Blockchain Papers

Iliasse Abdennour, Mustapha Ouardouz, Abdes Samed Bernoussi

No abstract is available for this record.

Jian Ping, Zheng Yan, Sijie Chen

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.

Zeng Zeng, Meiya Dong, Weiwei Miao, Mingming Zhang · 5 authors

The smart grid is emerging as a future paradigm for power networks. While it has many successful applications, peer-to-peer trading in the local energy market (LEM) is still challenging due to the lack of security and trading mechanisms. In this paper, we design a data-driven, secure, and smart solution DS2to address this problem. We first propose a five-layer design of LEM based on blockchain. We then model peer-to-peer trading in LEM as a cost minimization problem and derive an efficient online solution leveraging matrix factorization and integer linear programming. DS2is implemented and evaluated on a private Ethereum blockchain. We show that DS2achieves a mean absolute percentage error (MAPE) of 12.8% compared with the offline optimal method through extensive simulations on the real-world dataset.

Ümit Cali, Ozan Çakır

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.

Daniël Reijsbergen, Zheng Yang, Aung Htein Maw, Tien Tuan Anh Dinh · 5 authors

Smart grids leverage data from smart meters to improve operations management and to achieve cost reductions. The fine-grained meter data also enable pricing schemes that simultaneously benefit electricity retailers and users. Our goal is to design a practical dynamic pricing protocol for smart grids in which the rate charged by a retailer depends on the total demand among its users. Realizing this goal is challenging because neither the retailer nor the users are trusted. The first challenge is to design a pricing scheme that incentivizes consumption behavior that leads to lower costs for both the users and the retailer. The second challenge is to prevent the retailer from tampering with the data, for example, by claiming that the total consumption is much higher than its real value. The third challenge is data privacy, that is, how to hide the meter data from adversarial users. To address these challenges, we propose a scheme in which peak rates are charged if either the total or the individual consumptions exceed some thresholds. We formally define a privacy-preserving transparent pricing scheme (PPTP) that allows honest users to detect tampering at the retailer while ensuring data privacy. We present two instantiations of PPTP, and prove their security. Both protocols use secure commitments and zero-knowledge proofs. We implement and evaluate the protocols on server and edge hardware, demonstrating that PPTP has practical performance at scale.

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.

Pablo Mendez Royo, Jesús Rodríguez-Molina, Juan Garbajosa, Pedro Castillejo

Hardware solutions based on blockchain used in peer-to-peer electricity trading operations have been on rise during the last years. It is expected that due to their usage, it will become easier for prosumers to participate in the power grid on more equal terms when compared to the traditional players that have been settled in this market for the last decades. However, devices used to fully integrate prosumers are scarce and often offer minimal functionalities to perform the task of becoming integrated in those markets. This manuscript puts forward a Constrained Hardware Device enhanced with several software elements related to blockchain and cloud infrastructures, which make possible for any electricity generator or storage system to perform major actions like executing smart contracts, requesting energy prices to a Transmission System Operator and replicating the interchanged data in a cloud computing environment in case there are blockchain node failures. In this way, Renewable Energy Sources can be integrated by means of inexpensive, reliable devices with all the required software components preinstalled, with prosumers being able to further intervene in energy markets.

Hien Thanh Doan, Jeongho Cho, Daehee Kim

In a smart grid, each residential unit with renewable energy sources can trade energy with others for profit. Buyers with insufficient energy meet their demand by buying the required energy from other houses with surplus energy. However, they will not be willing to engage in the trade if it is not beneficial. With the aim of improving participants' profits and reducing the impacts on the grid, we study a peer-to-peer (P2P) energy trading system among prosumers using a double auction-based game theoretic approach, where the buyer adjusts the amount of energy to buy according to varying electricity price in order to maximize benefit, the auctioneer controls the game, and the seller does not participate in the game but finally achieves the maximum social welfare. The proposed method not only benefits the participants but also hides their information, such as their bids and asks, for privacy. We further study individual rationality and incentive compatibility properties in the proposed method's auction process at the game's unique Stackelberg equilibrium. For practical applicability, we implement our proposed energy trading system using blockchain technology to show the feasibility of real-time P2P trading. Finally, simulation results under different scenarios demonstrate the effectiveness of the proposed method.

