Smart Management of Energy Storage in Microgrid: Adapting the Control Algorithm to Specific Industrial Facility Conditions

Dominika Kaczorowska (), Jacek Rezmer, Vishnu Suresh () and Tomasz Sikorski
Additional contact information
Dominika Kaczorowska: Faculty of Electrical Engineering, Wroclaw University of Science and Technology, 50-370 Wrocław, Poland
Jacek Rezmer: Faculty of Electrical Engineering, Wroclaw University of Science and Technology, 50-370 Wrocław, Poland
Vishnu Suresh: Faculty of Electrical Engineering, Wroclaw University of Science and Technology, 50-370 Wrocław, Poland
Tomasz Sikorski: Faculty of Electrical Engineering, Wroclaw University of Science and Technology, 50-370 Wrocław, Poland

Sustainability, 2023, vol. 15, issue 21, 1-15

Abstract: The article introduces a method for optimizing energy storage system scheduling in industrial microgrids. It employs a PSO-based heuristic algorithm using daily generation and load forecasts. The objective is economic optimization, minimizing energy costs, and maximizing profits. Market energy prices and distributor tariffs are the base of the objective function. An algorithm maintains the plan by controlling storage power based on real-time microgrid measurements, aligning with the intended power exchange curve. Due to PSO’s ability to perform multidimensional optimization, it is possible to find the global optimum of the objective function. To validate the practical applicability of this approach, it is exemplified through its implementation within a real-world industrial microgrid setting. The presented results indicate the method’s effectiveness but also show its weaknesses. For the two considered cases, a decrease in operating costs of 6.7% and 10.8% was achieved, respectively. On the other hand, the best results are obtained for shorter forecasts, which is why the algorithm, despite long planning periods, revises the ESS operation plan whenever there are significant deviations between the forecast and the actual power.

Keywords: microgrid; energy storage system; control optimization; economic efficiency (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://www.mdpi.com/2071-1050/15/21/15576/pdf (application/pdf)
https://www.mdpi.com/2071-1050/15/21/15576/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jsusta:v:15:y:2023:i:21:p:15576-:d:1273254

Access Statistics for this article

Sustainability is currently edited by Ms. Alexandra Wu

More articles in Sustainability from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().