Energy Trading System and Strategy Based on Blockchain and Deep Learning

2022 ◽  
pp. 525-533
Author(s):  
Weijun Zheng ◽  
Ding Chen ◽  
Jinghui Fang ◽  
Haiwei Zhang ◽  
Yifei Wei
Keyword(s):  
Deep Learning ◽  
Trading System ◽  
Energy Trading

scholarly journals Influence of Features on Accuracy of Anomaly Detection for an Energy Trading System

Sensors ◽  
2021 ◽  
Vol 21 (12) ◽  
pp. 4237
Author(s):  
Hoon Ko ◽  
Kwangcheol Rim ◽  
Isabel Praça
Keyword(s):  
Anomaly Detection ◽  
Real Time ◽  
Feature Detection ◽  
Trading System ◽  
Judgment Accuracy ◽  
Energy Trading ◽  
Real Time Processing ◽  
Detection Model ◽  
Time Required ◽  
The Relationship

The biggest problem with conventional anomaly signal detection using features was that it was difficult to use it in real time and it requires processing of network signals. Furthermore, analyzing network signals in real-time required vast amounts of processing for each signal, as each protocol contained various pieces of information. This paper suggests anomaly detection by analyzing the relationship among each feature to the anomaly detection model. The model analyzes the anomaly of network signals based on anomaly feature detection. The selected feature for anomaly detection does not require constant network signal updates and real-time processing of these signals. When the selected features are found in the received signal, the signal is registered as a potential anomaly signal and is then steadily monitored until it is determined as either an anomaly or normal signal. In terms of the results, it determined the anomaly with 99.7% (0.997) accuracy in f(4)(S0) and in case f(4)(REJ) received 11,233 signals with a normal or 171anomaly judgment accuracy of 98.7% (0.987).

Consortium Blockchain-based V2G Energy Trading System Using Tokens

2020 ◽  
Author(s):  
Junho Hong ◽  
Eunhwa Oh ◽  
Yeojin Yang ◽  
Kyungwoo Roh ◽  
Minji Oh ◽  
...  
Keyword(s):  
Trading System ◽  
Energy Trading

scholarly journals Demonstration of Blockchain Based Peer to Peer Energy Trading System with Real-Life Used PHEV and HEMS Charge Control

Energies ◽  
2021 ◽  
Vol 14 (22) ◽  
pp. 7484
Author(s):  
Yuki Matsuda ◽  
Yuto Yamazaki ◽  
Hiromu Oki ◽  
Yasuhiro Takeda ◽  
Daishi Sagawa ◽  
...  
Keyword(s):  
Supply And Demand ◽  
Real Life ◽  
Energy System ◽  
Energy Markets ◽  
Peer To Peer ◽  
Renewable Energy Resources ◽  
Trading System ◽  
Energy Trading ◽  
Demonstration Experiment ◽  
Home Energy Management

To further implement decentralized renewable energy resources, blockchain based peer-to-peer (P2P) energy trading is gaining attention and its architecture has been proposed with virtual demonstrations. In this paper, to further socially implement this concept, a blockchain based peer to peer energy trading system which could coordinate with energy control hardware was constructed, and a demonstration experiment was conducted. Previous work focused on virtually matching energy supply and demand via blockchain P2P energy markets, and our work pushes this forward by demonstrating the possibility of actual energy flow control. In this demonstration, Plug-in Hybrid Electrical Vehicles(PHEVs) and Home Energy Management Systems(HEMS) actually used in daily life were controlled in coordination with the blockchain system. In construction, the need of a multi-tagged continuous market was found and proposed. In the demonstration experiment, the proposed blockchain market and hardware control interface was proven capable of securing and stably transmitting energy within the P2P energy system. Also, by the implementation of multi-tagged energy markets, the number of transactions required to secure the required amount of electricity was reduced.

scholarly journals When Energy Trading Meets Blockchain in Electrical Power System: The State of the Art

