Very Short-Term Wind Speed Forecasting Using Spatio-Temporal Lazy Learning

نویسندگان

  • Annalisa Appice
  • Sonja Pravilovic
  • Antonietta Lanza
  • Donato Malerba
چکیده

A wind speed forecast corresponds to an estimate of the upcoming production of a wind farm. The paper illustrates a variant of the Nearest Neighbor algorithm that yields wind speed forecasts, with a fast time resolution, for a (very) short time horizon. The proposed algorithm allows us to monitor a grid of wind farms, which collaborate by sharing information (i.e. wind speed measurements). It accounts for both spatial and temporal correlation of shared information. Experiments show that the presented algorithm is able to determine more accurate forecasts than a state-of-art statistical algorithm, namely auto. ARIMA.

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Improved Spatio-Temporal Linear Models for Very Short-Term Wind Speed Forecasting

In this paper, the spatio-temporal (multi-channel) linear models, which use temporal and the neighbouring wind speed measurements around the target location, for the best short-term wind speed forecasting are investigated. Multi-channel autoregressive moving average (MARMA) models are formulated in matrix form and efficient linear prediction coefficient estimation techniques are first used and ...

متن کامل

Deep Forecast: Deep Learning-based Spatio-Temporal Forecasting

The paper presents a spatio-temporal wind speed forecasting algorithm using Deep Learning (DL) and in particular, Recurrent Neural Networks (RNNs). Motivated by recent advances in renewable energy integration and smart grids, we apply our proposed algorithm for wind speed forecasting. Renewable energy resources (wind and solar) are random in nature and, thus, their integration is facilitated wi...

متن کامل

Spatio-temporal Prediction of Wind Fields PhD Thesis

Short-term wind and wind power forecasts are required for the reliable and economic operation of power systems with significant wind power penetration. This thesis presents new statistical techniques for producing forecasts at multiple locations using spatiotemporal information. Forecast horizons of up to 6 hours are considered for which statistical methods outperform physical models in general...

متن کامل

Short-Term Traffic Forecasting: Modeling and Learning Spatio-Temporal Relations in Transportation Networks Using Graph Neural Networks

Short Term Tra c Forecasting: Modeling and Learning Spatio Temporal Relations in Transportation Networks Using Graph Neural Networks

متن کامل

Short and Mid-Term Wind Power Plants Forecasting With ANN

In recent years, wind energy has a remarkable growth in the world, but one of the important problems of power generated from wind is its uncertainty and corresponding power. For solving this problem, some approaches have been presented. Recently, the Artificial Neural Networks (ANN) as a heuristic method has more applications for this propose. In this paper, short-term (1 hour) and mid-term (24...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 2015