Reliability and life cycle cost assessment of local energy systems

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Project abstract

The port industry is transforming towards smart ports by developing a sustainable maritime transportation system and greater electrification. In the process, approaches for the inclusion of renewables, emissions reduction are gathering momentum with advancements in technologies. Global containerization leads to high electricity demand at container terminals and the electricity demand is highly dynamic and dependent on different operation processes. A correctly forecasted electricity demand profile is crucial for less expensive and reliable power operation and planning. Parnian et al.[1] provides results of a forecast of the hourly peak load demand and short-term electricity demand profile in a container terminal in the Port of Gävle. Firstly in [1], Artificial Neural Network (ANN) method is used to predict the container terminal baseload demand. Second, the worst-case simultaneous peak load is estimated. Third, the day ahead load profile is modeled based on the handling operation scheduled for the day. This approach is implemented at the container terminal in Port of Gävle, and the results have been used in dialogue with the local energy company for the future predicted need of load.

Inputs from [1] have been used to assess the possibility of a future local energy system covering the port area. Therefore, the current project focuses on obtaining a suitable sizing of Photo-Voltaic (PV) electricity generation and battery storage systems. This includes forecasting the PV generation, modeling and optimizing the size of grid-connected PV-battery system for the port area. The ultimate aim is to weigh the Life Cycle Cost (LCC) against the reliability of the systems to arrive at the smartest design decision.

[1]. Parnian Alikhani, Lina Bertling Tjernberg, Linda Astner, Pontus Donnerstål. “Forecasting the Electrical Demand at the Port of Gavle Container Terminal”, 2021 IEEE Power & Energy Society Innovative Smart Grid Technologies Conference (ISGT) Europe, Espoo, Finland, 2021.

Keywords:  smart ports, demand forecasting, generation forecasting, container terminal, peak load demand, Life Cycle Cost (LCC), Photo-Voltaic (PV) and battery storage.

Summary of work

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Event log

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Project reference-group

Adam Engstrom,  EON
Jonathan Hallinder,  EON
Ying He,  Vattenfall

Publications by this researcher

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Peak Demand Shaving Based on Solar and Load Forecasting at Port of Gavle
Pavithra Gopalakrishnan,   Parnian Alikhani,   Hamza Shafique,   Lina Bertling Tjernberg,   Jonathan Hallinder,   Adam Engström,   Ying He.
2022,   17th International Conference on Probabilistic Methods Applied to Power Systems, PMAPS 2022, Manchester, 12 June 2022, through 15 June 2022

Expert-Guided Security Risk Assessment of Evolving Power Grids
Seppo Borenius,   Pavithra Gopalakrishnan,   Lina Bertling Tjernberg,   Raimo Kantola.
2022,   Energies, vol. 15(9)

Publication list last updated from DiVA on 2024-08-22 22:58.

Page started: 2021-10-01
Last generated: 2024-08-22