Real-time smart charging based on precomputed schedules


Frendo, Oliver ; Gärtner, Nadine ; Stuckenschmidt, Heiner



DOI: https://doi.org/10.1109/TSG.2019.2914274
URL: https://ieeexplore.ieee.org/document/8703849
Additional URL: https://www.researchgate.net/publication/332814412...
Document Type: Article
Year of publication: 2019
The title of a journal, publication series: IEEE Transactions on Smart Grid
Volume: 10
Issue number: 6
Page range: 6921-6932
Place of publication: New York, NY
Publishing house: IEEE
ISSN: 1949-3053 , 1949-3061
Publication language: English
Institution: School of Business Informatics and Mathematics > Praktische Informatik II (Stuckenschmidt 2009-)
Subject: 004 Computer science, internet
Abstract: Employees are increasingly using electric vehicles (EVs) as their choice of company car. Charging infrastructure is limited by undersized connection lines and a lack of charging stations on company premises. Upgrades require significant financial investment, time and effort. Smart charging represents an approach to making the most of existing infrastructure while satisfying charging needs. The objective of smart charging depends on the business context. Objectives of interest include fair share maximization, electricity cost minimization, peak demand minimization and load imbalance minimization. During business hours, EV arrivals and departures are predictable while still containing uncertainty. To utilize this knowledge ahead of time, this work presents a novel approach for combining day-ahead and real-time planning for smart charging. First, we model the problem using mixed integer programming for day-ahead planning to precompute schedules. Next, we propose a schedule guided heuristic which takes as input precomputed schedules and adapts them in real-time as new information arrives. Both methods use a parameterized weighting mechanism to flexibly combine and emphasize individual objectives of smart charging. Experimental results from simulations show significant benefits of combining day-ahead and real-time planning over using a single planning approach in isolation. Improvements include increased fair share and decreased energy costs.

Dieser Eintrag ist Teil der Universitätsbibliographie.




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Frendo, Oliver ; Gärtner, Nadine ; Stuckenschmidt, Heiner ORCID: 0000-0002-0209-3859 (2019) Real-time smart charging based on precomputed schedules. IEEE Transactions on Smart Grid New York, NY 10 6 6921-6932 [Article]


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