Optimal scheduling of reconfigurable interconnected microgrids is a precious and critical task for the residential consumers especially with the integration of renewable energy sources, dispatchable units and energy storage systems. In this regard, not only the optimal scheduling of the microgrids in a realistic and correlated environment is a necessity, but also the guarantied security and the prevention of cyber-attacks are mandatory tasks for the operators. This article first addresses these issues by developing a novel framework based on blockchain for secured data transaction from the individual microgrids’ components to the central control unit and then tries to find the optimal scheduling plan using stochastic programming based on point estimate method (PEM). Through such a hybrid PEM-blockchain based framework, the interconnected microgrids can supply the residential loads in a fully reliable, economic and secured structure. We also consider a social-economic framework to not only minimize the total operating cost of the microgrids, but also benefit the customers by enhancing the social factors through the optimal switching. Considering the complex and nonlinear nature of the problem, an effective corrected crow search (CCS) algorithm is deployed to find the most optimal operating point for the microgrids. The quality and capabilities of the proposed model are investigated using a practical residential interconnected microgrid. The results show that the optimal switching could reduce the total operation cost from $22,716 to $21,935 (3.56% reduction). Also, the average energy not supplied (AENS) has reduced from 1.4115 to 1.352 kWh/customer.yr (4.40% reduction), which are notable values. The results advocate the quality and functionality of the proposed framework.
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.
Today’s technologies, techniques, and systems leveraged for managing energy trading operations in electric vehicles fall short in providing operational transparency, immutability, fault tolerance, traceability, and trusted data provenance features. They are centralized and vulnerable to the single point of failure problem, and less trustworthy as they are prone to the data modifications and deletion by adversaries. In this paper, we present the potential advantages of blockchain technology to manage energy trading operations between electric vehicles as it can offer data traceability, immutability, transparency, audit, security, and confidentiality in a fully decentralized manner. We identify and discuss the essential requirements for the successful implementation of blockchain technology to secure energy trading operations among electric vehicles. We present a detailed discussion on the potential opportunities offered by blockchain technology to secure the energy trading operations of electric vehicles. We discuss several blockchain-based research projects and case studies to highlight the practicability of blockchain technology in electric vehicles energy trading. Finally, we identify and discuss open challenges in fulfilling the requirements of electric vehicles energy trading applications.
The objective of this study is to introduce a new use case under smart energy cyber-physical-social system (CPSS) that brings together the competence of distributed ledger technology (DLT) and essence of peer-to-peer local energy markets. This use case involves donation sharing under a DLT-based charity system to support financially-disadvantaged citizens in covering their residential energy requirements in an anonymous and effective manner, as a means to contend the notorious energy poverty problem. Essential architecture and processes for such a sharing concept are discussed by adopting a layer-based representation of the smart energy CPSS. Fundamental step-by-step interactions among its functional layers for realizing prospective social welfare benefits are illustrated. Based on this framework, two distinct donation sharing mechanisms that work under a DLT-empowered local market setting are proposed. Operation of these donation sharing mechanisms are illustrated on a local energy market with resorting to a sample daily energy profile and a series of hybrid scenarios. Effect of donation sharing on accounts of market participants and charity system are detailed.
We investigate the operational and coordinated strategies of a low carbon supply chain in the carbon limit and exchange market, where the capital-constrained manufacturer exhibits loss-reluctance behavior due to the uncertainty of market demand. In this paper, we calculate the greatest loan interest rate for the electronic business platform, the greatest ordering amount for the manufacturer in the decentralized system, and the greatest ordering amount for the entire supply chain in the centralized system. We design a transfer payment contract to coordinate the emission-dependent supply under the electronic business platform financing service by comparing the manufacturer's greatest ordering amount in different systems. We conclude from theoretical analyses that when the critical value of the manufacturer's self-owned capital exceeds a certain point, the greatest ordering amount of the loss-reluctance manufacturer under the electronic business platform financing service is greater than that of the well-funded manufacturer. Furthermore, when the manufacturer's self-owned capital changes within a certain range, the electronic business platform financing service can cause both an electronic business platform and a loss-reluctant manufacturer to achieve Pareto improvement, even though the electronic business platform financing service does not coordinate the supply chain, which is regulated by a carbon limit and an exchange mechanism. Furthermore, when a certain condition is met by the transfer payment contract, the lack of capital and the low carbon supply chain can achieve complete coordination.
