A Survey on Energy Trading in the Smart Grid: Taxonomy, Research Challenges and Solutions

Aggarwal, Shubhani; Kumar, Neeraj; Tanwar, Sudeep; Alazab, Mamoun

doi:10.1109/access.2021.3104354

Cited by 49 publications

(11 citation statements)

References 165 publications

(183 reference statements)

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“…Up to now, a variety of literature surveys were carried out to examine these research outputs from various perspectives and application needs. For instance, some surveys attempted to overview blockchain application for P2P energy exchange [11], [12], [13], [14], [15]. Whereas the authors in [16], [17] focused on blockchain use cases within microgrids.…”

Section: B Related Surveys and Our Contributionsmentioning

confidence: 99%

A Taxonomy and Lessons Learned From Blockchain Adoption Within the Internet of Energy Paradigm

et al. 2022

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The concept of the internet of energy (IoE) emerged as an innovative paradigm to encompass all the complex and intertwined notions relevant to the transition of current smart grids towards more decarbonization, digitalization and decentralization. With a focus on the two last aspects, the amount of intelligent devices being connected in a scattered way to the existing power grid is ever-growing. Nevertheless, guaranteeing a cyber-secure and resilient control of these IoE components as well as a seamless and reliable delivery of electricity services, such as renewable energy exchange, electric vehicles charging, demand response, and so forth; might be the bottleneck of current power systems that are largely still functioning following a centralized approach. Thus, the future power grid would gradually incorporate a growing number of distributed-based control schemes to deal with this challenge. And many believe that blockchain could be a key-enabler in this transition, due to its consistent characteristics with multiple requirements of future power systems. In this paper, we provide an extensive state-of-the-art of blockchain-based additions to the IoE. Where, we first introduce various concepts related to blockchain and discuss the rationale behind its adoption in the context of IoE. Then, differently from the existing body of literature surveys, we do not only provide a taxonomy and evaluate a wide range of recent research outputs that integrated blockchain within modern power systems. But we also draw some valuable lessons learned for each studied category and discuss the intersection of blockchain with various emerging paradigms that have the potential of radically impacting the smart grid. In addition, we present some real-world industrial initiatives and ongoing projects built on top of blockchain, dedicated for offering diverse electricity services with a case study of a pilot project on energy trading in Amsterdam. Finally, we discuss the remaining challenges and worthwhile opportunities of deploying blockchain in this particular area, with a focus on the aspect of operational cyber-security.

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Section: B Related Surveys and Our Contributionsmentioning

confidence: 99%

A Taxonomy and Lessons Learned From Blockchain Adoption Within the Internet of Energy Paradigm

et al. 2022

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“…Blockchain’s inherent characteristics, such as decentralized platform, transparency, auditable, irrevocable digital ledger, etc., attract many organizations to adopt it [ 9 , 10 , 11 ]. The viable solution to future energy, which needs the system to be secure, efficient, decentralized with respect to energy records, digitized with respect to technologies, democratized with respect to more consumer participation, and decarbonized with respect to carbon free green energy resources, is integration of blockchain technology [ 12 , 13 , 14 ].…”

Section: Introductionmentioning

confidence: 99%

Performance Evaluation and Cyberattack Mitigation in a Blockchain-Enabled Peer-to-Peer Energy Trading Framework

Pradhan

Singh

Sudha

et al. 2023

Sensors

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With the electric power grid experiencing a rapid shift to the smart grid paradigm over a deregulated energy market, Internet of Things (IoT)-based solutions are gaining prominence, and innovative peer-to-peer (P2P) energy trading at a micro level is being deployed. Such advancement, however, leaves traditional security models vulnerable and paves the path for blockchain, a distributed ledger technology (DLT), with its decentralized, open, and transparency characteristics as a viable alternative. However, due to deregulation in energy trading markets, most of the prototype resilience regarding cybersecurity attack, performance and scalability of transaction broadcasting, and its direct impact on overall performances and attacks are required to be supported, which becomes a performance bottleneck with existing blockchain solutions such as Hyperledger, Ethereum, and so on. In this paper, we design a novel permissioned Corda framework for P2P energy trading peers that not only mitigates a new class of cyberattacks, i.e., delay trading (or discard), but also disseminates the transactions in a optimized propagation time, resulting in a fair transaction distribution. Sharing transactions in a permissioned R3 Corda blockchain framework is handled by the Advanced Message Queuing Protocol (AMQP) and transport layer security (TLS). The unique contribution of this paper lies in the use of an optimized CPU and JVM heap memory scenario analysis with P2P metric in addition to a far more realistic multihosted testbed for the performance analysis. The average latencies measured are 22 ms and 51 ms for sending and receiving messages. We compare the throughput by varying different types of flow such as energy request, request + pay, transfer, multiple notary, sender, receiver, and single notary. In the proposed framework, request is an energy asset that is based on payment state and contract in the P2P energy trading module, so in request flow, only one node with no notary appears on the vault of the node.Energy request + pay flow interaction deals with two nodes, such as producer and consumer, to deal with request and transfer of asset ownership with the help of a notary. Request + repeated pay flow request, on node A and repeatedly transfers a fraction of energy asset state to another node, B, through a notary.

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“…proposes a 27% energy saving by 2030. The considerable rise in energy consumption poses several problems to energy safekeeping and the environment [5]. Increased energy efficiency was seen as an essential approach to handling the issues and encouraged the expansion of intelligent energy networks (IENs).…”

Section: Introductionmentioning

confidence: 99%

Intelligent Energy Consumption For Smart Homes Using Fused Machine-Learning Technique

AlZaabi¹,

Shaalan²,

Ghazal³

et al. 2023

Computers, Materials &Amp; Continua

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Energy is essential to practically all exercises and is imperative for the development of personal satisfaction. So, valuable energy has been in great demand for many years, especially for using smart homes and structures, as individuals quickly improve their way of life depending on current innovations. However, there is a shortage of energy, as the energy required is higher than that produced. Many new plans are being designed to meet the consumer's energy requirements. In many regions, energy utilization in the housing area is 30%-40%. The growth of smart homes has raised the requirement for intelligence in applications such as asset management, energy-efficient automation, security, and healthcare monitoring to learn about residents' actions and forecast their future demands. To overcome the challenges of energy consumption optimization, in this study, we apply an energy management technique. Data fusion has recently attracted much energy efficiency in buildings, where numerous types of information are processed. The proposed research developed a data fusion model to predict energy consumption for accuracy and miss rate. The results of the proposed approach are compared with those of the previously published techniques and found that the prediction accuracy of the proposed method is 92%, which is higher than the previously published approaches.

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A Survey on Energy Trading in the Smart Grid: Taxonomy, Research Challenges and Solutions

Cited by 49 publications

References 165 publications

A Taxonomy and Lessons Learned From Blockchain Adoption Within the Internet of Energy Paradigm

A Taxonomy and Lessons Learned From Blockchain Adoption Within the Internet of Energy Paradigm

Performance Evaluation and Cyberattack Mitigation in a Blockchain-Enabled Peer-to-Peer Energy Trading Framework

Intelligent Energy Consumption For Smart Homes Using Fused Machine-Learning Technique

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