Making and evaluating point forecasts
T Gneiting - Journal of the American Statistical Association, 2011 - Taylor & Francis
Typically, point forecasting methods are compared and assessed by means of an error
measure or scoring function, with the absolute error and the squared error being key …
measure or scoring function, with the absolute error and the squared error being key …
Evaluation of spatio-temporal forecasting methods in various smart city applications
A Tascikaraoglu - Renewable and Sustainable Energy Reviews, 2018 - Elsevier
Together with the increasing population and urbanization, cities have started to face
challenges that hinder their socio-economic and sustainable development. The concept of …
challenges that hinder their socio-economic and sustainable development. The concept of …
Very-short-term probabilistic wind power forecasts by sparse vector autoregression
J Dowell, P Pinson - IEEE Transactions on Smart Grid, 2015 - ieeexplore.ieee.org
A spatio-temporal method for producing very-short-term parametric probabilistic wind power
forecasts at a large number of locations is presented. Smart grids containing tens, or …
forecasts at a large number of locations is presented. Smart grids containing tens, or …
Improved deep mixture density network for regional wind power probabilistic forecasting
H Zhang, Y Liu, J Yan, S Han, L Li… - IEEE Transactions on …, 2020 - ieeexplore.ieee.org
Unsteady motion of the atmosphere incurs nonlinear and spatiotemporally coupled
uncertainties in the wind power prediction (WPP) of multiple wind farms. This brings both …
uncertainties in the wind power prediction (WPP) of multiple wind farms. This brings both …
Wind energy: Forecasting challenges for its operational management
P Pinson - 2013 - projecteuclid.org
Renewable energy sources, especially wind energy, are to play a larger role in providing
electricity to industrial and domestic consumers. This is already the case today for a number …
electricity to industrial and domestic consumers. This is already the case today for a number …
Wind power prediction using hybrid autoregressive fractionally integrated moving average and least square support vector machine
Precise prediction of wind power can not only conduct wind turbine's operation, but also
reduce the impact on power systems when wind energy is injected into the grid. A hybrid …
reduce the impact on power systems when wind energy is injected into the grid. A hybrid …
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 …
Learning (DL) and in particular, Recurrent Neural Networks (RNNs). Motivated by recent …
Short-term spatio-temporal wind power forecast in robust look-ahead power system dispatch
We propose a novel statistical wind power forecast framework, which leverages the spatio-
temporal correlation in wind speed and direction data among geographically dispersed wind …
temporal correlation in wind speed and direction data among geographically dispersed wind …
[图书][B] Data science for wind energy
Y Ding - 2019 - taylorfrancis.com
Data Science for Wind Energy provides an in-depth discussion on how data science
methods can improve decision making for wind energy applications, near-ground wind field …
methods can improve decision making for wind energy applications, near-ground wind field …
Exploiting sparsity of interconnections in spatio-temporal wind speed forecasting using Wavelet Transform
Integration of renewable energy resources into the power grid is essential in achieving the
envisioned sustainable energy future. Stochasticity and intermittency characteristics of …
envisioned sustainable energy future. Stochasticity and intermittency characteristics of …