A Case Study on Smart Grid Technologies with Renewable Energy for Central Parts of Hamburg

Pierre Bouchard (), Stefan Voß, Leonard Heilig and Xiaoning Shi
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Pierre Bouchard: Institute of Information Systems, University of Hamburg, 20148 Hamburg, Germany
Stefan Voß: Institute of Information Systems, University of Hamburg, 20148 Hamburg, Germany
Leonard Heilig: Institute of Information Systems, University of Hamburg, 20148 Hamburg, Germany
Xiaoning Shi: Institute of Information Systems, University of Hamburg, 20148 Hamburg, Germany

Sustainability, 2023, vol. 15, issue 22, 1-29

Abstract: Globally, efforts are made to balance energy demands and supplies while reducing CO 2 emissions. Germany, in its transition to renewable energies, faces challenges in regulating its energy supply. This study investigates the impact of various technologies, including energy storage solutions, peak shaving, and virtual buffers in a smart energy grid on a large scale. Real-time energy supply and demand data are collected from the Port of Hamburg and HafenCity in Germany to analyze the characteristics of different technologies such as load shifting of reefer containers and private electric vehicles’ energy, as well as pumped hydro storage. Through simulations, we assess the usability of renewable energies in a smart grid with versatile energy demands and determine the effects of peak shaving, storage solutions, and virtual buffers on uncertain energy supply. Our case study reveals that integrating smart grid technologies can reduce the overproduction of renewable energies needed to prevent blackouts from 95% to 65% at the HafenCity and the Port of Hamburg. Notably, large, reliable, and predictable energy consumers like the Port of Hamburg play a vital role in managing the uncontrollable nature of renewables, resulting in up to 31% cost savings for new infrastructure.

Keywords: smart energy grid; seaports; renewable energy; peak shaving; virtual buffer; energy management (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2023
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