Mazin Debe, Haya R. Hasan, Khaled Salah, Ibrar Yaqoob · 5 authors
The massive adoption of electric vehicles (EVs) has caused an increasing demand for electric energy to charge the vehicles. Efficiently managing energy trading between energy providers and energy consumers can lead to meet the high demand for charging EVs while reducing its cost compared to traditional power provided by the utility company. However, a large portion of the existing systems leveraged for trading energy between EVs are centralized and fall short in providing transparency, reliability, audit, security, and trustworthy features. In this paper, we propose blockchain-based energy trading using an auctioning and reputation scheme. We develop Ethereum smart contracts which enable owners of EVs to automatically request electricity to charge their vehicles in a reliable, cost-effective, secure, and trustworthy manner. The proposed approach ensures the lowest rate available by implementing a reverse auctioning scheme for fair competition between providers to provide the requested service at the lowest cost. The proposed solution enforces high quality of service through a reputation-based approach that quantifies the performance of the service providers and gives an advantage to more reputable providers. We present the implementation details of the deployed system on a test Ethereum blockchain platform. We perform system testing and evaluation to validate and assess the functionality and performance of the proposed solution. Furthermore, we present security and cost analyses to show the affordability, robustness, and practicality of the proposed approach.
Ecumenical carbon dioxide (CO2) emission emanates from car, bus, taxi, and motorcycle is around 45%. Electric vehicle could be the major contributor to abbreviate the pollution level in a transportation sector. According to the Forbes report the ecumenical passenger electric vehicle demand expected to reach 15% in 2025, and 23% in 2030. This research provides a blockchain predicated solution for a pre-owned electric vehicle market that could engender a trust, transparency, immutable records, and an efficient way to track the entire life cycle of a futuristic electric vehicle supply chain. At present most of the pre-owned electric conveyance purchase transpires through the third-party accommodations, websites, and mobile applications. This does not provide the authentic information on electric conveyance history, charging capabilities of the battery, history of the charging records, and performance of the driver (wear and tear affect battery life). Our solution implemented utilizing hybrid blockchain technology. Each stakeholder assigned with the Ethereum blockchain address to track the vehicle records as a distributed ledger. This design considered electric vehicle manufacturer, charging station, battery manufacturer, road convey ascendancy as major stakeholders. Astute contract designed with solidity programming. Truffle platform used to deploy keenly intellective contract in private blockchain that ascertain the privacy of electric conveyance owners and other stakeholders. Meta mask a mobile application utilized kovan network for tracking vehicle in a public blockchain. This application tested with 0.1 Ether for each transaction. Blockchain Electric Vehicle Cloud of Things (BEVCoT) concept proposed to integrate the IoT-Blockchain application in a cloud environment.
Atif Iqbal, Arun Sekar Rajasekaran, Gadilli Sai Nikhil, Azees Maria
In this work, a secure and decentralized Blockchain based energy trading model for electric vehicles (EVs) using Smart contract that achieves Peer-to-Peer (P2P) transactions between EVs in Vehicle to Grid networks is designed. The traditional energy trading model is a centralized structure based on trusted third parties, and there may an issue of single-point failure and leakage of privacy. In this way, a blockchain-based framework offers a secure, efficient and transparent trading model. Initially, the participating EVs and aggregator in the trading process should register at the trusted authority. Once the registration is successfully completed, both EVs and aggregator authenticate each other mutually in an anonymous manner. Moreover, only authorized EVs (charging and discharging EVs) participate in the contrary auction mechanism to exchange power/money based on their demand. Simulation conducted for the proposed scheme shows that our scheme has high speed (i.e., less computational time and execution time) which improves the market efficiency. In-addition, the transactions are non tamperable, when compared to the conventional scheme.
