def test_getRawFreq(self) -> None:
"""tests the function that gets raw frequency data
"""
appDbConnStr = self.jsonConf['appDbConnStr']
mRepo = MetricsDataRepo(appDbConnStr)
startDt = dt.datetime(2021, 2, 1)
samples = mRepo.getRawFreq(startDt, startDt)
self.assertFalse(len(samples) == 0)
def fetchSection2_1FrequencyDurationCurve(appDbConnStr: str, startDt: dt.datetime, endDt: dt.datetime) -> dict:
mRepo = MetricsDataRepo(appDbConnStr)
frequencyData = mRepo.getRawFreq(startDt,endDt)
df = pd.DataFrame(frequencyData)
frequencyDataVals = deriveDurationVals(df['frequency'],0.01)
maxFreq = round(df['frequency'].max(),2)
minFreq = round(df['frequency'].min(),2)
meanFreq = round(df['frequency'].mean(),2)
pltTitle = 'Frequency Duration Curve for {0} Max={1} , Min={2} , Avg={3} '.format(startDt.strftime('%b-%y') , maxFreq,minFreq,meanFreq)
fig, ax = plt.subplots(figsize=(7.5, 4.5))
ax.set_title(pltTitle)
ax.set_ylabel('Freq (HZ)')
ax.set_xlabel('% of time')
# ax.xaxis.set_major_locator(mdates.DayLocator(interval=2))
# ax.xaxis.set_major_formatter(mdates.DateFormatter('%d'))
ax.plot( frequencyDataVals['perc_exceeded'],frequencyDataVals['bins'], color='orange')
ax.yaxis.grid(True)
ax.xaxis.grid(True)
ax.legend( loc='best',
ncol=4, borderaxespad=0.)
plt.xticks(np.arange(0,110,10))
ax.set_xlim(xmin=0 , xmax= 100)
ax.set_ylim(ymin=49.6, ymax=50.4)
fig.subplots_adjust(bottom=0.25, top=0.8)
ax.set_facecolor("#ffffcc")
fig.patch.set_facecolor('#cbcbcb')
fig.savefig('assets/section_2_2_frequencyDurationCurve.png')
# plt.show()
# plt.close()
secData: dict = {}
return secData
def fetchSection1_4_1Context(appDbConnStr: str, startDt: dt.datetime,
endDt: dt.datetime) -> ISection_1_4_1:
mRepo = MetricsDataRepo(appDbConnStr)
# get WR demand hourly values for this month and prev yr month
# Load Shedding(MW)
# initialize demand rows
dem_data_1_4_1: List[IDemDataRow_1_4_1] = []
constList: List[IConstituentConfig] = getConstituentsMappings()
for con in constList:
cTag = con["entity_tag"]
cName = con["display_name"]
cDemVals = mRepo.getEntityMetricHourlyData(cTag, 'Demand(MW)', startDt,
endDt)
cLsVals = mRepo.getEntityMetricHourlyData(cTag, 'Load Shedding(MW)',
startDt, endDt)
cDemDf = pd.DataFrame(cDemVals + cLsVals)
cDemDf = cDemDf.pivot(index="time_stamp",
columns="metric_name",
values="data_value")
cDemDf["Req"] = cDemDf["Demand(MW)"] + cDemDf["Load Shedding(MW)"]
# get max month demand met
maxDem = cDemDf["Demand(MW)"].max()
maxDemDt = cDemDf["Demand(MW)"].idxmax().to_pydatetime()
maxDemDateStr = dt.datetime.strftime(maxDemDt, "%d-%m-%Y")
maxDemTimeStr = dt.datetime.strftime(maxDemDt, "%H:%M")
freqSamples = mRepo.getRawFreq(maxDemDt, maxDemDt)
freqAtMaxDem = 50
if len(freqSamples) > 0:
freqAtMaxDem = freqSamples[0]["frequency"]
maxReq = cDemDf["Req"].max()
maxReqDt = cDemDf["Req"].idxmax()
lsAtMaxReq = cDemDf["Load Shedding(MW)"].loc[maxReqDt]
maxReqDateStr = dt.datetime.strftime(maxReqDt.to_pydatetime(),
"%d-%m-%Y")
maxReqTimeStr = dt.datetime.strftime(maxReqDt.to_pydatetime(), "%H:%M")
freqSamples = mRepo.getRawFreq(maxDemDt, maxDemDt)
freqAtMaxReq = 50
if len(freqSamples) > 0:
freqAtMaxReq = freqSamples[0]["frequency"]
freqCorrAtMaxReq = 0
# TODO find freq correction at max req
demMetAtMaxReq = maxReq - lsAtMaxReq
if freqAtMaxReq < 50:
freqCorrAtMaxReq = 0.035 * demMetAtMaxReq * (50 - freqAtMaxReq)
reqPlusFreqCorrAtMaxReq = maxReq + freqCorrAtMaxReq
dem_data_1_4_1.extend([{
'state_name': cName,
'catered': "",
'ls': "",
'freq_corr': "",
'pc': "",
'tot_dem': "",
'peak_date': "",
'peak_time': "",
'freq_at_peak': ""
}, {
'state_name': "Registered",
'catered': round(maxDem),
'ls': "",
'freq_corr': "",
'pc': "",
'tot_dem': round(maxDem),
'peak_date': maxDemDateStr,
'peak_time': maxDemTimeStr,
'freq_at_peak': round(freqAtMaxDem, 3)
}, {
'state_name': "Un-Restricted",
'catered': round(demMetAtMaxReq),
'ls': round(lsAtMaxReq, 1),
'freq_corr': round(freqCorrAtMaxReq, 1),
'pc': "0",
'tot_dem': round(reqPlusFreqCorrAtMaxReq),
'peak_date': maxReqDateStr,
'peak_time': maxReqTimeStr,
'freq_at_peak': round(freqAtMaxReq, 3)
}])
secData: ISection_1_4_1 = {'dem_data_1_4_1': dem_data_1_4_1}
return secData
