Mihael Skornšek (Author), Gorazd Štumberger (Author)

Abstract

Delo obravnava spremljanje in primerjavo obratovalnih lastnosti sončnih elektrarn. Vsa odstopanja v delovanju lahko spremljamo z dodatnimi meritvami na elektrarni, kot sta sončno obsevanje in temperatura celice. Na podlagi polletnih meritev parametrov delovanja je s pomočjo umetnega nevronskega omrežja v programskem paketu Matlab pripravljen algoritem za izračun napovedane moči sončne elektrarne v danem trenutku, s katerim lahko ovrednotimo pravilno delovanje le-te. Omenjeni algoritem predstavlja nadgradnjo sistema za spremljanje obratovanja sončne elektrarne. Večja razlika med izmerjenimi in z algoritmom določenimi trenutnimi izhodnimi močmi sončne elektrarne kaže na neustrezno delovanje posameznih elementov sončne elektrarne in potrebo po podrobnejšem preverjanju.

Keywords

algoritmi;napovedovanje;trenutna moč;sončne elektrarne;nevronsko omrežje;

Data

Language: Slovenian
Year of publishing:
Typology: 1.08 - Published Scientific Conference Contribution
Organization: UM FERI - Faculty of Electrical Engineering and Computer Science
UDC: 621.311
COBISS: 20727062 Link will open in a new window
Parent publication: 26. mednarodno posvetovanje Komunalna energetika, 9. do 11. maj 2017, Maribor, Slovenija
Views: 850
Downloads: 73
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Other data

Secondary language: English
Secondary title: Algoritem for predicting solar power plant output power with an artificial neural network
Secondary abstract: This work deals with the comparison of operating propertis of photovoltaic power plants. All derogations in the operation of photovoltaic power plant can be monitored with additional measurements of solar irradiation and temperature of photovoltaic cells. Based on data acquired during six months operation of discussed photovoltaic power plant an Artificial Neural Network (ANN) has been built in order to predict output power of the power plant. The ANN complements the already existing monitoring system. When the difference between the ANN predicted and measured output power of the photovoltaic power plant is too high, a detail check of the power plant components is required.
Secondary keywords: algorithm;prediction;out power;solar power plant;artificial neural network;
URN: URN:SI:UM:
Type (COBISS): Not categorized
Pages: Str. [229]-238
ID: 10869818