Naipeng Dong, Babu Pillai, Guangdong Bai, Mark Utting
Abstract Distributed ledger technology (DLT) emerged as a disruptive force towards decentralization and has expanded beyond its origins in cryptocurrencies like Bitcoin. At the heart of DLT is an infrastructure that replicates data across multiple network nodes, enabling new opportunities for data integrity, transparency, and trust in distributed business environments. In recent years, technological advances have improved the performance, energy efficiency, and functionality of DLT, expanding its application to various sectors such as finance, healthcare, trade and media, logistics, and the public sector. Despite these advances, adoption remained limited, with notable successes primarily in areas such as decentralized finance and non-fungible tokens. By placing DLT within the historical development of ledgers and distributed databases, this Fundamental provides a business-oriented foundation for structuring and assessing DLT-based solutions. It presents, a unified definition covering blockchain technologies, describes the key characteristics of DLT, and offers a structured analysis of its potential and challenges using a multi-dimensional interaction framework. Ultimately, it serves to carve out where and under which conditions DLT infrastructures add value for interorganizational relationships.
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.
Many countries in Europe are adopting a deregulated system where prosumers can subscribe with any energy supplier in an open market, independently of location. However, the mobility aspect of transactions in the existing system is not satisfactorily covered. For instance, if a person receives the service of charging an EV from a prosumer's local outlet, he cannot pay to the prosumer directly without the presence of an intermediary system. This has led to a situation where the EV owners need to have a large number of subscriptions for EV charging providers and visitors cannot pay for the electricity used there. This study evaluates this mobility gap and proposes a solution for charging transactions using blockchain technology. Furthermore, we implement a proof of concept using the Hyperledger consortium platform for the technical feasibility of the proposed approach and evaluate the performance metrics such as transaction latency and throughput.
Raziq Yaqub, Sadiq Ahmad, Hassan Ali, Azzam ul Asar
Due to the proliferation of extended travel range electric vehicles (EVs), these will travel through different networks that might be served by different utility companies. Therefore, we propose an architecture capable of offering a charging service to roaming vehicles. Furthermore, although the energy internet supports both the flow of energy and information, it does not support seamless EV roaming service, because it is based on a centralized architecture. The blockchain technology that is based on a decentralized system has the potential to support a secure billing platform for charging the EVs roaming through different electrical jurisdictions. Furthermore, the integration of artificial intelligence (AI) ensures that the participating players get a fair portion of the revenue. Thus, the objective of this paper is to develop an AI and blockchain integrated billing architecture that would offer a charging service to the “roaming” EVs and present a fair and unified billing solution.
Yingchun Feng, Jie Fan, Hao Chen, Qixin Wang · 6 authors
Abstract Transnational power trading can promote the development of global energy Internet, which can enable various countries and regions to optimize the allocation of resources on a larger scale. However, transnational electricity trading still faces many challenges. First, the issues of trust, member management, and huge transaction volume hinder the development of transnational power trading. Second, the issues of considering the differences among countries and establishing a reasonable and efficient transnational power market trading mechanism are also particularly important. The emergence of a consortium‐blockchain technology provides a new idea of solving these problems. The distributed‐ledger technology and member‐management services of a consortium blockchain can solve the problems of trust in the transnational power transaction and access the review of market subjects. Simultaneously, the chain‐code technology can be used to improve the efficiency of transactions. Therefore, according to the actual needs of transnational power transactions, the applicability of the consortium‐blockchain technology was analysed. Then, a mathematical model of transnational power transactions that considered the transaction costs was designed, and simulation tests were conducted on Hyperledger Fabric. The calculation example shows that the proposed transaction model plays a positive role and significance in promoting transnational power transactions and stabilizing the market.
Abstract To reduce emissions in the maritime transport sector, the International Maritime Organisation (IMO) follows a global clean shipping strategy. Among the different directives of IMO, currently especially the sulphur emission regulations pose challenges for the shipping industry. Related to this are the established Sulphur Emission Control Areas (SECAs) and the introduced global sulphur cap. To comply with the sulphur restrictions, according to the present technological state of the art, ship-owners have three options for their existing fleet: the installation of emission abatement technologies, the switch to low sulphur fuels, or retrofitting for the usage of alternative fuels. Regardless which option is favoured, most often selected solutions still depend on fossil fuels. The reasons for this can be traced back to the fact that supply of biofuels is not ensured in ports and generally seen as no profitable solution. This paper develops and examines an innovative business model with a special focus on liquefied biogas (LBG). The study bases on collected qualitative and quantitative data, which was used by applying the Business Model Canvas. The results will highlight that the business model bears the potential to promote LBG supply. Next to this, the research will show that blockchain and smart contracts are able to foster the implementation of the business model and optimisation of value chain operations. Lastly, economic advantages were highlighted within a case study that refers to the seaport Karlskrona in Sweden and the RoPax ferries from Stena Line that travel back and forth to Gdynia seaport in Poland.
