Matches in SemOpenAlex for { <https://semopenalex.org/work/W4381569696> ?p ?o ?g. }
Showing items 1 to 67 of
67
with 100 items per page.
- W4381569696 endingPage "38" @default.
- W4381569696 startingPage "32" @default.
- W4381569696 abstract "New power plants are included in the grid continuously to meet the increasing need for electrical energy. More than half of the power plants that have been newly added to the grid since 2015 are renewable energy power plants. As of 2022, the total installed renewable energy power increased by 11% compared to the previous year and reached 3146 GW. This increase will likely accelerate with the widespread use of electric vehicles. Wind energy is one of the renewable energy types with the highest installed capacity among renewable energy sources. Due to the nature of the wind, fluctuations in production cause adverse effects on the management of the electricity grid. Therefore, the forecast of renewable energy generation is very important for managing the electricity grid. This paper presents a wind energy forecast for the next 24 hours using data from a wind farm in Turkey. The forecast model consists of two stages. In the first stage, numerical weather predictions (NWP) have improved by using Artificial Neural Networks (ANN) and Artificial Bee Colony (ABC) methods. In the second stage, estimation is carried out by the ANFIS method. Improving the NWP using past NWP data and actual wind speed data increases the power forecast accuracy. The forecast results are compared with the forecasts made by the wind power plant (WPP). The proposed model has forecasted wind power with NRMSE 16.73%, and it has given more successful results than the forecast made by the power plant." @default.
- W4381569696 created "2023-06-22" @default.
- W4381569696 creator A5008875371 @default.
- W4381569696 creator A5062443164 @default.
- W4381569696 date "2023-05-30" @default.
- W4381569696 modified "2023-10-07" @default.
- W4381569696 title "Day-Ahead Wind Power Forecasting Using Numerical Weather Prediction" @default.
- W4381569696 doi "https://doi.org/10.33422/icarste.v1i1.42" @default.
- W4381569696 hasPublicationYear "2023" @default.
- W4381569696 type Work @default.
- W4381569696 citedByCount "0" @default.
- W4381569696 crossrefType "journal-article" @default.
- W4381569696 hasAuthorship W4381569696A5008875371 @default.
- W4381569696 hasAuthorship W4381569696A5062443164 @default.
- W4381569696 hasBestOaLocation W43815696961 @default.
- W4381569696 hasConcept C119599485 @default.
- W4381569696 hasConcept C121332964 @default.
- W4381569696 hasConcept C127413603 @default.
- W4381569696 hasConcept C147947694 @default.
- W4381569696 hasConcept C153294291 @default.
- W4381569696 hasConcept C161067210 @default.
- W4381569696 hasConcept C163258240 @default.
- W4381569696 hasConcept C188573790 @default.
- W4381569696 hasConcept C205649164 @default.
- W4381569696 hasConcept C206658404 @default.
- W4381569696 hasConcept C2781084341 @default.
- W4381569696 hasConcept C39432304 @default.
- W4381569696 hasConcept C423512 @default.
- W4381569696 hasConcept C62520636 @default.
- W4381569696 hasConcept C78600449 @default.
- W4381569696 hasConcept C89227174 @default.
- W4381569696 hasConceptScore W4381569696C119599485 @default.
- W4381569696 hasConceptScore W4381569696C121332964 @default.
- W4381569696 hasConceptScore W4381569696C127413603 @default.
- W4381569696 hasConceptScore W4381569696C147947694 @default.
- W4381569696 hasConceptScore W4381569696C153294291 @default.
- W4381569696 hasConceptScore W4381569696C161067210 @default.
- W4381569696 hasConceptScore W4381569696C163258240 @default.
- W4381569696 hasConceptScore W4381569696C188573790 @default.
- W4381569696 hasConceptScore W4381569696C205649164 @default.
- W4381569696 hasConceptScore W4381569696C206658404 @default.
- W4381569696 hasConceptScore W4381569696C2781084341 @default.
- W4381569696 hasConceptScore W4381569696C39432304 @default.
- W4381569696 hasConceptScore W4381569696C423512 @default.
- W4381569696 hasConceptScore W4381569696C62520636 @default.
- W4381569696 hasConceptScore W4381569696C78600449 @default.
- W4381569696 hasConceptScore W4381569696C89227174 @default.
- W4381569696 hasIssue "1" @default.
- W4381569696 hasLocation W43815696961 @default.
- W4381569696 hasOpenAccess W4381569696 @default.
- W4381569696 hasPrimaryLocation W43815696961 @default.
- W4381569696 hasRelatedWork W2370333049 @default.
- W4381569696 hasRelatedWork W2383707816 @default.
- W4381569696 hasRelatedWork W2528649053 @default.
- W4381569696 hasRelatedWork W2770854060 @default.
- W4381569696 hasRelatedWork W3033688541 @default.
- W4381569696 hasRelatedWork W3137479036 @default.
- W4381569696 hasRelatedWork W4205282669 @default.
- W4381569696 hasRelatedWork W4365145658 @default.
- W4381569696 hasRelatedWork W4379137528 @default.
- W4381569696 hasRelatedWork W4379160479 @default.
- W4381569696 hasVolume "1" @default.
- W4381569696 isParatext "false" @default.
- W4381569696 isRetracted "false" @default.
- W4381569696 workType "article" @default.