Blockchain Papers

Enis Karaarslan, Doğan Aydın

No abstract is available for this record.

Mehdi Mehdinejad, Heidarali Shayanfar, Behnam Mohammadi‐Ivatloo

This paper designs and models a fully decentralized peer-to-peer energy token market for small-scale prosumers using blockchain technology in a smart grid environment in the presence of the demand response program (DRP) and demurrage mechanism. As the market players, prosumers in the local distribution network are considered in two groups, producers (sellers) and consumers (buyers). Using smart contracts, all sellers and buyers in the proposed market can engage in bilateral energy token transactions with each other under an agreed price and with the retail market at a certain price. Furthermore, the local consumers can participate in price-based DR programs and shift their consuming load to the periods with high local generation. demurrage mechanism is applied to avoid energy token accumulation and enhance attraction for local transactions. With demurrage in place, the redemption value of energy-backed tokens reduces with time. A fully decentralized approach called the primal-dual sub-gradient method is developed to clear this fully decentralized energy market in the presence of DRPs and demurrage. The proposed market-clearing scheme guarantees the global and feasible solution without requiring the players’ private information. Numerical studies demonstrated the feasibility and effectiveness of the proposed energy token market and the decentralized approach for its clearing.

Naveed ur Rehman, Max Yap, Mujaddad Afzal, Abdul Rehman · 5 authors

This paper presents a model for assessing the financial viability of cryptocurrency mining setups powered by off-grid solar photovoltaic (PV) systems. The model considers the features of mining hardware, the network attributes, the price of virtual currency and the solar potential of the installation site, to predict the payback period of the investment in months. As a case study, the feasibility of mining using various state-of-the-art Application-Specific Integrated Circuits (ASICs) and Graphics Processing Units (GPUs), powered by PV installed in New Zealand has been investigated. The results show that for ASICs setups, the initial cost is very high compared to GPU setups. However, considering the best-performing cryptocurrencies, the payback period for ASICs is much shorter than for GPU setups. This work will help to improve the sustainability of cryptocurrency mining businesses by reducing their dependence on exhaustible energy resources and their impact on the environment.

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.

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.

Mohammad Ghiasi, Moslem Dehghani, Taher Niknam, Abdollah Kavousi‐Fard · 6 authors

Due to the simultaneous development of DC-microgrids (DC-MGs) and the use of intelligent control, monitoring and operation methods, as well as their structure, these networks can be threatened by various cyber-attacks. Overall, a typical smart DC-MG includes battery, supercapacitors and power electronic devices, fuel cell, solar Photovoltaic (PV) systems, and loads such as smart homes, plug-in hybrid electrical vehicle (PHEV), smart sensors and network communication like fiber cable or wireless to send and receive data. Given these issues, cyber-attack detection and securing data exchanged in smart DC-MGs like CPS has been considered by experts as a significant subject in recent years. In this study, in order to detect false data injection attacks (FDIAs) in a MG system, Hilbert-Huang transform methodology along with blockchain-based ledger technology is used for enhancing the security in the smart DC-MGs with analyzing the voltage and current signals in smart sensors and controllers by extracting the signal details. Results of simulation on the different cases are considered with the objective of verifying the efficacy of the proposed model. The results offer that the suggested model can provide a more precise and robust detection mechanism against FDIA and improve the security of data exchanging in a smart DC-MG.

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.

Weifeng Lu, Zhihao Ren, Jia Xu, Siguang Chen

Compared with traditional power systems, smart grid is designed to provide effective and secure energy services. Data aggregation is one of the key technologies in wireless sensor networks, which reduces the amount of data transmission between nodes by merging similar data and simplifying redundant data, thus significantly reducing the computation cost and communication overhead of the system. Many data aggregation schemes have been developed for the smart grid in the past years. However, most of the data aggregation schemes ignore the data security and privacy protection issues of the edge layer. To solve these problems, in this article, we propose an edge blockchain assisted lightweight privacy-preserving data aggregation for smart grid, named EBDA. In this work, we integrate edge computing and blockchain to design a three-layer architecture data aggregation scheme for smart grid. This new architecture supports a two-level data aggregation scheme, which is more efficient and secure. Through theoretical analysis and simulations, EBDA shows great superiority in terms of resisting network attacks, reducing system computation costs and communication overhead compared with existing schemes.