Jianxiong Guo, Xingjian Ding, Weili Wu, Ding‐Zhu Du
Electric Vehicles (EVs) are becoming more and more popular in our daily life, which replaces traditional fuel vehicles to reduce carbon emissions and protect the environment. EVs need to be charged, but the number of charging piles in a Charging Station (CS) is limited and charging is usually more time-consuming than fueling. According to this scenario, we propose a secure and efficient charging scheduling system based on a Directed Acyclic Graph (DAG)-blockchain and double auction mechanism. In a smart area, it attempts to assign EVs to the available CSs in the light of their submitted charging requests and status information. First, we design a lightweight charging scheduling framework that integrates DAG-blockchain and modern cryptography technology to ensure security and scalability during performing scheduling and completing tradings. In this process, a constrained multi-item double auction problem is formulated because of the limited charging resources in a CS, which motivates EVs and CSs in this area to participate in the market based on their preferences and statuses. Due to this constraint, our problem is more complicated and harder to achieve truthfulness as well as system efficiency compared to the existing double auction model. To adapt to it, we propose two algorithms, namely Truthful Mechanism for Charging (TMC) and Efficient Mechanism for Charging (EMC), to determine an assignment between EVs and CSs and pricing strategies. Then, both theoretical analysis and numerical simulations show the correctness and effectiveness of our proposed algorithms.
This paper explores a future perspective to foster the provision of balancing services to the electricity grid by distributed assets. One recent test case, initiated by the Dutch Transmission System Operator (TSO), was to operate an Electric Vehicle (EV) fleet on the automatic Frequency Restoration Reserve (aFRR) market, which entails fast and automated reserves. To achieve that in a decentralised, automated and transparent manner, the role of blockchain technology for this specific application is explored. We propose a novel configuration that can serve as a basis for deploying distributed assets for aFRR markets using blockchain or any alternative Distributed Ledger Technology (DLT). Automation can be achieved via the deployment of smart contracts, which also results in transparency in the system. The blockchain configurations are designed for three phases in the aFRR market, namely: (i) Operational planning and scheduling by a balancing service provider (i.e., formulation and submission of aFRR bid), (ii) Real-time operations (i.e., activation and measurements), and (iii) Verification and settlement (i.e., imbalance correction and financial settlement). The paper concludes that the scalability of distributed assets that can participate in the system, combined with the large transaction times and energy consumption of some consensus mechanisms, could put limitations on the proposed architecture. Future research should address benchmarking studies of other alternatives (e.g., DLTs, such as the ones based on directed acyclic graphs, and non-DLT solutions) with the proposed blockchain solution.
Jacob G. Monroe, Paula Hansen, Matthew Sorell, Emily Zechman Berglund
The transfer of market power in electric generation from utilities to end-users spurred by the diffusion of distributed energy resources necessitates a new system of settlement in the electricity business that can better manage generation assets at the grid-edge. A new concept in facilitating distributed generation is peer-to-peer energy trading, where households exchange excess power with neighbors at a price they set themselves. However, little is known about the effects of peer-to-peer energy trading on the sociotechnical dynamics of electric power systems. Further, given the novelty of the concept, there are knowledge gaps regarding the impact of alternative electricity market structures and individual decision strategies on neighborhood exchanges and market outcomes. This study develops an empirical agent-based modeling (ABM) framework to simulate peer-to-peer electricity trades in a decentralized residential energy market. The framework is applied for a case study in Perth, Western Australia, where a blockchain-enabled energy trading platform was trialed among 18 households, which acted as prosumers or consumers. The ABM is applied for a set of alternative electricity market structures. Results assess the impact of solar generation forecasting approaches, battery energy storage, and ratio of prosumers to consumers on the dynamics of peer-to-peer energy trading systems. Designing an efficient, equitable, and sustainable future energy system hinges on the recognition of trade-offs on and across, social, technological, economic, and environmental levels. Results demonstrate that the ABM can be applied to manage emerging uncertainties by facilitating the testing and development of management strategies.
