The report describes machine learning algorithms: to obtain appropriate parameters for the model (task 3.3.2), to formulate a new model (task 3.3.5). A methodology regarding the choice of the proper machine learning algorithm is also given. Amendment 2016: The shift is in order to align D3.5 with task 3.3.2. The alignment is necessary since results of task 3.3.2 will become part of D3.5. The amendment does not influence any other tasks or deliverables.
Three typical locations for CSP power plants, but different with respect to their weather characteristics are chosen – the report provides the site assessment results and methodology.
The aim of this deliverable is provide all those tools that the project needs to achieve fluid communication, both among PreFlexMS partners and to potential stakeholders, and as well as a high impact of its results. So, it includes the design of the project image aspects, like logos, templates, posters or videos and the project web site. This web site will serve to vertebrate the communication and dissemination flow, to share internal information and to link the project with partners and external interests.
Describe set-up and model characteristics of both deterministic and probabilistic weather forecasting at AEMET.
Describe method and results on the inclusion of aerosol forecasts.
Projections in market pricing scenarios likely to occur in the most important markets where large scale CSP would be deployed taking into account incentives or demands by local grid operators. These are displayed as electricity prices vs time of day for a variety of markets.
The report describes formal knowledge representation of the performance model. It provides its capabilities and expressive power. It includes parametrization and further extension guidelines. Amendment 2016: The shift is in order to align D3.4 with task 3.3.1. The alignment is necessary since results of task 3.3.1 will become part of D3.4. The amendment does not influence any other tasks or deliverables.
Describe set-up and characteristics of the post-processing for both deterministic and probabilistic weather forecasting at CENER.
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