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fix whitespace
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@dpinney
dpinney committed Jan 2, 2024
1 parent 83ebdaf commit 522f2bc
Showing 1 changed file with 121 additions and 121 deletions.
242 changes: 121 additions & 121 deletions omf/models/restoration.py
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Original file line number Diff line number Diff line change
Expand Up @@ -197,12 +197,12 @@ def customerOutageStats(customerOutageData, outageCost):

# print business information and estimated customer outage costs
try:
customerOutageHtml = customerOutageStats(
customerOutageData = customerOutageData,
outageCost = outageCost)
customerOutageHtml = customerOutageStats(
customerOutageData = customerOutageData,
outageCost = outageCost)
except:
customerOutageHtml = ''
#HACKCOBB: work aroun.
customerOutageHtml = ''
#HACKCOBB: work aroun.
with open(pJoin(workDir, 'customerOutageTable.html'), 'w') as customerOutageFile:
customerOutageFile.write(customerOutageHtml)
return customerOutageHtml
Expand Down Expand Up @@ -731,19 +731,19 @@ def coordStrFormatter(coordString):
json.dump(feederMap, outFile, indent=4)
# Generate customer outage outputs
try:
customerOutageData = pd.read_csv(pathToCsv)
customerOutageData = pd.read_csv(pathToCsv)
except:
deviceTimeline = data["Device action timeline"]
loadsShed = []
for line in deviceTimeline:
loadsShed.append(line["Shedded loads"])
customerOutageData = pd.DataFrame(columns=['Customer Name','Season','Business Type','Load Name'])
for elementDict in tree.values():
if elementDict['object'] == 'load' and float(elementDict['kw'])>.1 and elementDict['name'] in loadsShed[0]:
loadName = elementDict['name']
avgLoad = float(elementDict['kw'])/2.5
busType = 'residential'*(avgLoad<=10) + 'retail'*(avgLoad>10)*(avgLoad<=20) + 'agriculture'*(avgLoad>20)*(avgLoad<=39) + 'public'*(avgLoad>39)*(avgLoad<=50) + 'services'*(avgLoad>50)*(avgLoad<=100) + 'manufacturing'*(avgLoad>100)
customerOutageData.loc[len(customerOutageData.index)] =[loadName,'summer',busType,loadName]
deviceTimeline = data["Device action timeline"]
loadsShed = []
for line in deviceTimeline:
loadsShed.append(line["Shedded loads"])
customerOutageData = pd.DataFrame(columns=['Customer Name','Season','Business Type','Load Name'])
for elementDict in tree.values():
if elementDict['object'] == 'load' and float(elementDict['kw'])>.1 and elementDict['name'] in loadsShed[0]:
loadName = elementDict['name']
avgLoad = float(elementDict['kw'])/2.5
busType = 'residential'*(avgLoad<=10) + 'retail'*(avgLoad>10)*(avgLoad<=20) + 'agriculture'*(avgLoad>20)*(avgLoad<=39) + 'public'*(avgLoad>39)*(avgLoad<=50) + 'services'*(avgLoad>50)*(avgLoad<=100) + 'manufacturing'*(avgLoad>100)
customerOutageData.loc[len(customerOutageData.index)] =[loadName,'summer',busType,loadName]
numberRows = max(math.ceil(customerOutageData.shape[0]/2),1)
fig, axs = plt.subplots(numberRows, 2)
row = 0
Expand All @@ -759,48 +759,48 @@ def coordStrFormatter(coordString):
loadShapeMeanMultiplier = {}
loadShapeMeanActual = {}
for dssLine in dssTree:
if 'object' in dssLine and dssLine['object'].split('.')[0] == 'loadshape':
shape = dssLine['mult'].replace('[','').replace('(','').replace(']','').replace(')','').split(',')
shape = [float(y) for y in shape]
