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Cited 13 time in webofscience Cited 14 time in scopus
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Optimal Hourly Scheduling of Community-Aggregated Electricity Consumptionopen access

Authors
Khodaei, AminShahidehpour, MohammadChoi, Jaeseok
Issue Date
Nov-2013
Publisher
SPRINGER SINGAPORE PTE LTD
Keywords
Residential community; Hourly community-aggregated load scheduling; Real-time electricity price; Lagrangian relaxation; Mixed integer program
Citation
JOURNAL OF ELECTRICAL ENGINEERING & TECHNOLOGY, v.8, no.6, pp 1251 - 1260
Pages
10
Indexed
SCIE
SCOPUS
KCI
Journal Title
JOURNAL OF ELECTRICAL ENGINEERING & TECHNOLOGY
Volume
8
Number
6
Start Page
1251
End Page
1260
URI
https://scholarworks.gnu.ac.kr/handle/sw.gnu/20394
DOI
10.5370/JEET.2013.8.6.1251
ISSN
1975-0102
2093-7423
Abstract
This paper presents the optimal scheduling of hourly consumption in a residential community (community, neighborhood, etc.) based on real-time electricity price. The residential community encompasses individual residential loads, communal (shared) loads, and local generation. Community-aggregated loads, which include residential and communal loads, are modeled as fixed, adjustable, shiftable, and storage loads. The objective of the optimal load scheduling problem is to minimize the community-aggregated electricity payment considering the convenience of individual residents and hourly community load characteristics. Limitations are included on the hourly utility load (defined as community-aggregated load minus the local generation) that is imported from the utility grid. Lagrangian relaxation (LR) is applied to decouple the utility constraint and provide tractable subproblems. The decomposed subproblems are formulated as mixed-integer programming (MIP) problems. The proposed model would be used by community master controllers to optimize the utility load schedule and minimize the community-aggregated electricity payment. Illustrative optimal load scheduling examples of a single resident as well as an aggregated community including 200 residents are presented to show the efficiency of the proposed method based on real-time electricity price.
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