Yuxin Zhong, Mi Zhou, Jiangnan Li, Jiahui Chen · 7 authors

Authentication and authorization (A & A) mechanisms are critical to the security of Internet of Things (IoT) applications. Smart grid system processing and exchanging data without human intervention, known as smart grids, are well‐known as IoT scenarios. Entities in such smart grid systems need to identify and validate one another and ensure the integrity of data exchange mechanisms. However, at present, most commonly used A & A protocols are centralized, resulting in security risks such as information leaks, illegal access, and identity theft. In this study, we propose a new distributed A & A protocol for smart grid networks based on blockchain technology to address with these risks. The proposed protocol integrates the decentralized authentication and immutable ledger characteristics of blockchain architectures suitable for power systems with a novel blockchain technique to realize both identity authentication and resource authorization for smart grid systems. We discuss the security of and threat models for prior A & A protocols and demonstrate how our protocol protects against these threats. We further demonstrate an approach to a real deployment of our A & A protocol using the FISCO consortium platform, applying algorithms from smart contract systems. Finally, we present the results of experimental simulations showing the efficacy and efficiency of our proposed protocol.

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.

Anna Klimenko, E. V. Melnik

No abstract is available for this record.

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.

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.

Jovan Karamachoski, Ninoslav Marina, Pavel Taskov

Blockchain technology will bring a disruption in plenty of industries and businesses. Recently it proved the robustness, immutability, auditability, in many crucial practical applications. The blockchain structure offers traceability of actions, alterations, alerts, which is an important property of a system needed for development of sustainable technologies. A crucial part of the blockchain technology regarding the optimization of the processes is the smart contract. It is a self-executable computer code, open and transparent, encoding the terms of a regular contract. It is able to automate the processes, thus decreasing the human-factor mistakes or counterfeits. In this paper, we are presenting the feasibility of the blockchain technology in the certification processes, with an application developed for university diploma certification. The example is easily transferable in other areas and business models such as logistics, supply chain management, or other segments where certification is essential.

Alireza Parvizimosaed, Masoud Bashari, Ashkan Rahimi‐Kian, Daniel Amyot · 5 authors

Through transactive energy (TE) platforms, prosumers can enter into a contractual agreement with an Independent Electricity System Operator (IESO) to buy and sell energy. Accordingly, the TE contract holders are liable for contractual violations. Manual compliance checking of such transactions is infeasible due to large number of market rules as well as the plethora of executing TE contracts. Moreover, the TE system big data (e.g., offers, bids, and transaction activities) need to be maintained on a transparent, reliable, and secure plat-form. This paper presents a compliance checking method for transactive energy markets based on the IESO (in Ontario, Canada) market rules by using smart contracts that assure the integrity, reliability, and transparency of energy transactions’ data with a permissioned blockchain. The performance of the blockchain network is evaluated through transaction latency and resource utilization. In addition, an acceptance test is successfully conducted to validate the correctness of the platform in terms of trading workflow, runtime status of the TE contracts, and the quality of market clearing results.

Omaji Samuel, Nadeem Javaid, Adia Khalid, Muhammad Imrarn · 5 authors

In a multi-agent system (MAS), the trust of each agent has become hot research issues in the smart grids. The traditional trust systems that use access control and cryptography are not sufficient to handle the dynamic behavior of agents. Also, they are inefficient to solve the computational overhead of the cryptographic primitives. Based on these limitations, this paper proposes a blockchain-based trust management system for MAS. The proposed system consists of two layers: a lower layer that enables an agent to perform direct and indirect trust evaluations of other agents during interactions. Multi-source feedback from the interactions among different aggregators is feed to the blockchain. The upper layer is used to perform trust credibility of agents based on trust distortion, consistency and reliability. The credibility evaluation is used to determine the dynamic behavior of agents and also detect dishonest agents in the system. Trust model and security analysis of the proposed system are provided. Moreover, simulation results evaluate the effectiveness of the proposed trust system while the system is secure against bad-mouthing and on-off attacks.

Wenjun Fan, Younghee Park, Shubham Kumar, Priyatham Ganta · 6 authors

Collaborative intrusion detection system (CIDS) shares the critical detection-control information across the nodes for improved and coordinated defense. Software-defined network (SDN) introduces the controllers for the networking control, including for the networks spanning across multiple autonomous systems, and therefore provides a prime platform for CIDS application. Although previous research studies have focused on CIDS in SDN, the real-time secure exchange of the detection-relevant information (e.g., the detection signature) remains a critical challenge. In particular, the CIDS research still lacks robust trust management of the SDN controllers and the integrity protection of the collaborative defense information to resist against the insider attacks transmitting untruthful and malicious detection signatures to other participating controllers. In this paper, we propose a blockchain-enabled collaborative intrusion detection in SDN, taking advantage of the blockchain's security properties. Our scheme achieves three important security goals: to establish the trust of the participating controllers by using the permissioned blockchain to register the controller and manage digital certificates, to protect the integrity of the detection signatures against malicious detection signature injection, and to attest the delivery/update of the detection signature to other controllers. Our experiments in CloudLab based on a prototype built on Ethereum, Smart Contract, and IPFS demonstrates that our approach efficiently shares and distributes detection signatures in real-time through the trustworthy distributed platform.

