| Autor: |
Safwan Ghanem, Ghaeth Fandi, Vladimír Krepl, Tarek Husein, Osama Rzek, Zdenek Muller, Jan Kyncl, Josef Tlustý, Luboš Smutka |
| Jazyk: |
angličtina |
| Rok vydání: |
2021 |
| Předmět: |
|
| Zdroj: |
Applied Sciences, Vol 11, Iss 19, p 8793 (2021) |
| Druh dokumentu: |
article |
| ISSN: |
2076-3417 |
| DOI: |
10.3390/app11198793 |
| Popis: |
COVID-19 is likely to be the 2020s’ deadliest pandemic according to the World Health Organization (WHO). There have been more than 3.7 million confirmed deaths after 15 months spread. Besides the loss of human lives, COVID-19 has other unfavorable impacts on society, education, and the economy. Due to successive lockdowns and the continuous quarantines, the demands on power resources have reduced. Therefore, there is a need to investigate the impacts of the COVID-19 pandemic on electricity prices (EP). In this paper, a set of six economic factors that are affected by COVID-19 and affect EP are considered. These factors were fed into a functional link artificial neural network (FLANN) to model the relationships between them and the EP. An empirical equation was formulated to help decision makers and strategic developers in the electricity markets come up with more appropriate plans. Italy, the Czech Republic, and China were used as case studies in this research. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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