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derUtilityCost: Added stacked plots of subsidies and savings to Cash …
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…Flow Projection plot
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@astronobri
astronobri committed Dec 9, 2024
1 parent 02e3a0d commit 180d695
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12 changes: 9 additions & 3 deletions omf/models/derUtilityCost.html
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Expand Up @@ -114,7 +114,7 @@

<!-- Fossil Fuel Generator Inputs -->
<div class="wideInput">
<p class="inputSectionHeader">Fossil Fuel Generator Device Inputs</p>
<p class="inputSectionHeader">Utility-Owned Fossil Fuel Generator Device Inputs</p>
</div>
<hr style="border-style: solid; border-color: #196b12; margin-top: 10px;">
<div class="shortInput">
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"xAxis":{"title":{"text":"Year After Installation","style":{"color":"gray"}},"type":"linear","tickColor":"gray","tickInterval":1,"lineColor":"gray","minorTickColor":"gray", "minorTickInterval":5},
"title":{"text":"NPV:$" + allOutputData.NPV.toFixed(0) + ", SPP:" + allOutputData.SPP.toFixed(3), "verticalAlign":"top", "align":"right", "y":5, "x":-10, "style":{"color":"#333333", "fontSize":"12px"}},
//"title":{"text":""},
"series":[{"name":"Net Benefits", "data":allOutputData.netCashflow},
{"name":"Cumulative Return", "type":"spline", "data":allOutputData.cumulativeCashflow}
"series":[
{"name":"Net Benefits", "data": allOutputData.netCashflow},
{"name":"Utility Savings", "data": allOutputData.savingsAllYears},
{"name":"Subsidies", "data": allOutputData.subsidies},
//{"name":"BESS Compensation to Member-consumers", "data": allOutputData.BESS_compensation_to_consumer_allyears},
//{"name":"Ongoing Operational Costs", "data": allOutputData.operationalCosts_ongoing_allyears_total},
//{"name":"One-time Operational Costs", "data": allOutputData.operationalCosts_onetime_allyears_total},
{"name":"Cumulative Return", "type":"spline", "data": allOutputData.cumulativeCashflow}
],
"yAxis":{"title":{"text":"Income ($)","style":{"color":"gray"}}},
"chart":{"marginBottom":55,"zoomType":"x","renderTo":"cashFlowChartDiv","type":"column","marginRight":20, "height":250,"width":1000},
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62 changes: 39 additions & 23 deletions omf/models/derUtilityCost.py
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Expand Up @@ -146,13 +146,16 @@ def work(modelDir, inputDict):
vbatMaxPowerCapacity = pd.Series(vbatResults['maxPowerSeries'])
vbatPower = vbpower_series

projectionLength = int(inputDict['projectionLength'])
subsidyUpfront = float(inputDict['subsidyUpfront'])
subsidyRecurring_1year_total = float(inputDict['subsidyRecurring'])
subsidyRecurring_1month_total = subsidyRecurring_1year_total / 12
subsidyRecurring_total = subsidyRecurring_1year_total * int(inputDict['projectionLength'])
subsidyRecurring_total = subsidyRecurring_1year_total * projectionLength
total_subsidy_1year = subsidyUpfront + subsidyRecurring_1year_total
total_subsidy_1year_array = np.full(12, subsidyRecurring_1month_total)
total_subsidy_1year_array[0] += subsidyUpfront
total_subsidy_allyears_array = np.full(projectionLength, subsidyRecurring_1year_total)
total_subsidy_allyears_array[0] += subsidyUpfront

## NOTE: temporarily comment out the two derConsumer runs to run the code quicker
"""
Expand Down Expand Up @@ -571,6 +574,8 @@ def work(modelDir, inputDict):
BESS = reoptResults['ElectricStorage']['storage_to_load_series_kw']
electricityCost = float(inputDict['electricityCost'])
BESS_monthly_compensation_to_consumer = np.array([sum(BESS[s:f])*rateCompensation for s, f in monthHours])
BESS_yearly_compensation_to_consumer_total = np.sum(BESS_monthly_compensation_to_consumer)
BESS_allyears_compensation_to_consumer_array = np.full(projectionLength, BESS_yearly_compensation_to_consumer_total)
BESS_monthly_if_bought_from_grid = np.array([sum(BESS[s:f])*electricityCost for s, f in monthHours])
utilitySavings_from_BESS_TESS = np.array(outData['savings']) + BESS_monthly_if_bought_from_grid

Expand All @@ -588,53 +593,64 @@ def work(modelDir, inputDict):
## Total operational costs (e.g. utility costs from API calls)
operationalCosts_ongoing = float(inputDict['BESS_operationalCosts_ongoing']) + float(inputDict['TESS_operationalCosts_ongoing'])
operationalCosts_onetime = float(inputDict['BESS_operationalCosts_onetime']) + float(inputDict['TESS_operationalCosts_onetime'])
total_operationalCosts_1year = operationalCosts_onetime + operationalCosts_ongoing*12
total_operationalCosts_1year_array = np.full(12, operationalCosts_ongoing)
total_operationalCosts_1year_array[0] += operationalCosts_onetime
operationalCosts_1year_total = operationalCosts_onetime + operationalCosts_ongoing*12
operationalCosts_1year_array = np.full(12, operationalCosts_ongoing)
operationalCosts_1year_array[0] += operationalCosts_onetime
operationalCosts_ongoing_allyears_array = np.full(projectionLength, operationalCosts_ongoing*12)
operationalCosts_onetime_allyears_array = np.full(projectionLength, 0)
operationalCosts_onetime_allyears_array[0] = operationalCosts_1year_total

