{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,30]],"date-time":"2026-06-30T07:22:05Z","timestamp":1782804125879,"version":"3.54.5"},"reference-count":32,"publisher":"MDPI AG","issue":"23","license":[{"start":{"date-parts":[[2020,11,27]],"date-time":"2020-11-27T00:00:00Z","timestamp":1606435200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"The work was within in framework of statutory research","award":["06\/010\/BK-20\/0042"],"award-info":[{"award-number":["06\/010\/BK-20\/0042"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Applied Sciences"],"abstract":"<jats:p>The impact of environmental regulations introduced by the European Union is of key importance for electricity generation systems. The Polish fuel structure of electricity production is based on solid fuels. Moreover, the generating base is outdated and must gradually be withdrawn from the power system. In this context, Poland\u2019s energy policy is undergoing a transformation as climate and environmental regulations are becoming increasingly stringent for the energy sector based on solid fuels (hard coal and lignite). However, the transformation process must be adapted to market demands, because the overriding goal is to ensure energy security by maintaining the continuity of energy supplies and an acceptable electricity price. This directly contributes to the development of the entire economy and the standard of living of the society, in accordance with the European Agreement establishing an association between the Republic of Poland and the European Communities and their Member States, signed on 16 December 1991, and the European Energy Charter, signed on 17 December 1991. Ensuring energy security is the most important goal of the energy policy. Therefore, energy companies must forecast the demand. The main goal of this article is to develop a mathematical model of electricity consumption by 2040 by all sectors of the economy: industry, transport, residential, commercial and public services, agriculture, forestry, and fishing. In order to achieve the intended goal, a model was developed by using Long Short-Term Memory (LSTM) artificial neural networks, which belong to deep learning techniques and reflect long-term relationships in time series for a small set of statistical data. The results show that the proposed model can significantly improve the accuracy of forecasts (1\u20133% of mean absolute percentage error (MAPE) for the analyzed sectors of the economy).<\/jats:p>","DOI":"10.3390\/app10238455","type":"journal-article","created":{"date-parts":[[2020,11,27]],"date-time":"2020-11-27T02:13:51Z","timestamp":1606443231000},"page":"8455","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":34,"title":["Using the LSTM Network to Forecast the Demand for Electricity in Poland"],"prefix":"10.3390","volume":"10","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-9300-215X","authenticated-orcid":false,"given":"Anna","family":"Manowska","sequence":"first","affiliation":[{"name":"Faculty of Mining, Safety Engineering and Industrial Automation, Silesian University of Technology, 44-100 Gliwice, Poland"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2020,11,27]]},"reference":[{"key":"ref_1","unstructured":"PEP2040 2019\u2014Ministry of State Assets (2020, July 21). The Energy Policy of Poland until 2040 (PEP2040) (Ministerstwo Aktyw\u00f3w Pa\u0144stwowych in Polityka Energetyczna Polski do 2040 roku (PEP2040)), (In Polish)."},{"key":"ref_2","unstructured":"Council of Ministers 2017 (2020, November 03). The Strategy for Responsible Development until 2020\u2014With Prospects until 2030. Document Adopted by Resolution of the Council of Ministers on 14 February 2017. (Strategia na rzecz Odpowiedzialnego Rozwoju do roku 2020 (z perspektyw\u0105 do 2030 r.)\u2013SOR Zosta\u0142a przyj\u0119ta przez Rad\u0119 Ministr\u00f3w 14 lutego 2017 r.), (In Polish)."},{"key":"ref_3","unstructured":"(2020, July 20). Ministry of State Assets, 2019. National Energy and Climate Plan for 2021\u20132030. Assumptions, Goals and Policies Project\u2014v. 3.1. 