DocumentCode :
1798213
Title :
A simulation based approach to forecast a demand load curve for a container terminal using battery powered vehicles
Author :
Grundmeier, Nico ; Ihle, Norman ; Hahn, Anna ; Runge, Serge ; Meyer-Barlag, Claas
Author_Institution :
Carl-von-Ossietzky Univ. Oldenburg, Oldenburg, Germany
fYear :
2014
fDate :
6-11 July 2014
Firstpage :
1711
Lastpage :
1718
Abstract :
This article presents a simulation based approach to provide a short-term energy demand load curve forecast in a container terminal. While common methods for forecasting electricity consumption are working well in industrial enterprises with continuous and recurrent production cycles, in a container terminal the processes are highly dynamical. That is why the most common methods are not working well, and a simulation based approach is chosen. If the energy consumption can be forecasted precisely it is possible to benefit from cheaper energy purchase prices. If the container terminal uses battery powered vehicles additional strategies to use the forecast can be employed. One possibility is to reduce the costs by using intelligent strategies for charging the batteries in a battery-exchange station where the energy consumption can be forecasted as well. The important fact is that with the exchange station the load curve can be influenced without interfering in the logistic processes of the terminal because the energy consumption of the transport vessels is decoupled from the logistic processes by the use of batteries. This is why methods like load shifting and peak clipping can be applied quite easily. First, a simulation based approach is introduced to calculate a reliable load forecast of the entire terminal and of the battery changing station. Second, several use cases are presented for how the terminal benefits from this forecast.
Keywords :
battery powered vehicles; load forecasting; power consumption; power engineering computing; power markets; power system reliability; pricing; battery powered vehicle; battery-exchange station; container terminal; electricity consumption; energy consumption; energy purchase pricing; industrial enterprise; load shifting method; logistic processing; peak clipping method; reliability; short-term energy demand load curve forecasting; simulation based approach; Batteries; Containers; Cranes; Energy consumption; Load modeling; Logistics; Vehicles;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Neural Networks (IJCNN), 2014 International Joint Conference on
Conference_Location :
Beijing
Print_ISBN :
978-1-4799-6627-1
Type :
conf
DOI :
10.1109/IJCNN.2014.6889838
Filename :
6889838
Link To Document :
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