Tudor Cioara, Marcel Antal, Vlad Mihailescu, Claudia Antal · 6 authors

The deployment of small-scale renewable energy sources will transform the management of energy grids towards more decentralized solutions in which the prosumers will have a more active role. Regulatory and market barriers are driving the implementation of virtual aggregation models in which the small-scale prosumers work together on a larger scale to gain benefits that could not be obtained on an individual basis. In this paper, we propose to use public blockchain and self-enforcing smart contracts to construct Virtual Power Plants (VPPs) of prosumers to provide energy services. A model has been defined for capturing the prosumer level constraints in terms of available energy profiles and energy service requirements enabling their optimal aggregation in hierarchical structures. A lightweight decentralized solution for VPPs construction is implemented using smart contracts enabling its efficient running on the public blockchain. Smart contracts are encoding the model constraints and are defining functionalities for prosumers to initiate or join a VPP implementing the complete chain of Offer-Operate-Measure-Remunerate actions. The VPP will be managed on top of a distributed ledger technology offering decentralized functionality for tracking and validating the delivery of energy based on the blockchain transactions and for energy and financial settlement, the remuneration being done according to the amount of energy provided by individual prosumers. Experimental results show that the proposed solution runs successfully on the public blockchain with good execution time and can address Balancing Responsible Party requests for additional generation. The overhead in terms of gas consumption and transactional throughput stays within reasonable boundaries.

M. Caruso, Pierluigi Gallo, Mariano Giuseppe Ippolito, S. Nassuato · 8 authors

No abstract is available for this record.

Faisal Jamil, Naeem Iqbal, Imran Imran, Shabir Ahmad · 5 authors

It is expected that peer to peer energy trading will constitute a significant share of research in upcoming generation power systems due to the rising demand of energy in smart microgrids. However, the on-demand use of energy is considered a big challenge to achieve the optimal cost for households. This paper proposes a blockchain-based predictive energy trading platform to provide real-time support, day-ahead controlling, and generation scheduling of distributed energy resources. The proposed blockchain-based platform consists of two modules; blockchain-based energy trading and smart contract enabled predictive analytics modules. The blockchain module allows peers with real-time energy consumption monitoring, easy energy trading control, reward model, and unchangeable energy trading transaction logs. The smart contract enabled predictive analytics module aims to build a prediction model based on historical energy consumption data to predict short-term energy consumption. This paper uses real energy consumption data acquired from the Jeju province energy department, the Republic of Korea. This study aims to achieve optimal power flow and energy crowdsourcing, supporting energy trading among the consumer and prosumer. Energy trading is based on day-ahead, real-time control, and scheduling of distributed energy resources to meet the smart grid’s load demand. Moreover, we use data mining techniques to perform time-series analysis to extract and analyze underlying patterns from the historical energy consumption data. The time-series analysis supports energy management to devise better future decisions to plan and manage energy resources effectively. To evaluate the proposed predictive model’s performance, we have used several statistical measures, such as mean square error and root mean square error on various machine learning models, namely recurrent neural networks and alike. Moreover, we also evaluate the blockchain platform’s effectiveness through hyperledger calliper in terms of latency, throughput, and resource utilization. Based on the experimental results, the proposed model is effectively used for energy crowdsourcing between the prosumer and consumer to attain service quality.

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.

Anri MORCHILADZE

Nowadays, researchers are trying to improve and find new ways and methods to mitigate climate change and increase energy efficiency. Areas of study include smart grid, smart grid, distributed energy systems, accumulative and renewable energy sources. Renewable energy integration, system operation, transparent spending system and data integrity are the common challenges facing distribution network providers. The overall, holistic view of the technologies listed above about delivering and consuming any kind of energy has many aspects that need to be studied and optimized. Good compatibility with distribution systems is characterized by modern blockchain technology and multi-agent system. Blockchain has very good data protection, immutability and transparency properties in transactions. Its decentralized nature and automatic calculation system can bring great potential in terms of financing and calculation in the energy sector. In this thesis article a novel process to coordinate, allocate and settle energy transactions in a district multi-carrier energy system. The process operates in a decentralized way, fully on-chain. The design leaves producers the freedom to choose their preferred pricing strategy for profit maximization. The price-availability-based allocation system guarantees consumers the lowest possible cost.

Shivam Saxena, Hany E. Z. Farag, Aidan Brookson, Hjalmar Turesson · 5 authors

Residential energy trading systems (RETS) enable homeowners with distributed energy resources (DERs) to participate in virtualized energy markets that have the potential to reduce the peak demand of residential communities. Blockchains are key enablers of RETS, by virtue of providing a decentralized, self-governed network that mitigates concerns regarding privacy and transparency. However, more real-world case studies are needed to evaluate the techno-economic viability of blockchain-based RETS to improve their positive uptake. Thus, this article develops a permissioned blockchain-based RETS, which enables homeowners to select bidding strategies that consider the individual preferences of their DERs, and further evaluates the impact of the bidding strategies on reducing the peak demand of the community. The proposed system is implemented on the permissioned Hyperledger Fabric platform, where a decentralized ledger is used to store all energy bids, and a smart contract is used to execute a double auction mechanism and dispatch the homeowner DERs. The proposed system is validated by conducting simulations on a 8-home community using real-world data, and also by deploying the system to a Canadian microgrid, where the smart contract execution time is benchmarked. Simulation results demonstrate the efficacy of the proposed system by achieving a peak demand reduction of up to 48 kW (62%), which leads to an average savings of $1.02 M for the distribution system operator by avoiding transformer upgrades. Also, the simulation results show that the execution time of the proposed smart contract is 17.12 seconds across 12 nodes, which is sufficient for RETS.