if 'useactual' in dssLine and dssLine['useactual'] == 'yes': loadShapeMeanActual[dssLine['object'].split('.')[1]] = np.mean(shape)
else: loadShapeMeanMultiplier[dssLine['object'].split('.')[1]] = np.mean(shape)/np.max(shape)
if 'object' in dssLine and dssLine['object'].split('.')[0] == 'loadshape':
shape = dssLine['mult'].replace('[','').replace('(','').replace(']','').replace(')','').split(',')
shape = [float(y) for y in shape]
if 'useactual' in dssLine and dssLine['useactual'] == 'yes': loadShapeMeanActual[dssLine['object'].split('.')[1]] = np.mean(shape)
else: loadShapeMeanMultiplier[dssLine['object'].split('.')[1]] = np.mean(shape)/np.max(shape)
while row < customerOutageData.shape[0]:
customerName = str(customerOutageData.loc[row, 'Customer Name'])
loadName = str(customerOutageData.loc[row, 'Load Name'])
businessType = str(customerOutageData.loc[row, 'Business Type'])
duration = str(0)
averagekWperhr = str(0)
for elementDict in dssTree:
if 'object' in elementDict and elementDict['object'].split('.')[0] == 'load' and elementDict['object'].split('.')[1] == loadName:
if 'daily' in elementDict: averagekWperhr = float(loadShapeMeanMultiplier.get(elementDict['daily'],0)) * float(elementDict['kw']) + float(loadShapeMeanActual.get(elementDict['daily'],0))
else: averagekWperhr = float(elementDict['kw'])/2
duration = str(cumulativeLoadsShed.count(loadName) * stepSize)
if float(duration) >= .1 and float(averagekWperhr) >= .1:
durationColumn.append(duration)
avgkWColumn.append(float(averagekWperhr))
season = str(customerOutageData.loc[row, 'Season'])
customerOutageCost, kWperhrEstimate, times, localMax = customerCost1(duration, season, averagekWperhr, businessType)
average_lost_kwh.append(float(averagekWperhr))
outageCost.append(customerOutageCost)
outageCostsByType[businessType].append(customerOutageCost)
if localMax > globalMax:
globalMax = localMax
# creating series
timesSeries = pd.Series(times)
kWperhrSeries = pd.Series(kWperhrEstimate)
trace = py.graph_objs.Scatter(
x = timesSeries,
y = kWperhrSeries,
name = customerName,
hoverlabel = dict(namelength = -1),
hovertemplate =
'<b>Duration</b>: %{x} h<br>' +
'<b>Cost</b>: $%{y:.2f}')
fig.add_trace(trace)
row += 1
else:
customerOutageData = customerOutageData.drop(index=row)
customerOutageData = customerOutageData.reset_index(drop=True)
customerName = str(customerOutageData.loc[row, 'Customer Name'])
loadName = str(customerOutageData.loc[row, 'Load Name'])
businessType = str(customerOutageData.loc[row, 'Business Type'])
duration = str(0)
averagekWperhr = str(0)
for elementDict in dssTree:
if 'object' in elementDict and elementDict['object'].split('.')[0] == 'load' and elementDict['object'].split('.')[1] == loadName:
if 'daily' in elementDict: averagekWperhr = float(loadShapeMeanMultiplier.get(elementDict['daily'],0)) * float(elementDict['kw']) + float(loadShapeMeanActual.get(elementDict['daily'],0))
else: averagekWperhr = float(elementDict['kw'])/2
duration = str(cumulativeLoadsShed.count(loadName) * stepSize)
if float(duration) >= .1 and float(averagekWperhr) >= .1:
durationColumn.append(duration)
avgkWColumn.append(float(averagekWperhr))
season = str(customerOutageData.loc[row, 'Season'])
customerOutageCost, kWperhrEstimate, times, localMax = customerCost1(duration, season, averagekWperhr, businessType)
average_lost_kwh.append(float(averagekWperhr))
outageCost.append(customerOutageCost)