Uzma Amin, M. J. Hossain, Wayes Tushar, Khizir Mahmud
Emerging smart grid technologies and increased penetration of renewable energy sources (RESs) direct the power sector to focus on RESs as an alternative to meet both baseload and peak load demands in a cost-efficient way. A key issue in such schemes is the design and analysis of energy trading techniques involving complex interactions between an aggregator and multiple electricity suppliers (ESs) with RESs fulfilling a certain demand. This is challenging because ESs can be of various categories, such as small/medium/large scale, and they are self-interested and generally have different preferences toward trading based on their types and constraints. This article introduces a new contract theoretic framework to tackle this challenge by designing optimal contracts for ESs. To this end, a dynamic pricing scheme is developed such that the aggregator can utilize to incentivize the ESs to contribute to both baseload and peak load demands according to their categories. An algorithm is proposed that can be implemented in a distributed manner by trading partners to enable energy trading. It is shown that the trading strategy under a baseload scenario is feasible, and the aggregator only needs to consider the per unit generation cost of ESs to decide on its strategy. The trading strategy for a peak load scenario, however, is complex and requires consideration of different factors, such as variations in the wholesale price and its effect on the selling price of ESs, and the uncertainty of energy generation from RESs. Simulation results demonstrate the effectiveness of the proposed scheme for energy trading in the local electricity market.
Sub-Saharan Africa requires affordable, reliable, and sustainable electricity to boost its economic, social, and human development. The main challenge posed to the region's electricity sector is the large investment gap needed to finance new power projects. The employment of new and innovative financing options is required to bridge this investment gap. Independent power projects have become one of the fastest-growing sources of new finance in the region. However, their development is constrained by the limited availability of debt finance for project implementation. The limited capital and bureaucratic burden of traditional financial institutions coupled with the high risks in the region ensures that the debt finance required by independent power projects is raised only after an arduous voyage and at high interest rates. We address these challenges by proposing a novel decentralized finance instrument, a blockchain special purpose vehicle that streamlines the processes in the financial layer of a traditional special purpose vehicle -- finance mobilization, revenue collection, and revenue disbursal. Specifically, the proposed decentralized finance instrument facilitates the mobilization of finance for the special purpose vehicle from a location-independent crowd, revenue collection from the electricity offtaker in a risk-mitigated manner, and disbursal of eventual project revenues to investors.
Muhammad Umar Javed, Nadeem Javaid, Abdulaziz Aldegheishem, Nabil Alrajeh · 6 authors
In this work, Electric Vehicles (EVs) are charged using a new and improved charging mechanism called the Mobile-Vehicle-to-Vehicle (M2V) charging strategy. It is further compared with conventional Vehicle-to-Vehicle (V2V) and Grid-to-Vehicle (G2V) charging strategies. In the proposed work, the charging of vehicles is done in a Peer-to-Peer (P2P) manner; the vehicles are charged using Charging Stations (CSs) or Mobile Vehicles (MVs) in the absence of a central entity. CSs are fixed entities situated at certain locations and act as charge suppliers, whereas MVs act as prosumers, which have the capability of charging themselves and also other vehicles. In the proposed system, blockchain technology is used to tackle the issues related with existing systems, such as privacy, security, lack of trust, etc., and also to promote transparency, data immutability, and a tamper-proof nature. Moreover, to store the data related to traffic, roads, and weather conditions, a centralized entity, i.e., Transport System Information Unit (TSIU), is used. It helps in reducing the road congestion and avoids roadside accidents. In the TSIU, an Inter-Planetary File System (IPFS) is used to store the data in a secured manner after removing the data’s redundancy through data filtration. Furthermore, four different types of costs are calculated mathematically, which ultimately contribute towards calculating the total charging cost. The shortest distance between a vehicle and the charging entities is calculated using the Great-Circle Distance formula. Moving on, both the time taken to traverse this shortest distance and the time to charge the vehicles are calculated using real-time data of four EVs. Location privacy is also proposed in this work to provide privacy to vehicle users. The power flow and the related energy losses for the above-mentioned charging strategies are also discussed in this work. An incentive provisioning mechanism is also proposed on the basis of timely delivery of credible messages, which further promotes users’ participation. In the end, simulations are performed and results are obtained that prove the efficiency of the proposed work, as compared to conventional techniques, in minimizing the EVs’ charging cost, time, and distance.
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.