Detailed Information

Cited 0 time in webofscience Cited 0 time in scopus
Metadata Downloads

전력기기 특성 및 가동 지연 불편도를 고려한 실시간 급작 수요 협상 프레임웍 기반 스마트 그리드 시스템Real Time Sudden Demand Negotiation Framework based Smart Grid System considering Characteristics of Electric device type and Customer’ Delay Discomfort

Other Titles
Real Time Sudden Demand Negotiation Framework based Smart Grid System considering Characteristics of Electric device type and Customer’ Delay Discomfort
Authors
유대선이현수
Issue Date
2019
Publisher
대한전기학회
Keywords
Smart grid; Real time pricing; Day-ahead scheduling; Sudden demand handling; Delay discomfort of consumer; metaheuristics
Citation
전기학회논문지, v.68, no.3, pp.405 - 415
Journal Title
전기학회논문지
Volume
68
Number
3
Start Page
405
End Page
415
URI
https://scholarworks.bwise.kr/kumoh/handle/2020.sw.kumoh/257
ISSN
1975-8359
Abstract
The considerations of the electrical device’ characteristics and the customers’ satisfaction have been important criteria for efficient smart grid systems. In general, an electrical device is classified into a non-interruptible device or an interruptible device. The consideration of the type is an essential information for the efficient smart grid scheduling. In addition, customers’ scheduling preferences or satisfactions have to be considered simultaneously. However, the existing research studies failed to consider both criteria. This paper proposes a new and efficient smart grid scheduling framework considering both criteria. The framework consists of two modules – 1) A day-head smart grid scheduling algorithm and 2) Real-time sudden demand negotiation framework. The first method generates the smart grid schedule efficiently using an embedded genetic algorithm with the consideration of the device’s characteristics. Then, in case of sudden electrical demands, the second method generates the more efficient real-time smart grid schedules considering both criteria. In order to show the effectiveness of the proposed framework, comparisons with the existing relevant research studies are provided under various electricity demand scenarios.
Files in This Item
There are no files associated with this item.
Appears in
Collections
School of Industrial Engineering > 1. Journal Articles

qrcode

Items in ScholarWorks are protected by copyright, with all rights reserved, unless otherwise indicated.

Related Researcher

Researcher LEE, Hyunsoo photo

LEE, Hyunsoo
College of Engineering (Department of Industrial Engineering)
Read more

Altmetrics

Total Views & Downloads

BROWSE