outageCostsByType[businessType].append(customerOutageCost)
if localMax > globalMax:
globalMax = localMax
# creating series
timesSeries = pd.Series(times)
kWperhrSeries = pd.Series(kWperhrEstimate)
trace = py.graph_objs.Scatter(
x = timesSeries,
y = kWperhrSeries,
name = customerName,
hoverlabel = dict(namelength = -1),
hovertemplate =
'<b>Duration</b>: %{x} h<br>' +
'<b>Cost</b>: $%{y:.2f}')
fig.add_trace(trace)
row += 1
else:
customerOutageData = customerOutageData.drop(index=row)
customerOutageData = customerOutageData.reset_index(drop=True)
customerOutageData.insert(1, "Duration", durationColumn, True)
customerOutageData.insert(3, "Average kW/hr", avgkWColumn, True)
durations = customerOutageData.get('Duration',['0'])
Expand Down Expand Up @@ -829,12 +829,12 @@ def coordStrFormatter(coordString):
busColors = {'residential':'#0000ff', 'manufacturing':'#ff0000', 'mining':'#708090', 'construction':'#ff8c00', 'agriculture':'#008000', 'finance':'#d6b600', 'retail':'#ff69b4', 'services':'#191970', 'utilities':'#8b4513', 'public':'#9932cc'}
custHist = go.Figure()
# custHist.add_trace(go.Histogram(
# x=outageCost,
# xbins=dict(
# start=minCustomerCost,
# end=maxCustomerCost+binSize,
# size=binSize
# )
# x=outageCost,
# xbins=dict(
# start=minCustomerCost,
# end=maxCustomerCost+binSize,
# size=binSize
# )
# ))
for busType in businessTypes:
custHist.add_trace(go.Histogram(
Expand All @@ -856,12 +856,12 @@ def coordStrFormatter(coordString):
)
meanCustomerCostStr = "Mean Outage Cost: $"+"{:.2f}".format(meanCustomerCost)
# custHist.add_vline(
# x=meanCustomerCost,
# line_width=3,
# line_dash="dash",
# line_color="black",
# annotation_text=meanCustomerCostStr,
# annotation_position="top right"
# x=meanCustomerCost,
# line_width=3,
# line_dash="dash",
# line_color="black",
# annotation_text=meanCustomerCostStr,
# annotation_position="top right"
# )
custHist.add_shape(
type="line",
Expand Down Expand Up @@ -898,56 +898,56 @@ def coordStrFormatter(coordString):
return {'utilityOutageHtml': utilityOutageHtml, 'customerOutageHtml': customerOutageHtml, 'timelineStatsHtml': timelineStatsHtml, 'gens': gens, 'loads': loads, 'volts': volts, 'fig': fig, 'customerOutageCost': customerOutageCost, 'numTimeSteps': numTimeSteps, 'stepSize': stepSize, 'custHist': custHist}

def buildCustomEvents(eventsCSV='', feeder='', customEvents='customEvents.json', defaultDispatchable = 'true'):
def outageSwitchState(outList): return ('open'*(outList[3] == 'closed') + 'closed'*(outList[3]=='open'))
def eventJson(dispatchable, state, timestep, affected_asset):
return {
"event_data": {
"status": 1,
"dispatchable": dispatchable,
"type": "breaker",
"state": state
},
"timestep": timestep,
"affected_asset": ("line." + affected_asset),
"event_type": "switch"
}
if eventsCSV == '': # Find largest switch, flip it and set to non-dispatchable at timestep 1.
with open(feeder, 'a') as f:
f.write('Export Currents')
with open(feeder, 'r') as f:
f.read()
elif ',' in eventsCSV:
outageReader = csv.reader(io.StringIO(eventsCSV))
else:
outageReader = csv.reader(open(eventsCSV))
if feeder.endswith('.omd'):
with open(feeder) as omdFile:
tree = json.load(omdFile)['tree']
niceDss = dssConvert.evilGldTreeToDssTree(tree)
dssConvert.treeToDss(niceDss, 'circuitOmfCompatible.dss')
dssTree = dssConvert.dssToTree('circuitOmfCompatible.dss')
else: return('Error: Feeder must be an OMD file.')
