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Multivariate probabilistic forecasting and its performance's impacts on long-term dispatch of hydro-wind hybrid systems.
- Source :
-
Applied Energy . Feb2021, Vol. 283, pN.PAG-N.PAG. 1p. - Publication Year :
- 2021
-
Abstract
- • A novel multivariate probabilistic forecasting method. • The impacts of probabilistic forecasting's performance on hydro-wind dispatch. • Appropriate trade-off between running time and benefit. • Case study that optimizes the long-term optimal dispatch scheme. There are two difficulties in long-term optimal dispatch of hydro-wind hybrid systems. First, monthly runoffs and wind speeds have the dynamic characteristics such as variability, instability, seasonality, heteroscedasticity, linear and nonlinear dynamic correlations. Second, hydro-wind hybrid systems have highly non-convex nonlinear constraints. To overcome the problem, this research develops a novel X-12 seasonal adjustment, vector autoregressive integrated moving average (VARIMA), component generalized autoregressive conditional heteroscedasticity (C-GARCH) and dynamic copula mixed model to estimate the joint probability distribution of runoffs and wind speeds. And then, this paper builds a multistage stochastic mixed-integer linear programming (MILP) with the help of several linearization methods. Finally, the paper compares several probabilistic forecasting models' performances and analyzes their impacts on the dispatch of the hydro-wind hybrid system under different hydrological years. A hydro-wind hybrid system in southwest China is taken as an example. The case study leads to the following conclusions: 1) the more sufficient to capture the dynamic characteristics of variables, the higher benefit will be; 2) it is necessary to increase the scale of scenario tree to reduce the electricity shortfall during the dry year; 3) serious spilled water can be caused by insufficient interregional transmission capacity under the wet year and it is the most appropriate to expand the capacity to 8000 MW; 4) the model proposed in this paper can increase the economic benefit by 0.466 × 10 9 C N Y , 1.775 × 10 9 C N Y and 0.400 × 10 9 C N Y during the normal, dry and wet year, respectively. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 03062619
- Volume :
- 283
- Database :
- Academic Search Index
- Journal :
- Applied Energy
- Publication Type :
- Academic Journal
- Accession number :
- 148166459
- Full Text :
- https://doi.org/10.1016/j.apenergy.2020.116243