04\/01\/2019. (Ministerstwo Energii. Krajowy plan na rzecz energii i klimatu na lata 2021\u20132030. Za\u0142o\u017cenia i cele oraz polityki i dzia\u0142ania. Projekt\u2014w. 3.1. 04.01.2019), (In Polish)."},{"key":"ref_4","doi-asserted-by":"crossref","unstructured":"Bluszcz, A. (2018, January 2\u20138). The emissivity and energy intensity in EU countries\u2013consequences for the polish economy. Geo Conference. Proceedings of the Conference Proceedings of Energy and Clean Technologies, Albena, Bulgaria.","DOI":"10.5593\/sgem2018\/4.2\/S19.081"},{"key":"ref_5","unstructured":"Gawlik, L., and Mokrzycki, E. (2018, January 24\u201326). The importance of fossil fuels in the energy transformation of Poland. Proceedings of the Materials of the XXIVth Electricity Market Conference (REE 2018)\u2014Current Challenges, (Znaczenie Paliw Kopalnych w Transformacji Energetycznej Polski [W:] Materia\u0142y XXIV Konferencji Naukowo-Technicznej Rynek Energii Elektrycznej 2018\u2014Aktualne wyzwania), Kazimierz Dolny, Poland. (In Polish)."},{"key":"ref_6","doi-asserted-by":"crossref","unstructured":"Gawlik, L., and Mokrzycki, E. (2019). Changes in the structure of electricity generation in Poland in view of the EU climate package. Energies, 12.","DOI":"10.3390\/en12173323"},{"key":"ref_7","first-page":"269","article-title":"Challenges of the energy sector in Poland from the shareholders perspective (Wyzwania sektora energetycznego w Polsce z perspektywy akcjonariuszy)","volume":"1","author":"Lipski","year":"2016","journal-title":"Acad. J. State Univ. Appl. Sci. P\u0142ock. Econ. Sci."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"401","DOI":"10.1016\/j.scs.2018.03.002","article-title":"Utility companies strategy for short-term energy demand forecasting using machine learning based models","volume":"39","author":"Ahmad","year":"2018","journal-title":"Sustain. Cities Soc."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"460","DOI":"10.1016\/j.scs.2018.12.013","article-title":"2019. Nonlinear autoregressive and random forest approaches to forecasting electricity load for utility energy management systems","volume":"39","author":"Ahmad","year":"2019","journal-title":"Sustain. Cities Soc."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"169","DOI":"10.1109\/TIA.2004.841029","article-title":"Improve the unit commitment scheduling by using the neural-network-based short-term load forecasting","volume":"41","author":"Saksornchai","year":"2005","journal-title":"IEEE Trans. Ind. Appl."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"257","DOI":"10.1016\/j.scs.2017.08.009","article-title":"Electrical load forecasting models: Acritical systematic review","volume":"35","author":"Kuster","year":"2017","journal-title":"Sustain. Cities Soc."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"2498","DOI":"10.1016\/j.rser.2017.09.016","article-title":"Electricity consumption and economic growth nexus in Beijing: A causal analysis of quarterly sectoral data","volume":"82","author":"Liu","year":"2018","journal-title":"Ren. Sustain. Energy Rev."},{"key":"ref_13","unstructured":"Eurostat (2020, July 20). Available online: https:\/\/ec.europa.eu\/eurostat."},{"key":"ref_14","unstructured":"ESR Regulation (2018). Regulation of the European Parliament and of the Council No. 2018\/842 of 30 May 2018 on Binding Annual Reductions of GREENHOUSE Gas Emissions by Member States from 2021 to 2030 Contributing to Climate Action to Meet The Commitments under the Paris Agreement and Amending Regulation (EU) No 525\/2013, Official Journal of the European Union."},{"key":"ref_15","unstructured":"(2020, July 20). National Center for Balancing and Emissions Management. Available online: https:\/\/www.kobize.pl."},{"key":"ref_16","unstructured":"Ministry of Economy 2009 Poland\u2019s Energy Policy until 2030. Appendix to Resolution no. 202\/2009 of the Council of Ministers of 10 November 2009."},{"key":"ref_17","unstructured":"Forum Energii 2020 (2020, July 21). Energy Transformation in Poland. 2020 Edition (Transformacja energetyczna w Polsce. Edycja 2020). (In Polish)."