## Calculating total utility costs
projectionLength = int(inputDict['projectionLength'])
utilityCosts_1year_total = total_operationalCosts_1year + operationalCosts_ongoing + total_subsidy_1year + total_residential_BESS_compensation
utilityCosts_1year_total = operationalCosts_1year_total + operationalCosts_ongoing + total_subsidy_1year + total_residential_BESS_compensation
## NOTE: utilityCosts_allyears_total (below) assumes that the REopt BESS array will be the same for every year of the entire projectionLength (entire analysis)
utilityCosts_allyears_total = utilityCosts_1year_total + (projectionLength-1)*(operationalCosts_ongoing+subsidyRecurring_1year_total+total_residential_BESS_compensation)
utilityCosts_1year_array = list(np.array(total_operationalCosts_1year_array) + np.array(total_subsidy_1year_array) + np.array(BESS_monthly_compensation_to_consumer))
utilityCosts_1year_array = list(np.array(operationalCosts_1year_array) + np.array(total_subsidy_1year_array) + np.array(BESS_monthly_compensation_to_consumer))

## Calculating total utility savings
utilitySavings_1year_total = np.sum(utilitySavings_from_BESS_TESS)
utilitySavings_1year_array = utilitySavings_from_BESS_TESS
utilitySavings_allyears_total = utilitySavings_1year_total*projectionLength
utilitySavings_allyears_array = np.full(projectionLength, utilitySavings_1year_total)

## Calculating total utility net savings (savings minus costs)
utilityNetSavings_1year_total = utilitySavings_1year_total - utilityCosts_1year_total
utilityNetSavings_1year_total = utilityCosts_1year_total - utilitySavings_1year_total
utilityNetSavings_1year_array = list(np.array(utilitySavings_1year_array) - np.array(utilityCosts_1year_array))
utilityNetSavings_allyears_total = utilitySavings_allyears_total - utilityCosts_allyears_total
utilityNetSavings_allyears_array = np.full(projectionLength,utilityNetSavings_1year_total)

## Note: The following for-loop would display the net savings as positive. If there are negative savings (when costs are greater than savings), it will only show $0 savings, rather than the negative savings amount. This might not be a useful way to display it, so it is commented for now.
## Calculate the net savings and costs for each month
utilityNetSavings_1year_list = []
leftoverCosts = 0
for savings, costs in zip(utilitySavings_1year_array, utilityCosts_1year_array):
net = costs - savings
#utilityNetSavings_1year_list = []
#leftoverCosts = 0
#for savings, costs in zip(utilitySavings_1year_array, utilityCosts_1year_array):
# net = costs - savings

## Add leftover costs from previous months
net_with_leftover = net + leftoverCosts
# ## Add leftover costs from previous months
# net_with_leftover = net + leftoverCosts

## If any leftover costs, then carry them over to the next month
if net_with_leftover > 0:
leftoverCosts = net_with_leftover
utilityNetSavings_1year_list.append(0) ## No net savings for this month
else:
leftoverCosts = 0 ## No leftover costs if net is covered
utilityNetSavings_1year_list.append(-net_with_leftover) ## Record net savings (positive)
# ## If any leftover costs, then carry them over to the next month
# if net_with_leftover > 0:
# leftoverCosts = net_with_leftover
# utilityNetSavings_1year_list.append(0) ## No net savings for this month
# else:
# leftoverCosts = 0 ## No leftover costs if net is covered
# utilityNetSavings_1year_list.append(-net_with_leftover) ## Record net savings (positive)

#outData['savings'] = utilityNetSavings_1year_list

# Update financial parameters
outData['savings'] = utilityNetSavings_1year_list
#outData['savings'] = utilityNetSavings_1year_array
outData['savings'] = utilityNetSavings_1year_array
outData['totalCost'] = list(np.array(outData['totalCost']) + np.array(utilityCosts_1year_array))
outData['NPV'] = utilityNetSavings_allyears_total
outData['SPP'] = utilityCosts_allyears_total / utilitySavings_1year_total
outData['netCashflow'] = list(utilityNetSavings_allyears_array)
outData['cumulativeCashflow'] = [sum(utilityNetSavings_allyears_array[:i+1]) for i in range(len(utilityNetSavings_allyears_array))]
outData['savingsAllYears'] = list(utilitySavings_allyears_array)
outData['subsidies'] = list(total_subsidy_allyears_array)
outData['BESS_compensation_to_consumer_allyears'] = list(BESS_allyears_compensation_to_consumer_array)
#outData['operationalCosts_ongoing_allyears_total'] = list(operationalCosts_ongoing_allyears_array)
#outData['operationalCosts_onetime_allyears_total'] = list(operationalCosts_onetime_allyears_array)


# Model operations typically ends here.
# Stdout/stderr.
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