2023
DOI: 10.1016/j.engappai.2023.107190
|View full text |Cite
|
Sign up to set email alerts
|

Prediction-based peer-to-peer energy transaction market design for smart grids

I. Chien,
P. Karthikeyan,
Pao-Ann Hsiung
Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
2

Citation Types

0
1
0

Year Published

2024
2024
2024
2024

Publication Types

Select...
6

Relationship

0
6

Authors

Journals

citations
Cited by 11 publications
(2 citation statements)
references
References 21 publications
0
1
0
Order By: Relevance
“…Blockchain's influence extends to the development of P2P energy trading platforms. These platforms allow for the direct trade of excess renewable energy between individuals and businesses, bypassing traditional energy intermediaries [ [84] , [85] , [86] , [87] ]. This direct trade leads to more efficient use of renewable energy and potentially lower costs for consumers [ 3 ].…”
Section: Introductionmentioning
confidence: 99%
“…Blockchain's influence extends to the development of P2P energy trading platforms. These platforms allow for the direct trade of excess renewable energy between individuals and businesses, bypassing traditional energy intermediaries [ [84] , [85] , [86] , [87] ]. This direct trade leads to more efficient use of renewable energy and potentially lower costs for consumers [ 3 ].…”
Section: Introductionmentioning
confidence: 99%
“…Energies 2024, 17, 2119 3 of 30 transactions occur between microgrids, the scheduling strategy of micro-grids is relatively simple, and the output of the gas boiler is lower, making the overall scheduling more flexible. Chien et al [16] proposed the application scenario of tradable energy systems in the operation of community microgrids and established a model suitable for P2P transactions between microgrid users with distributed energy sources and storage. Microgrid users have the ability to trade with the grid on demand or surplus electricity in P2P markets and can choose to store excess electricity.…”
Section: Introductionmentioning
confidence: 99%