},{"key":"ref_18","first-page":"5","article-title":"The forecast of Polish power production sector development by 2050\u2212Coal scenario (Prognoza rozwoju polskiego sektora wytw\u00f3rczego do 2050 roku\u2014scenariusz w\u0119glowy)","volume":"19","author":"Szczerbowski","year":"2016","journal-title":"Polityka Energetyczna Energy Policy J."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"117200","DOI":"10.1016\/j.energy.2020.117200","article-title":"A hybrid approach based on autoregressive integrated moving average and least-square support vector machine for long-term forecasting of net electricity consumption","volume":"197","author":"Kaytez","year":"2020","journal-title":"Energy"},{"key":"ref_20","doi-asserted-by":"crossref","unstructured":"Kaszy\u0144ski, P., and Kami\u0144ski, J. (2020). Coal demand and environmental regulations: A Case Study of the Polish Power Sector. Energies, 13.","DOI":"10.3390\/en13061521"},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"2222","DOI":"10.1109\/TNNLS.2016.2582924","article-title":"LSTM: A search space odyssey","volume":"28","author":"Greff","year":"2015","journal-title":"IEEE Trans. Neural Net. Learn. Syst."},{"key":"ref_22","first-page":"217","article-title":"2020 Analysis and forecasting of the primary energy consumption in Poland using deep learning","volume":"1","author":"Manowska","year":"2018","journal-title":"In\u017cynieria Mineralna J. Polish Mineral. Eng. Soc."},{"key":"ref_23","first-page":"2","article-title":"Minimum sample size requirements for seasonal forecasting models","volume":"6","author":"Hyndman","year":"2008","journal-title":"Foresight"},{"key":"ref_24","first-page":"2451","article-title":"Learning to forget: Continual prediction with LSTM","volume":"13","author":"Gers","year":"2006","journal-title":"Neural Comput."},{"key":"ref_25","doi-asserted-by":"crossref","unstructured":"Gers, F.A., Schhmidhuber, J., and Cummins, F. (1999, January 7\u201310). Learning to forget: Continual prediction with LSTM. Proceedings of the 9th International Conference on Artificial Neural: ICANN \u201999, Networks, Edinburgh, UK.","DOI":"10.1049\/cp:19991218"},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"1735","DOI":"10.1162\/neco.1997.9.8.1735","article-title":"Long short-term memory","volume":"9","author":"Hochreiter","year":"1997","journal-title":"Neural Comput."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"276","DOI":"10.1016\/j.energy.2015.04.039","article-title":"Hybrid methodologies for electricity load forecasting: Entropy-based feature selection with machine learning and soft computing techniques","volume":"86","author":"Jurado","year":"2015","journal-title":"Energy"},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"371","DOI":"10.1016\/j.enconman.2015.02.023","article-title":"Simultaneous day-ahead forecasting of electricity price and load in smart grids","volume":"95","author":"Shayeghi","year":"2015","journal-title":"Energy Conver. Manag."},{"key":"ref_29","unstructured":"Li, J. (2020, July 24). The 10 Deep Learning Methods AI Practitioners Need to Apply. Available online: https:\/\/medium.com\/cracking-the-data-science-interview\/the-10-deep-learning-methods-ai-practitioners-need-to-apply-885259f402c1."},{"key":"ref_30","unstructured":"Ziela\u015b, A., Pawe\u0142ek, B., and Wanat, S. (2003). Prognozowanie Ekonomiczne, Teoria, Przyk\u0142ady, Zadana, Wydawnictwo Naukowe PWN. (In Polish)."},{"key":"ref_31","unstructured":"GUS 2019 (2019). Energy Statistics in 2017 and 2018, Statistics Poland."},{"key":"ref_32","unstructured":"IEA (2019). International Energy Agency, World Energy Outlook."}],"container-title":["Applied Sciences"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2076-3417\/10\/23\/8455\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T10:38:07Z","timestamp":1760179087000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2076-3417\/10\/23\/8455"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,11,27]]},"references-count":32,"journal-issue":{"issue":"23","published-online":{"date-parts":[[2020,12]]}},"alternative-id":["app10238455"],"URL":"https:\/\/doi.org\/10.3390\/app10238455","relation":{},"ISSN":["2076-3417"],"issn-type":[{"value":"2076-3417","type":"electronic"}],"subject":[],"published":{"date-parts":[[2020,11,27]]}}}