First time here? We are a friendly community of Power Systems Engineers. Check out the FAQ!

PSSE with dask/Python for large datasets in contingency results

Divya
1 ●3 ●4 ●3

Hi,

I am trying to extract the results of acc files using pssarrays.acccsummary and pssarrays.acccsolution. I have more than 80,000 contingencies. When I try to read the result of each contingency using for loop in python, I get MemoryError after reading 8,000 contingencies. The size of my .acc file is 2GB

Since I am working with large datasets, will Dask be helpful for this issue? Did anyone face a similar issue?

Any suggestion is greatly appreciated. Thanks in advance

add a comment

1 answer

Sort by » oldest newest most voted

answered Sep 10 '0

jconto
2756 ●10 ●30 ●41

Divide an Conquer.

Contingencies have specific features for testing the electric network. Select contingencies are defined per geographical regions (sometimes bus numbering can be used as proxy for geographical location), or per areas, zones in network model, per type (P1, P2, .. P7 in NERC TPL definition or equivalent definitions), per structure (single element in contingency, double elements,...) .

It would be better to create the contingency sets definition before running ACCC. Multiple ACCC would be created but much smaller in size, and processing them may be faster if done in parallel.

link

add a comment

Question Tools

1 follower

Stats

Asked: Sep 10 '0

Seen: 1,287 times

Last updated: Sep 10 '20

PSSE with dask/Python for large datasets in contingency results

1 answer

Your Answer

Question Tools

Stats

Related questions