A Bi-Level EV Aggregator Coordination Scheme for Load Variance Minimization with Renewable Energy Penetration Adaptability

Clicks: 283
ID: 68343
2018
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.
AI Quality Assessment
Not analyzed
Readership in this journal
Steady

Ranked #58 of 220 articles by views in energies

Most read Least read

Bar heights use a square-root scale. Only the 120 most-read articles are drawn; the journal has 220 in total.

Mint this article as an NFT
Not yet minted

Create 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
The provision of ancillary services by electric vehicles (EVs) such as load smoothing and renewable energy (RE) compensation in the form of an aggregated storage is more regulated in the smart grid context. As such, the presence of multiple EV aggregators in the distribution network requires adept supervision by the distribution system operator (DSO). In this paper, a coordination scheme of aggregators is proposed to smoothen the load profile of distribution networks by enacting EV discharging during peak load and off-peak charging, keeping in view the EV driving requirements. A bi-level on-line interaction procedure from the DSO to the aggregators and vice versa is devised to manage the aggregators based upon their energy capacity and requirements. The aggregators employ a water-filling algorithm in a two-step EV power allocation method. The proposed scheme operation is demonstrated on an medium voltage (MV) distribution feeder located in Seoul with its actual traffic density data. The results show the achievement of peak shaving and valley filling objectives under aggregator coordination and that the EVs are completely charged before departure. The effect of various EV penetration levels and adaptivity of the scheme to RE incorporation is also verified. Furthermore, a comparison with an existing peak shaving method shows the superior performance of the proposed scheme.
Reference Key
khan2018aenergies Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Khan, Saad Ullah;Mehmood, Khawaja Khalid;Haider, Zunaib Maqsood;Rafique, Muhammad Kashif;Kim, Chul-Hwan;
Journal energies
Year 2018
DOI
DOI not found
URL
Keywords

Citations

No citations found. To add a citation, contact the admin at info@scimatic.org

No comments yet. Be the first to comment on this article.