byuflowlab / FLOWFarm.jl

Wind farm tools based in Julia
MIT License
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consider how to achieve performance improvements when the speed distribution is the same in all directions #27

Open jaredthomas68 opened 4 years ago

jaredthomas68 commented 4 years ago

Excerpt from email from Erik Q.

(first some comments by Jared T.)

Right now our framework is built on a "state" concept, where each wind speed and wind direction represent a flow state (could also make combinations of various other wind resource characteristics).

(response from Erik Q.) My feeling is that if you have a Cartesian product state space, using ‘iterated expectation’ (which is what I described) should remain possible. Any joint probability distribution is very often provided decomposed in a marginal and conditionals (in what we looked at: marginal for direction and conditionals for wind speed on direction) and this decomposition determines the efficient calculation of the expectation. So any set of characteristics and particular decomposition of the joint distribution gives rise to a single calculation approach. (Am I making sense?)

If you don't have a Cartesian product space (e.g., different speeds per direction), this breaks down and working with the joint directly may then be more efficient than filling up the holes to create a Cartesian product structure.