Profitability of Photovoltaic and Energy Storage System in a Foundry Plant

• Autorzy: Stawowy Adam , Wrona R. , Sawczuk M. , Lasek D.

Identyfikatory

DOI

10.24425/afe.2023.144300

• Języki publikacji: EN

Abstrakty

EN

The article presents a case study on the effectiveness of photovoltaic farm and battery energy storage in one of the Polish foundries. In the study, we consider two investment options: stand-alone PV farm of 1MWp and the farm together with battery energy storage with a maximum capacity of 4MWh. The Payback Period and Net Present Value were used as measures of investment profitability. The paper provides a detailed presentation of the assumptions made, as well as the PV electricity production model of the farm and the optimization model that determines the operation cycle of the energy storage. The case study presented in the article shows that the PV farm is economically sensible and profitable, but the battery energy storage is too costly to give a positive economic effect. Energy storage is an important element that provides flexibility in the energy supply system, so it is necessary to find a technical solution that gives this flexibility. Such a solution could be a virtual power plant, which could include a foundry energy system with a RES installation inside.

Słowa kluczowe

EN

economics of foundry process; energy management; environmental protection; energy storage system; profitability of photovoltaic

PL

ekonomika procesu odlewniczego; zarządzanie energią; ochrona środowiska; magazynowanie energii; rentowność fotowoltaiki

• Wydawca: Komisja Odlewnictwa Polskiej Akademii Nauk Oddział w Katowicach
• Czasopismo: Archives of Foundry Engineering
• Rocznik: 2023
• Tom: Vol. 23, iss. 2
• Strony: 100--105
• Opis fizyczny: Bibliogr. 12 poz., tab., wykr.

Twórcy

autor

Stawowy Adam

• AGH University of Science and Technology, Faculty of Management, Poland

• https://orcid.org/0000-0001-7200-8640

autor

Wrona R.

• Modus Sp. z o.o., Poland

autor

Sawczuk M.

• Modus Sp. z o.o., Poland

autor

Lasek D.

• Modus Sp. z o.o., Poland

Bibliografia

• [1] Bänsch, K., Busse, J., Meisel, F., Rieck, J., Scholz, S., Volling, T. & Wichmann, M.G. (2021). Energy-aware decision support models in production environments: A systematic literature review. Computers & Industrial Engineering. 159, 107456, 1-27. DOI: https://doi.org/10.1016/ j.cie.2021.107456.
• [2] Pechmann, A. & Zarte, M. (2017). Procedure for generating a basis for PPC systems to schedule the production considering energy demand and available renewable energy. Procedia CIRP. 64, 393-398. https://doi.org/10.1016/j.procir. 2017.03.033.
• [3] Ogliari, E., Dolara, A., Manzolini, G. & Leva, S. (2017). Physical and hybrid methods comparison for the day ahead PV output power forecast. Renewable Energy. 113, 11-21. DOI: 10.1016/j.renene.2017.05.063.
• [4] Photovoltaic farm. Retrieved January 13, 2023, from https://www.soltechenergy.pl/farma-fotowoltaiczna-co-to-jest-i-czy-sie-opaca. (in Polish).
• [5] Holmgren, W.F., Hansen, C.W. & Mikofski, M.A. (2018). Pvlib Python: a Python package for modeling solar energy systems. Journal of Open Source Software. 3(29), 884, 1-3. https://doi.org/10.21105/joss.00884.
• [6] Baringo, L., Rahimiyan, M. (2020). Virtual Power Plants. In L. Baringo & M. Rahimiyan (Eds.), Virtual Power Plants and Electricity Markets: Decision Making Under Uncertainty (pp. 1-7). Cham: Springer.
• [7] About OR-Tools. Retrieved January 13, 2023, from https://developers.google.com/optimization/introduction/overview?hl=en.
• [8] Ma, Y., Lv, Q., Zhang, R., Zhang, Y., Zhu, H. & Yin, W. (2021). Short-term photovoltaic power forecasting method based on irradiance correction and error forecasting. Energy Reports. 7, 5495-5509. DOI: https://doi.org/10.1016/ j.egyr.2021.08.167.
• [9] Dutka, M. (2020). Forecasting electricity generation from renewable energy sources using artificial intelligence methods. Unpublished doctoral dissertation, AGH University of Science and Technology, Kraków, Poland. (in Polish).
• [10] Perveen, G., Rizwan, M. & Goel, N. (2019). Comparison of intelligent modelling techniques for forecasting solar energy and its application in solar PV based energy system. IET Energy Systems Integration. 1(1), 34-51. DOI: 10.1049/iet-esi.2018.0011.
• [11] Naval, N. & Yusta, J.M. (2021). Virtual power plant models and electricity markets – a review. Renewable and Sustainable Energy Reviews. 149, 111393, 1-13. DOI: https://doi.org/10.1016/j.rser.2021.111393.
• [12] Virtual power plant. Retrieved January 13, 2023, from https://www.next-kraftwerke.pl/produkty. (in Polish).

Uwagi

Opracowanie rekordu ze środków MEiN, umowa nr SONP/SP/546092/2022 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2022-2023)