A Method to Improve the Accuracy of Simulation Models: A Case Study on Photovoltaic System Modelling
| Autor: | Wisut Titiroongruang, Sasiwimon Songtrai, Kobsak Sriprapha, Songkiate Kittisontirak, Perawut Chinnavornrungsee, Aekkawat Bupi, Phassapon Manosukritkul, Surasak Niemcharoen |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2021 |
| Předmět: |
Control and Optimization
Computer science 020209 energy Data management Energy Engineering and Power Technology Climate change 02 engineering and technology Solar irradiance lcsh:Technology photovoltaic 0202 electrical engineering electronic engineering information engineering Point (geometry) Electrical and Electronic Engineering Diffusion (business) Engineering (miscellaneous) Simulation learning Renewable Energy Sustainability and the Environment business.industry lcsh:T Photovoltaic system Simulation modeling Process (computing) preciseness function learning model (PFL model) solar irradiance 021001 nanoscience & nanotechnology module temperature 0210 nano-technology business Energy (miscellaneous) |
| Zdroj: | Energies Volume 14 Issue 2 Energies, Vol 14, Iss 372, p 372 (2021) |
| ISSN: | 1996-1073 |
| DOI: | 10.3390/en14020372 |
| Popis: | This research presents a method to improve data accuracy for the more efficient data management of the studied applications. The data accuracy was improved using the preciseness function learning model (PFL model). It contains a database in which the amount of data is more or less dependent on all of the possible behavior of the studied application. The proposed model improves data with functions obtained by optimizing curves to represent the data at each point, which estimate the database&rsquo s diffusion behavior, and functions can be built around all of the various forms of databases. The proposed model always updates its database after processing. It has been learning to optimize the processing precision. In order to verify the precision of the proposed model through its application to a PV system simulation model, the process&rsquo s database should contain at least one year. This is because the overall behavior of the PV power output in Thailand depends on the seasonal weather Thailand has three seasons in a period of one year. The testing was performed by comparing the PV power output. The simulation results with the actual measurement data (12 MW PV system) can be divided into two conditions: the daily comparison and the seasonal PV power output. As a result, the proposed model can accurately simulate the PV power output despite the sudden daily climate change. The average nRMSE (normalized RMSE) of the proposed model is very low (1.23%), and ranges from 0.30% to 2.26%. Therefore, it has been proven that this model is very accurate. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|
| Nepřihlášeným uživatelům se plný text nezobrazuje | K zobrazení výsledku je třeba se přihlásit. |