Power Flow Forecasts: A Status Quo Review. Part 1: RES Generation Prediction

• Autorzy: Kopyt Marcin

Identyfikatory

DOI

10.15199/48.2020.11.01

Warianty tytułu

PL

Prognozy przepływów mocy-przegląd status quo. Część 1: Predykcja generacji z OZE

• Języki publikacji: EN

Abstrakty

EN

In recent years, rising electricity demand accompanied by CO2 reduction targets has dramatically increased RES penetration into power systems, giving rise to the need to estimate power production and demand to properly manage power infrastructure. This paper is Part 1 of an extensive, two-part review of recent literature related to forecasts of RES generation, electricity demand and power flows. This Part 1 focuses on forecasts of RES generation.

PL

W ostatnich latach chęć pokrycia zapotrzebowania na energię elektryczną przy jednoczesnej redukcji CO2, spowodowała silny wzrost mocy zainstalowanej OZE. Konsekwencją jest potrzeba szacowania generacji z OZE oraz zapotrzebowania na energię, by poprawnie zarządzać pracą systemu elektroenergetycznego. Niniejszy artykuł to 1 z 2 części szerokiej analizy najnowszej literatury dotyczącej prognoz generacji z OZE, zapotrzebowania i przepływów mocy i prezentuje pierwszy z aspektów.

Słowa kluczowe

EN

forecasting; photovoltaics; wind turbines; review

PL

prognozowanie; panele fotowoltaiczne; turbiny wiatrowe; przegląd

• Wydawca: Wydawnictwo SIGMA-NOT
• Czasopismo: Przegląd Elektrotechniczny
• Rocznik: 2020
• Tom: R. 96, nr 11
• Strony: 1--4
• Opis fizyczny: Bibliogr. 24 poz., tab.

Twórcy

autor

Kopyt Marcin

• Politechnika Warszawska, Instytut Elektroenergetyki, ul. Koszykowa 75, 00-662 Warszawa

Bibliografia

• [1] EC European Commission and others. Directive 2009/28/EC of the European Parliament and of the Council of 23 April 2009 on the promotion of the use of energy from renewable sources and amending and subsequently repealing Directives 2001/77/EC and 2003/30, Official Journal of the European Union Belgium; 2009. Available: https://eur-lex.europa.eu/eli/dir/2009/28/oj
• [2] General Secretariat of the European Council. 2030 Climate And Energy Policy Framework European Council 23/24 October 2014 – Conclusions, Brussels; 24 October 2014. Available:http://www.consilium.europa.eu/uedocs/cms_data/docs/pressdata/en/ec/145397.pdf
• [3] European Commission. Proposal for a DIRECTIVE OF THE EUROPEAN PARLIAMENT AND OF THE COUNCIL on the promotion of the use of energy from renewable sources, COM(2016) 767 final/22016/0382(COD), Brussels; 23.02.2017
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• [7] Çevik H., Çunkaş M. Polat K., A new multistage short-term wind power forecast model using decomposition and artificial intelligence methods, Physica A, 534 (2019),1-16
• [8] Fang X ,Hodge B-M. ,Du E., Zhang N., Li F., Modelling wind power spatial-temporal correlation in multi-interval optimal power flow: A sparse correlation matrix approach, Applied Energy, 230 (2018), 531-539
• [9] Rajanarayan Prusty B., Debashisha Jena, A spatiotemporal probabilistic model‐based temperature‐augmented probabilistic load flow considering PV generations, International Transactions on Electrical Energy Systems, 29 (2019), no. 5
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• [16] Wang C, Zhang H., Ma P., Wind power forecasting based on singular spectrum analysis and a new hybrid Laguerre neural network, Applied Energy, 259 (2020)
• [17] Afshari-Igder M., Niknam T., Khooban M-H., Probabilistic wind power forecasting using a novel hybrid intelligent method, Neural Comput & Applic,30 (2018),473–485
• [18] López E., Valle C., Allende H., Gil E., Madsen H., Wind Power Forecasting Based on Echo State Networks and Long Short- Term Memory, Energies, 11 (2018)
• [19] Kushwaha V., Pindoriya N.M, A SARIMA-RVFL hybrid model assisted by wavelet decomposition for very short-term solar PV power generation forecast, Renewable Energy, 140 (2019), 124-139
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Uwagi

Opracowanie rekordu ze środków MNiSW, umowa Nr 461252 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2020).