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Line closure distribution factor-PSS/E

asked 2018-10-30 03:17:36 -0500

Eddiewen gravatar image

Does anyone know PSS/E can calculate Line closure distribution factor(LCDF) or Line outage distribution factor(LODF)? or how can use OTDF to transfer? Thanks!

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answered 2018-10-30 15:53:50 -0500

knucklehead gravatar image

I have found that looping through the contingencies in the .acc file, then looping through the branches for each contingency, then comparing to the "BASE CASE" contingency is the best approach. if you find that one of the distribution factors satisfies some criteria, then you can do what you like with the branch, outage, flow, df, information. (version 34) Here is a snippet that effectively does this.

accobject = arrbox.accc_pp.CONTINGENCY_PP(n1accfnames[j])
accsummary = accobject.summary()
conlabels = accsummary.colabel
branches = list(accsummary.melement)
buses = list(accsummary.mvbuslabel)

# -- GET N-0 RESULTS ----------------------------------------------------------------------
n0results = accobject.solution('BASE CASE')
n0volts = n0results.volts
n0flows = list(n0results.ampflow)

# -----------------------------------------------------------------------------------------
# -- CHECK N-1 RESULTS FOR IMPACTED BUSES AND BRANCHES ------------------------------------
# -----------------------------------------------------------------------------------------
for prilabel in conlabels[1:]:
    results = accobject.solution(prilabel)
    pridesc = list(results.codesc)
    n1volts = results.volts
    n1flows = list(results.ampflow)

    if not results.cnvflag: continue
    for f in range(len(branches)):
        getcon = False
        if n1flows[f] == 0.0:
        df = abs((n1flows[f] - n0flows[f]) / n0flows[f])
        if df > screenDF:
            getcon = True
        if not getcon:
            getcon = True in [abs(n1volts[v] - n0volts[v]) > screenVF for v in range(len(buses))]
        if getcon:   ....................
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answered 2018-10-30 09:24:01 -0500

jconto gravatar image

A good discussion about these linear factors can be found at ""

does someone have a related python code, besides the "" posted at the example folder?

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Asked: 2018-10-30 03:17:36 -0500

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Last updated: Oct 30 '18