2019 ◽  
Vol 9 (8) ◽  
pp. 1561 ◽  
Author(s):  
Naiyu Wang ◽  
Xiao Zhou ◽  
Xin Lu ◽  
Zhitao Guan ◽  
Longfei Wu ◽  
...  
Keyword(s):  
Power System ◽  
Electrical Power ◽  
System Optimization ◽  
Assessment Model ◽  
Security And Privacy ◽  
Renewable Energy Resources ◽  
Electrical Power System ◽  
Trading System ◽  
Energy Trading ◽  
Low Efficiency

With the rapid growth of renewable energy resources, energy trading has been shifting from the centralized manner to distributed manner. Blockchain, as a distributed public ledger technology, has been widely adopted in the design of new energy trading schemes. However, there are many challenging issues in blockchain-based energy trading, e.g., low efficiency, high transaction cost, and security and privacy issues. To tackle these challenges, many solutions have been proposed. In this survey, the blockchain-based energy trading in the electrical power system is thoroughly investigated. Firstly, the challenges in blockchain-based energy trading are identified and summarized. Then, the existing energy trading schemes are studied and classified into three categories based on their main focuses: energy transaction, consensus mechanism, and system optimization. Blockchain-based energy trading has been a popular research topic, new blockchain architectures, models and products are continually emerging to overcome the limitations of existing solutions, forming a virtuous circle. The internal combination of different blockchain types and the combination of blockchain with other technologies improve the blockchain-based energy trading system to better satisfy the practical requirements of modern power systems. However, there are still some problems to be solved, for example, the lack of regulatory system, environmental challenges and so on. In the future, we will strive for a better optimized structure and establish a comprehensive security assessment model for blockchain-based energy trading system.

Peer-to-peer based energy trading system for heterogeneous small-scale DERs

2017 ◽  
Author(s):  
Yoon-Sik Yoo ◽  
Taein Hwang ◽  
Shinyuk Kang ◽  
S.H. Shah Newaz ◽  
Il-Woo Lee ◽  
...  
Keyword(s):  
Peer To Peer ◽  
Small Scale ◽  
Trading System ◽  
Energy Trading

scholarly journals Event-Driven Energy Trading System in Microgrids: Aperiodic Market Model Analysis With a Game Theoretic Approach

IEEE Access ◽  
2017 ◽  
Vol 5 ◽  
pp. 26291-26302 ◽  
Author(s):  
Sangdon Park ◽  
Joohyung Lee ◽  
Ganguk Hwang ◽  
Jun Kyun Choi
Keyword(s):  
Model Analysis ◽  
Market Model ◽  
Theoretic Approach ◽  
Trading System ◽  
Energy Trading ◽  
Event Driven ◽  
Game Theoretic ◽  
Game Theoretic Approach

scholarly journals SynergyGrids: blockchain-supported distributed microgrid energy trading

2021 ◽  
Author(s):  
Moayad Aloqaily ◽  
Ouns Bouachir ◽  
Öznur Özkasap ◽  
Faizan Safdar Ali
Keyword(s):  
Energy Consumption ◽  
Energy Demand ◽  
Hybrid Approach ◽  
Energy Resources ◽  
Local Energy ◽  
Trading System ◽  
Data Set ◽  
Energy Trading ◽  
Hybrid Energy ◽  
Smart Contract

AbstractGrowing intelligent cities is witnessing an increasing amount of local energy generation through renewable energy resources. Energy trade among the local energy generators (aka prosumers) and consumers can reduce the energy consumption cost and also reduce the dependency on conventional energy resources, not to mention the environmental, economic, and societal benefits. However, these local energy sources might not be enough to fulfill energy consumption demands. A hybrid approach, where consumers can buy energy from both prosumers (that generate energy) and also from prosumer of other locations, is essential. A centralized system can be used to manage this energy trading that faces several security issues and increase centralized development cost. In this paper, a hybrid energy trading system coupled with a smart contract named SynergyGrids has been proposed as a solution, that reduces the average cost of energy and load over the utility grids. To the best of our knowledge, this work is the first attempt to create a hybrid energy trading platform over the smart contract for energy demand prediction. An hourly energy data set has been utilized for testing and validation purposes. The trading system shows 17.8% decrease in energy cost for consumers and 76.4% decrease in load over utility grids when compared with its counterparts.

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