outageAssets = [] # formerly row[0] for row in outageReader
customEventList = []
for row in outageReader:
outageAssets.append(row[0])
try:
customEventList.append(eventJson('false',outageSwitchState(row),int(row[1]),row[0]))
if int(row[2])>0:
customEventList.append(eventJson(row[4],row[3],int(row[2]),row[0]))
except: pass
unaffectedOpenAssets = [dssLine['object'].split('.')[1] for dssLine in dssTree if dssLine['!CMD'] == 'open']
unaffectedClosedAssets = [dssLine['object'].split('.')[1] for dssLine in dssTree if dssLine.get('!CMD') == 'new' \
and dssLine['object'].split('.')[0] == 'line' \
and 'switch' in [key for key in dssLine] \
# and dssLine['switch'] == 'y'] # \
and (dssLine['object'].split('.')[1] not in (unaffectedOpenAssets + outageAssets))]
customEventList += [eventJson(defaultDispatchable,'open',1,asset) for asset in unaffectedOpenAssets]
customEventList += [eventJson(defaultDispatchable,'closed',1,asset) for asset in unaffectedClosedAssets]
customEventList += [eventJson('false',outageSwitchState(row),int(row[1]),row[0]) for row in outageReader]
customEventList += [eventJson(row.get('dispatchable'),row.get('defaultState',int(row.get('timestep'))),row.get('asset')) for row in outageReader if int(row[2])>0]
with open(customEvents,'w') as eventsFile:
json.dump(customEventList, eventsFile)
def outageSwitchState(outList): return ('open'*(outList[3] == 'closed') + 'closed'*(outList[3]=='open'))
def eventJson(dispatchable, state, timestep, affected_asset):
return {
"event_data": {
"status": 1,
"dispatchable": dispatchable,
"type": "breaker",
"state": state
},
"timestep": timestep,
"affected_asset": ("line." + affected_asset),
"event_type": "switch"
}
if eventsCSV == '': # Find largest switch, flip it and set to non-dispatchable at timestep 1.
with open(feeder, 'a') as f:
f.write('Export Currents')
with open(feeder, 'r') as f:
f.read()
elif ',' in eventsCSV:
outageReader = csv.reader(io.StringIO(eventsCSV))
else:
outageReader = csv.reader(open(eventsCSV))
if feeder.endswith('.omd'):
with open(feeder) as omdFile:
tree = json.load(omdFile)['tree']
niceDss = dssConvert.evilGldTreeToDssTree(tree)
dssConvert.treeToDss(niceDss, 'circuitOmfCompatible.dss')
dssTree = dssConvert.dssToTree('circuitOmfCompatible.dss')
else: return('Error: Feeder must be an OMD file.')
outageAssets = [] # formerly row[0] for row in outageReader
customEventList = []
for row in outageReader:
outageAssets.append(row[0])
try:
customEventList.append(eventJson('false',outageSwitchState(row),int(row[1]),row[0]))
if int(row[2])>0:
customEventList.append(eventJson(row[4],row[3],int(row[2]),row[0]))
except: pass
unaffectedOpenAssets = [dssLine['object'].split('.')[1] for dssLine in dssTree if dssLine['!CMD'] == 'open']
unaffectedClosedAssets = [dssLine['object'].split('.')[1] for dssLine in dssTree if dssLine.get('!CMD') == 'new' \
and dssLine['object'].split('.')[0] == 'line' \
and 'switch' in [key for key in dssLine] \
# and dssLine['switch'] == 'y'] # \
and (dssLine['object'].split('.')[1] not in (unaffectedOpenAssets + outageAssets))]
customEventList += [eventJson(defaultDispatchable,'open',1,asset) for asset in unaffectedOpenAssets]
customEventList += [eventJson(defaultDispatchable,'closed',1,asset) for asset in unaffectedClosedAssets]
customEventList += [eventJson('false',outageSwitchState(row),int(row[1]),row[0]) for row in outageReader]
customEventList += [eventJson(row.get('dispatchable'),row.get('defaultState',int(row.get('timestep'))),row.get('asset')) for row in outageReader if int(row[2])>0]
with open(customEvents,'w') as eventsFile:
json.dump(customEventList, eventsFile)

def work(modelDir, inputDict):
# Copy specific climate data into model directory
Expand Down Expand Up @@ -1064,7 +1064,7 @@ def work(modelDir, inputDict):
outData['geoDict'] = inFile.read().decode()
# Image outputs.
# with open(pJoin(modelDir,'customerCostFig.png'),'rb') as inFile:
# outData['customerCostFig.png'] = base64.standard_b64encode(inFile.read()).decode()
# outData['customerCostFig.png'] = base64.standard_b64encode(inFile.read()).decode()
# Plotly outputs.
layoutOb = go.Layout()
outData['fig1Data'] = json.dumps(plotOuts.get('gens',{}), cls=py.utils.PlotlyJSONEncoder)
Expand Down

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