Faizan Safdar Ali, Ouns Bouachir, Öznur Özkasap, Moayad Aloqaily

Industrial investments into distributed energy resource technologies are increasing and playing a pivotal role in the global transactive energy, as part of a wider drive to provide a clean and stable source of energy. The management of prosumers, which consume and as well as generate energy, with heterogeneous energy sources is critical for sustainable and efficient energy trading procedures. This article proposes a blockchain-assisted adaptive model, namely SynergyChain, for improving the scalability and decentralization of the prosumer grouping mechanism in the context of peer-to-peer energy trading. Smart contracts are used for storing the transaction information and for the creation of the prosumer groups. SynergyChain integrates a reinforcement learning module to further improve the overall system performance and profitability by creating a self-adaptive grouping technique. The proposed SynergyChain is developed using Python and Solidity and has been tested using Ethereum test nets. The comprehensive analysis using the hourly energy consumption dataset shows a 39.7% improvement in the performance and scalability of the system as compared to the centralized systems. The evaluation results confirm that SynergyChain can reduce the request completion time along with an 18.3% improvement in the overall profitability of the system as compared to its counterparts.

Moslem Dehghani, Mohammad Ghiasi, Taher Niknam, Abdollah Kavousi‐Fard · 7 authors

Using blockchain technology as one of the new methods to enhance the cyber and physical security of power systems has grown in importance over the past few years. Blockchain can also be used to improve social welfare and provide sustainable energy for consumers. In this article, the effect of distributed generation (DG) resources on the transmission power lines and consequently fixing its conjunction and reaching the optimal goals and policies of this issue to exploit these resources is investigated. In order to evaluate the system security level, a false data injection attack (FDIA) is launched on the information exchanged between independent system operation (ISO) and under-operating agents. The results are analyzed based on the cyber-attack, wherein the loss of network stability as well as economic losses to the operator would be the outcomes. It is demonstrated that cyber-attacks can cause the operation of distributed production resources to not be carried out correctly and the network conjunction will fall to a large extent; with the elimination of social welfare, the main goals and policies of an independent system operator as an upstream entity are not fulfilled. Besides, the contracts between independent system operators with distributed production resources are not properly closed. In order to stop malicious attacks, a secured policy architecture based on blockchain is developed to keep the security of the data exchanged between ISO and under-operating agents. The obtained results of the simulation confirm the effectiveness of using blockchain to enhance the social welfare for power system users. Besides, it is demonstrated that ISO can modify its polices and use the potential and benefits of distributed generation units to increase social welfare and reduce line density by concluding contracts in accordance with the production values given.

R. Rajaguru, Praveen Kumar S

Efficient energy distribution and utilization play a significant role in the energy grid, especially with renewable sources. The existing grid system has problems in resource utilization, data privacy, wireless communication, and dynamic demand handling. An energy grid is proposed based on IoT, blockchain, and machine learning techniques to solve the problems. The proposed energy grid architecture controls energy flow according to the demand, predicts expected load, analyzes consumer behavior, and enables the users in the grid trade energy in peer to peer manner. Energy flow in storage modules controlled with high voltage relays, and it automates the charging and discharging of respective battery pools in the grid. Energy consumption and battery status in the grid uploaded to the distributed file system. The data clustering model deployed in the server analyses those data and divides the consumers into three groups according to the consumer’s consumption behavior: high, moderate, and low consumption. The Time series analysis model deployed to forecast the load and predict peak hours. The codes deployed as a smart contract in an Ethereum blockchain platform. Machine learning algorithms are deployed for forecasting and clustering. In forecasting, the average error rate is 37% less than other generally used algorithms, and in the clustering algorithm, the accuracy increases as the dataset increases, which is 30% more than other cluster models. The controlled energy storage model in this grid provides up to 500–600 extra charge cycles for batteries than other traditional methods. The distributed IPFS storage provides data security, and smart contracts support grid operational security and data privacy. The data analyzation module of the grid helps effective resource utilization.

