A Case Study on Experiment Site Selection for PV Energy Generation Forecast
| Autor: | Ping Wang, Lin Wen Hui, Huang Yu Hsiang, Lin Hsiao Chung, Tseng Sheng Yuan |
|---|---|
| Rok vydání: | 2020 |
| Předmět: |
Wind power
business.industry Computer science 05 social sciences Scheduling (production processes) Site selection Software development 02 engineering and technology Wind direction Wind speed Reliability engineering Renewable energy Electricity generation 020204 information systems 0502 economics and business 0202 electrical engineering electronic engineering information engineering 050211 marketing business |
| Zdroj: | ICS |
| Popis: | Renewable energy from solar and wind energy systems is highly dynamic depending on different meteorological conditions. This paper focuses on developing a timing-intensive meteorological data management system (MDMS) for selection of a suitable experiment site of PV energy power forecasts. Intuitively, the factors of affecting renewable-energy power forecasts include solar radiation, wind speed, wind direction, temperature, and humidity. In practice, it needs to create meteorological records for every 5-10 minute collected from multiple data sources as a basis of renewable power forecasts using deep learning networks (DLNs). To meet evolving mission needs of project, the MDMS design incorporates MVC architecture and Laravel scheduling tool to software development that allows developers effectively perform program maintenance. Finally, a better experiment site of PV energy forecasts is decided using the MDMS by comparing the prediction errors of between power generation output vs. solar irradiation of each inverter in each PV experiment site. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|