a mathematical modeling technique with network flows for social welfare maximization in deregulated electricity markets
Clicks: 330
ID: 128766
2016
Article Quality & Performance Metrics
Overall Quality
Not rated
Combines reader engagement with the AI quality analysis. This
article has not been analysed, so there is no overall score —
reader engagement is measured and shown alongside.
Reader Engagement
Steady Performance
30.0
/100
330 views
44 readers
AI Quality Assessment
Not analyzed
Readership in this journal
SteadyRanked #4 of 10 articles by views in industrial health
Most read
Least read
Bar heights use a square-root scale.
Mint this article as an NFT
Not yet mintedCreate a permanent, verifiable on-chain record of this article on the Scimatic Network. The NFT is held in your Journament account, and you can withdraw it to your own wallet at any time.
5
SUSD
one-off · no wallet required
Abstract
This paper presents a sequential solution method to discover efficient trades in an electricity market model. The market model represents deregulated electricity market consisting of four types of participants: independent power producers, retailers, public utilities, and consumers. Our model is based on graph theory, and the market participants are denoted by a network composes of three types of agents including sellers, buyers, and traders. The market participants have different capacity and demand of electricity from each other, and each electricity trade should satisfy the capacity and demand. Our sequential solution method can discover efficient electricity trades satisfying the constraints regarding capacity and demand by utilizing network flow. Simulation results demonstrate the efficiency of electricity trades determined by our method by examining social welfare, which is the total of payoffs of all market participants. Furthermore, the simulation results also indicate the allocation of payoff to each market participant.
| Reference Key |
hase2016operationsa
Use this key to autocite in the manuscript while using
SciMatic Manuscript Manager or Thesis Manager
|
|---|---|
| Authors | ;Ryo Hase;Norihiko Shinomiya |
| Journal | industrial health |
| Year | 2016 |
| DOI |
10.1016/j.orp.2016.09.003
|
| URL | |
| Keywords |
Citations
No citations found. To add a citation, contact the admin at info@scimatic.org
Comments
No comments yet. Be the first to comment on this article.