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.

Ma Abdelwahed, Tarek A. Boghdady, Ah Madian, Raafat Shalaby

Energy and clean energy are big concerns and interests. As the needs differ from area to another, different solutions appear. Energy cost, availability, reliability and trading rules are important keys in energy market. Energy sharing is a hot topic as a consumer being a part of the sustainable distributed system also making benefits such as Prosumer. Blockchain technology provides more secure, distributed and fast way to transact financial payments between clients. This paper provide a simulation case for energy sharing concept using smart contract as a tool to rule the sharing process on isolated network to obtain the optimum performance and efficiency of the service. Creating a base for more conditions and complex scenarios and linking the sharing process to financial transactions.

Mohamed Hamouda, Mohammed E. Nassar, M.M.A. Salama

Microgrid planning philosophies are changing from islanding in the case of abnormal conditions to independent sustainability for constant secure, reliable operation. Large independent operators foresee a shift from gigantic-grid bulk generation and transmission to distributed generation (DG) from smaller, interlinked grid clusters. Customers and the community will benefit, but system operators and utilities will face challenges. Introduced to enhance electricity exchange and the energy market structure in such grids, transactive energy networks favor customers and DG owners, establish a utility business model, and enable power system innovation. Planners are also increasingly interested in blockchains for secure transactions. Blockchain-based transactive energy markets promise flexibility, transparency, security, competition, and superlative low-cost reliability, offering ideal energy-trading solutions in isolated microgrids and distribution-level markets. This article presents the development and case-study validation of a comprehensive transactive energy market framework with linked blockchain and power system layers, a novel market structure based on an end-user marginal price, and an adapted blockchain that fits intrinsic power system requirements. A new slot-ahead electricity market model is established through integration with the modified blockchain. With blockchain operation, monetary funds are managed equitably so that wallet billing rates for customers, utilities, and DG owners match broadcast smart-meter data.

Sachinkumar Suthar, Naran M. Pindoriya

The blockchain technology and smart contracts have opened up several new horizons for the energy sector. One of them is the possibility of local energy trading in which prosumers can trade their excess energy at the desired price without intermediaries. This paper presents a blockchain and smart contract-based trading platform to realize such kind of local energy trading. The blockchain technology is used to record the power deliveries and transactions, while the smart contract is used to check necessary conditions before executing the energy transactions. An interactive web-based user interface is developed to access the decentralized energy trading platform that incorporates the secure financial and energy deviation settlement mechanisms. It aims to provide transparency, energy affordability, and energy self-sufficiency to the prosumers and consumers at the edge of the grid. It also seeks to increase the usage of distributed renewable energy-based generations and promotes long-term energy security.

Junjie Wu, Kuo Li, Qing‐Shan Jia

Multi-agent reinforcement learning (MARL) has attracted more and more attention in recent years. It is now widely applied in various fields, including cyber physical systems, smart grid, finance, social network, and among others. The current researches on MARL mainly focus single-time scale, in which the agents have the same decision epoch. While in real applications, it is common that the agents make decisions by different frequencies. In addition, different agents may have separate roles in the system. In this paper, we propose a more general MARL framework by introducing multi-time scale of decision epochs. We assume that agents share information with their neighbors, including state, action, and reward. The global observability of state and action, which is a common assumption, is not required. We propose a decentralized Q-learning algorithm and a modified MADDPG algorithm to solve the problem. The main contributions of this paper are as follows. First, we formulate the multi-time scale multi-agent reinforcement learning (MTMARL) problem. This provides a general framework for the related systems and problems. Second, we provide a networked decentralized multi-time scale multi-agent Q-learning algorithm to solve the problem and prove its convergence. Third, we test the algorithm numerically. The results show that the proposed algorithm performs better than the previous QD-learning and is only slightly worse than the centralized algorithm.

Tudor Cioara, Claudia Pop, Razvan Zanc, Ionuț Anghel · 6 authors

Decentralized management and coordination of energy systems are emerging trends facilitated by the uptake of the Internet of Things and Blockchain offering new opportunities for more secure, resilient, and efficient energy distribution. Even though the use of distributed ledger technology in the energy domain is promising, the development of decentralized smart grid management solutions is in the early stages. In this paper, we define a layered architecture of a blockchain-based smart grid management platform featuring energy data metering and tamper-proof registration, business enforcement via smart contracts, and Oracle-based integration of high computational services supporting the implementation of future grid management scenarios. Three such scenarios are discussed from the perspective of their implementation using the proposed blockchain platform and associated challenges: peer to peer energy trading, decentralized management, and aggregation of energy flexibility and operation of community oriented Virtual Power Plants.