Aparna Kumari, Mohil Maheshkumar Patel, Arpit Shukla, Sudeep Tanwar · 6 authors

The next-generation energy system, i.e., Smart Grid (SG), empowers the real-time transfer of information using advanced metering infrastructure (AMI) and smart meter (SM) between end-consumers and grid. It accelerates various services such as automatic meter reading, time-of-use (TOU) pricing, demand-response management, and many more. Though it has growing security and privacy concerns and the detection of malicious activity is a critical security task that sacrifices the overall Quality-of-Service (QoS) of SG and Quality-of-Experience (QoE) for customers. To address the aforementioned issues, we propose a data analytics Scheme ArMor for malicious activity detection on the blockchain (BC)-based SG system. The ArMor detects data integrity issues in real-time like false data injection attack and SM failure. Here, we proposed a unique ARIMA-based malicious activity detection model and classified the customer. Then, we proposed a Smart Contract (SC)-based incentive mechanism for utility providers handling the malicious activity at their end. It prevents the entry of malicious data into the SG system as transactional data once stored in BC, it is secured using SC. The obtained results are compared against parameters like prediction accuracy, latency, and data storage cost compared to the state-of-the-art approaches to designate the efficacy of the proposed scheme.

Shunrong Jiang, Xiaoyan Zhang, Jinpeng Li, Hao Yue · 5 authors

The large-scale integration of distributed energy resources has resulted in surgical changes in energy trading systems. Traditional centralized trading systems suffer from high management cost and low efficiency. The recent advance of blockchain technology has enabled the invention of distributed energy trading systems, which can overcome the limitations of centralized trading systems. However, the distributed energy trading systems also bring new security and privacy challenges. For instance, transactions on blockchain are publicly visible which can lead to privacy leakage of trading information. Moreover, user privacy can also be leaked during verification of the aggregated energy trading result. In this paper, we propose a privacy-preserving energy trading scheme based on blockchain to meet the security requirements for distributed energy trading. We adopt a stealth transmission approach based on blockchain to ensure data privacy and break the linkage between consumers and providers in the energy trading process. We also use the non-interactive zero-knowledge proof technology to achieve privacy-preserving and trustworthy trading result verification. Security analysis and evaluation results have demonstrated that the proposed scheme can effectively protect the data privacy for distributed energy trading systems.

Aparna Kumari, Sudeep Tanwar

The exponential growth in energy demand led to increased demand-response gaps and decreased service quality of modern ICT-based smart grid (SG) in industry 4.0. It necessitates an efficient Demand Response Management (DRM) system in order to tackle aforementioned challenges. However, several DRM solutions exist, but these solutions are not adequate in terms of peak loads reduction, consumer comfort, and data security issues. Motivated from above facts, in this paper, we propose a scheme ϵ-Sutra, which is a security-aware DRM scheme for the SG system based on blockchain technology and integrated with data analytics. Here, a DRM algorithm is proposed to reduce peak energy consumption along with an incentive mechanism to consumers. ϵ-Sutra is incorporated with Ethereum-based smart contract (ESC) to handle security issues and InterPlanetary File System (IPFS) for data storage cost issues. The efficacy of the ϵ-Sutra scheme is evaluated in contrast with existing solutions based on various evaluation metrics.

Magda Foti, Costas Mavromatis, Manolis Vavalis

No abstract is available for this record.

Aasim Ullah, S.M. Shahnewaz Siddiquee, Md Akbar Hossain, Sayan Kumar Ray

Data security of present-day power systems, such as the electricity market, has spurred global interest in both industry and academia. The electricity market can either be regulated (state-controlled entrance, policies, and pricing) or deregulated (open for competitors). While the security threats in a deregulated electricity market are commonly known and have been investigated for years, those in a regulated market still have scope for extensive research. Our current work focuses on exploring the data security of the regulated electricity market, and the regulated New Zealand Electricity Market (NZEM) has been considered for this research. Although the chances of cyberattacks on state-controlled regulated electricity market are relatively less, different layers of the current SCADA systems do pose some threats. In this context, we propose a decentralized Ethereum Blockchain-based end-to-end security prototype for a regulated electricity market such as the NZEM. This prototype aims to enhance data security between the different layers of the current SCADA systems. The detailed operation process and features of this prototype are presented in this work. The proposed prototype has prospects of offering improved data security solutions for the regulated electricity market.