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Titel: Forecast Quality of Physics-Based and Data-Driven PV Performance Models for a Small-Scale PV System
VerfasserIn: Stüber, Moritz
Scherhag, Felix
Deru, Matthieu
Ndiaye, Alassane
Sakha, Muhammad Moiz
Brandherm, Boris
Baus, Jörg
Frey, Georg
Sprache: Englisch
Titel: Frontiers in energy research
Bandnummer: 9
Startseite: 1
Endseite: 16
Verlag/Plattform: Frontiers
Erscheinungsjahr: 2021
Dokumenttyp: Journalartikel / Zeitschriftenartikel
Abstract: In the context of smart grids, the need for forecasts of the power output of small-scale photovoltaic (PV) arrays increases as control processes such as the management of flexibilities in the distribution grid gain importance. However, there is often only very little knowledge about the PV systems installed: even fundamental system parameters such as panel orientation, the number of panels and their type, or time series data of past PV system performance are usually unknown to the grid operator. In the past, only forecasting models that attempted to account for cause-and-effect chains existed; nowadays, also data-driven methods that attempt to recognize patterns in past behavior are available. Choosing between physics-based or data-driven forecast methods requires knowledge about the typical forecast quality as well as the requirements that each approach entails. In this contribution, the achieved forecast quality for a typical scenario (day-ahead, based on numerical weather predictions [NWP]) is evaluated for one physics-based as well as five different data-driven forecast methods for a year at the same site in south-western Germany. Namely, feed-forward neural networks (FFNN), long short-term memory (LSTM) networks, random forest, bagging and boosting are investigated. Additionally, the forecast quality of the weather forecast is analyzed for key quantities. All evaluated PV forecast methods showed comparable performance; based on concise descriptions of the forecast approaches, advantages and disadvantages of each are discussed. The approaches are viable even though the forecasts regularly differ significantly from the observed behavior; the residual analysis performed offers a qualitative insight into the achievable forecast quality in a typical real-world scenario.
DOI der Erstveröffentlichung: 10.3389/fenrg.2021.639346
URL der Erstveröffentlichung: https://www.frontiersin.org/articles/10.3389/fenrg.2021.639346/full
Link zu diesem Datensatz: hdl:20.500.11880/31848
http://dx.doi.org/10.22028/D291-34826
ISSN: 2296-598X
Datum des Eintrags: 13-Okt-2021
Drittmittel / Förderung: Bundesministerium für Wirtschaft und Energie (BMWi); SINTEG-Projekt "Designetz"
Fördernummer: 03SIN224
Fakultät: NT - Naturwissenschaftlich- Technische Fakultät
Fachrichtung: NT - Systems Engineering
Professur: NT - Prof. Dr. Georg Frey
Sammlung:SciDok - Der Wissenschaftsserver der Universität des Saarlandes

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