Multi-commodity Optimization of Peer-to-peer Energy Trading Resources in Smart Grid

Jogunola, Olamide; Adebisi, Bamidele; Anoh, Kelvin; Ikpehai, Augustine; Hammoudeh, Mohammad; Harris, Georgina

doi:10.35833/mpce.2020.000136

Cited by 18 publications

(9 citation statements)

References 37 publications

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“…If the initial price of distributed generation is lower than the optimal power selling price, the risk coefficient needs to be increased, λ is set to 0.05, and vice versa is set to -0.05. Similarly, comparing the initial price declared by the remaining power purchase users with the optimal power purchase price, when the initial target price of the user is higher than the best purchase price, it means that it is necessary to increase its risk coefficient, λ is set to 0.05, and vice versa is set to -0.05 [17]. By substituting the changed risk factors into the formula, the quotations of market members can be adjusted.…”

Section: Trading Processesmentioning

confidence: 99%

The distributed trading platform design based on blockchain technology

Zeng,

Zhang,

Chen

et al. 2023

E3S Web Conf.

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At present, Chinese renewable energy generation is growing rapidly, distributed power trading as a market-oriented means to promote the consumption of renewable energy power has attracted wide attention. It is urgent to optimize the mechanism design and build a credible and efficient trading environment to meet the needs of credibility and timeliness of large-scale multi-agent transactions. This paper first constructs a distributed power trading mechanism considering multi-subject transactions, and then elaborates the design idea of the power distributed trading platform based on blockchain technology from three aspects: total volume architecture, platform core technology and platform deployment. Finally, based on the operation of the actual power trading center in a certain region, field application verification is carried out, which proves the effectiveness and superiority of the distributed trading platform designed in this paper based on blockchain technology. The next research will continue to expand the typical model application pilot in the applicable areas to further improve the platform functions.

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Section: Trading Processesmentioning

confidence: 99%

The distributed trading platform design based on blockchain technology

Zeng,

Zhang,

Chen

et al. 2023

E3S Web Conf.

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show abstract

“…For instance, in [4], an intelligent P2P system between prosumers and consumers is proposed allowing a dayahead energy control and generation schedule in order to meet the load demand of the smart grid. The authors in [9] used multi-commodity formulation (MCF) to optimize energy and communication resources in their proposed P2P energy trading platform. They aim to reduce the energy generation cost of the various prosumers and maximize utility with fair resource allocation.…”

Section: A P2p Energy Platformsmentioning

confidence: 99%

FederatedGrids: Federated Learning and Blockchain-Assisted P2P Energy Sharing

Bouachir

Aloqaily

Özkasap

et al. 2022

IEEE Trans. on Green Commun. Netw.

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Peer-to-Peer (P2P) energy trading platforms envisioned energy sectors to satisfy the increasing demand for energy. The vision of this paper is not only to trade energy but also to have part of it being shared. Therefore, this paper presents FederatedGrids which is a P2P energy trading and sharing platform inside and across microgrids. Energy sharing allows exchanging energy between the categories of consumers and prosumers in return for future benefits. FederatedGrids platform uses blockchain and federated learning to enable autonomous activities while providing trust and privacy among all participants. Indeed, based on various smart contracts using federated learning, FederatedGrids calculates a prediction of the future energy production and demand allowing the system to autonomously switch between trading and sharing, and enabling the prosumers to make decisions related to their participation in the energy sharing process. Up to our knowledge, this work is the first attempt to create a hybrid energy trading and sharing platform, with the real sharing meaning, and that uses federated learning over the smart contract for energy demand prediction. The experimental results showed a 17.8% decrease in energy cost for consumers and a 76.4% decrease in load over utility grids.

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“…However, achieving high Quality of Service (QoS) in LoRa communication is still challenging. This is particularly important as LoRa technology is frequently used in real-time applications such as intelligent transportation [2], soil monitoring systems [3], fish monitoring systems [4] and disaster response systems [5]. LoRa can be deployed to meet specific application requirements.…”

Section: Introductionmentioning

confidence: 99%