Blockchain technology in energy systems: A state‐of‐the‐art review

Choobineh, Moein; Arabnya, Ali; Sohrabi, Behrouz; Khodaei, Amin; Paaso, Aleksi

doi:10.1049/blc2.12020

Cited by 17 publications

(3 citation statements)

References 158 publications

(217 reference statements)

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“…This solution demonstrates its ability to reduce costs and validate forecasting models in realworld settings. A P2P Energy Management System (EMS) is presented, which uses energy forecasts 2 days in advance to minimize the net energy exchange with the utility and enables surplus energy sharing among users, resulting in improved energy independence and reduced operating costs (Al-Sorour et al, 2022;Choobineh et al, 2023) presents an overview of the development of blockchain, and its use in power systems, and explores barriers and emerging trends to widespread adoption in the power sector, emphasizing its potential for secure, decentralized energy trading platforms. The role of blockchain technology (BCT) in sustainable smart cities is examined, its applications in various fields are analyzed and trends, challenges, and future research directions are presented (Ullah et al, 2023;Lin et al, 2022) proposed a blockchain-based smart EV charging system to address congestion and demand imbalance, for privacy, fairness, and real-time control.…”

Section: Literature Reviewmentioning

confidence: 99%

DeepResTrade: a peer-to-peer LSTM-decision tree-based price prediction and blockchain-enhanced trading system for renewable energy decentralized markets

Safari,

Gharehbagh,

Nazari-Heris

et al. 2023

Front. Energy Res.

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Intelligent predictive models are fundamental in peer-to-peer (P2P) energy trading as they properly estimate supply and demand variations and optimize energy distribution, and the other featured values, for participants in decentralized energy marketplaces. Consequently, DeepResTrade is a research work that presents an advanced model for predicting prices in a given traditional energy market. This model includes numerous fundamental components, including the concept of P2P trading systems, long-term and short-term memory (LSTM) networks, decision trees (DT), and Blockchain. DeepResTrade utilized a dataset with 70,084 data points, which included maximum/minimum capacities, as well as renewable generation, and price utilized of the communities. The developed model obtains a significant predictive performance of 0.000636% Mean Absolute Percentage Error (MAPE) and 0.000975% Root Mean Square Percentage Error (RMSPE). DeepResTrade’s performance is demonstrated by its RMSE of 0.016079 and MAE of 0.009125, indicating its capacity to reduce the difference between anticipated and actual prices. The model performs admirably in describing actual price variations in, as shown by a considerable R2 score of 0.999998. Furthermore, F1/recall scores of [1, 1, 1] with a precision of 1, all imply its accuracy.

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Section: Literature Reviewmentioning

confidence: 99%

DeepResTrade: a peer-to-peer LSTM-decision tree-based price prediction and blockchain-enhanced trading system for renewable energy decentralized markets

Safari,

Gharehbagh,

Nazari-Heris

et al. 2023

Front. Energy Res.

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“…Choobineh [10] et al., outline the process of blockchain technology from the beginning to the latest development, and provide a thematic review of the latest application of the technology in the power system. Moreover, it addresses the obstacles to the large‐scale, full adoption of this technology in the power sector.…”

Section: Related Workmentioning

confidence: 99%

A blockchain database system for a rail transit equipment system

Jing²,

Lu³

et al. 2023

IET Blockchain

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As of today, blockchain technology is virtually absent from rail transit applications, however, it has promising potential. For cloud‐based systems or conventional systems, there is too much information at the centre, resulting in a high level of data processing. However, if the data processing capability can be provided at the edge station or at the edge equipment, it greatly reduces the operation and maintenance pressure, at the same time, if the edge device takes the form of a blockchain, it is possible to increase the safety protection capability. It is important to reduce operating and maintenance risks for metro equipment systems by installing fault diagnosis and health management capabilities. This paper presents a blockchain‐based platform for subway applications. The assistance includes design, construction, operation, and maintenance assistance, energy saving assistance, manpower reduction assistance, fire protection linkage assistance at transfer stations, federal learning analysis and artificial intelligence analysis, as well as specific implementation plans for implementing vent valve equipment as examples.

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“…The technology enables secure and efficient transactions for electric vehicle charging and billing, thereby facilitating the growth of the electric vehicle market [ 80 ]. Additionally, the technology promotes energy democratization and allows small-scale renewable energy producers direct access to the energy market [ 58 , [81] , [82] , [83] ]. This democratization enables these producers to sell excess energy, contributing to a more equitable and diversified energy landscape.…”

Section: Introductionmentioning

confidence: 99%