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Model predictive control considering forecast deviation in local districts
- Source :
- 2019 16th International Conference on the European Energy Market (EEM).
- Publication Year :
- 2019
- Publisher :
- IEEE, 2019.
-
Abstract
- The state of the art in science is to take into account forecast uncertainties in optimization either in the form of variant calculations or in stochastic optimization models. This paper presents an alternative approach for the consideration of forecast uncertainties within model predictive control. The approach defines a guaranteed flexibility range, which is responsible for the compensation of expected forecast errors. It is proven that the risk can be reduced with the help of quantiles based flexibility bands. To implement the approach, a controllable resource is required in the energy system. In this case it is an energy storage device. The result shows that with the help of the new approach it is possible to minimize the forecast uncertainties in the local energy system and thus reduce the impact on the overall system. With this algorithmic approach, the planning reliability in the overall energy system is to be increased.
- Subjects :
- Flexibility (engineering)
Mathematical optimization
010504 meteorology & atmospheric sciences
Computer science
0208 environmental biotechnology
02 engineering and technology
01 natural sciences
020801 environmental engineering
Compensation (engineering)
Model predictive control
Resource (project management)
Range (statistics)
Stochastic optimization
Reliability (statistics)
0105 earth and related environmental sciences
Quantile
Subjects
Details
- Database :
- OpenAIRE
- Journal :
- 2019 16th International Conference on the European Energy Market (EEM)
- Accession number :
- edsair.doi...........641a3c25801a66a48f84786ecba35b8d