMS are presented, using blockchain as the network and data layer of the application. The first implementation uses Ethereum as the blockchain framework for developing smart contracts, while the second uses a directed acyclic graph (DAG), on top of the IOTA tangle. The two approaches are implemented and compared, demonstrating that both platforms can provide a viable solution for an efficient, semi-decentralized, data-driven BMS.
Electric Vehicles (EVs) have generated a lot of interest in recent years, due to the advances in battery life and low pollution. Similarly, the expansion of Internet of Things (IoT) allowed more devices to be interconnected. One major problem electric vehicles face today is the limited range of the battery and the limited number of charging or battery swapping stations. A solution is to not only build the necessary infrastructure, but also to be able to correctly estimate the remaining power, using an efficient battery management system (BMS). For some EVs, battery swapping can also be an option, either at registered stations, or even directly from other EV drivers. Thus, a network of EV information is required, so that a successful battery charge or swap can be made available for drivers. In this paper, a blockchain implementation for an EV BMS is presented, using the IOTA tangle as the network and data layer of the application.
Zahra Foroozandeh, Sérgio Ramos, João Soares, Fernando Lezama · 7 authors
Efficient alternatives in energy production and consumption are constantly being investigated and conducted by increasingly strict policies. Buildings have a significant influence on electricity consumption, and their management may contribute to the sustainability of the electricity sector. Additionally, with growing incentives in the distributed generation (DG) and electric vehicle (EV) industries, it is believed that smart buildings (SBs) can play a key role in sustainability goals. In this work, an energy management system is developed to reduce the power demands of a residential building, considering the flexibility of the contracted power of each apartment. In order to balance the demand and supply, the electrical power provided by the external grid is supplemented by microgrids such as battery energy storage systems (BESS), EVs, and photovoltaic (PV) generation panels. Here, a mixed binary linear programming formulation (MBLP) is proposed to optimize the scheduling of the EVs charge and discharge processes and also those of BESS, in which the binary decision variables represent the charging and discharging of EVs/BESS in each period. In order to show the efficiency of the model, a case study involving three scenarios and an economic analysis are considered. The results point to a 65% reduction in peak load consumption supplied by an external power grid and a 28.4% reduction in electricity consumption costs.
Taesic Kim, Justin J. Ochoa, Tasnimun Faika, H. Alan Mantooth · 7 authors
Lithium-ion (Li-ion) batteries are a key energy storage component in various electrical and electronic systems, such as mobile phones and electric vehicles. A properly designed battery management system (BMS) is crucial to guarantee the safety, reliability, and optimal performance of the battery, as well as to interconnect the battery systems with each other and external systems through communication channels. However, security threats of the Li-ion battery systems are often overlooked by BMS developers in the design phase. The cybersecurity of BMSs is an essential factor to consider as more battery systems require internet connectivity for functionality, such as intelligent monitoring, control, and maintenance. This article discusses the overall security vulnerabilities from potential cyber-attacks and defense strategies, as well as the adoption of current blockchain technology in BMSs, which will be used as a cybersecurity baseline reference to BMS developers. The implementation of blockchain technology is promising to protect BMSs from malicious cyber-physical attacks and ensure the secure utilization of battery systems for numerous applications in cyber-physical environments.
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.
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.
The emergence of blockchain technology brings opportunities for the transactional energy to minimize the time gap and cost in the trading process. This paper proposes a public power exchange service network for Electric Vehicles (EV) to charge and discharge from the power grid. An enhanced novel consensus mechanism Proof-of-Benefit (ePoB) is proposed to improve the protocol security and performance of the electricity exchange system. Furthermore, the benefit number generation algorithm for choosing the leader in the network guarantees the overall power grid network performance by minimizing the load variance. Through theoretical and experimental analysis, the public power exchange system with ePoB consensus protocol achieves higher scalability than Proof- of-Work (PoW) and Paxo-based or BFT-based consensus protocols. Also, it demonstrates that the consensus protocol is capable of withstanding the Sybil attack while achieving lower power load fluctuation level compared with the benchmark.
Tasnimun Faika, Taesic Kim, Justin J. Ochoa, Maleq Khan · 6 authors
Wireless battery management systems (WBMSs) are recently proposed to solve critical wiring-harness issues in conventional BMSs. It is expected that the emerging Internet of Things (IoT) and cloud/edge computing technologies are expected to advance the WBMSs by fully utilizing IoT wireless network, powerful computing and unlimited cloud support, resulting in providing significant value in cost reduction, extended scalability, and greater visibility in the lithium-ion battery energy storage systems. However, the WBMSs present a growing threat from cyber-attacks as the WBMSs are always connected on networks and a lack of cybersecurity perspective is still prevalent in BMS usage and design phase. This paper explores blockchain technology for ensuring the communication and data security of an loT-enabled WBMS from malicious cyber-attacks. The concept of the proposed blockchain-based IoT network for WBMSs is validated by experimental studies.
U. Asfia, V. Kamuni, A. Sheikh, Sushama Wagh · 5 authors
Research related to electric vehicles (EV) is mainly focused on the hardware such as battery charging method, and still there is a lack of software research such as billing system that needs to be developed realistically. The result of charge measured in the charging EV can be different from the charged amount claimed to be charged in the charging system (CS). However, due to the potential security and privacy issues caused by untrusted and opaque energy markets, it becomes a great challenge to optimally schedule the charging behaviors of EVs with distinct energy delivery preferences of the CSs. In this paper, a novel EV participation charging scheme is proposed for a decentralized blockchain using smart contracts. Firstly, a permissioned blockchain system is introduced to implement secure charging services for EVs with the execution of smart contracts. Furthermore, based on the smart contract designed each EVs individual needs from CS is satisfied while maximizing its utility.
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.