Componentnet: Processing U- and V-components for spatio-Temporal wind speed forecasting
| Autor: | Bruno Quaresma Bastos, Fernando Luiz Cyrino Oliveira, Ruy Luiz Milidiú |
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| Rok vydání: | 2021 |
| Předmět: |
Computer science
business.industry 020209 energy Distributed computing 020208 electrical & electronic engineering Energy Engineering and Power Technology Context (language use) 02 engineering and technology Convolutional neural network Wind speed Renewable energy Electric power system 0202 electrical engineering electronic engineering information engineering Electrical and Electronic Engineering Architecture Operational costs business Mixing (physics) |
| Zdroj: | Electric Power Systems Research. 192:106922 |
| ISSN: | 0378-7796 |
| Popis: | The increasing presence of intermittent renewables in modern power systems motivates the development of methods for renewables forecasting. More accurate forecasts may implicate less operational costs for power systems. In this context, this paper proposes a family of architectures based on fully convolutional neural networks for wind speed prediction, the ComPonentNet (CPNet) family. The CPNet produces multi-site spatio-temporal forecasting for phenomena which may be decomposed into multiple components (e.g., wind, which may be decomposed into u- and v-wind). The CPNet family includes three architectures - the core CPNet, the fully-fused CPNet and the bottom-fused CPNet. Each architecture processes the components of the phenomenon in a different manner - in separate branches of convolutional operations, in the same branch, or mixing separate and joint branches. This paper investigates the performance of each CPNet architecture in forecasting multi-site spatio-temporal wind speed. Moreover, the CPNet framework is compared against the U-Net architecture. The results indicate that the proposed framework is promising, and that splitting the processing of wind components may be beneficial to spatio-temporal forecasting, with results that outperform the U-Net. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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