Outputs

Index
Installing DER-VET
Running a Case
Model Details
Services
Technologies
Command Line Inputs
Command Line Outputs
GUI Inputs
GUI Results
GUI Quick Start Cases
Resolving Issues

adv_monthly_bill.csv

The "advanced monthly bill" output file shows a relational data frame containing each energy and demand charge component for each month of each optimization year. The 'billing period' column allows you to match the charge back to the input tariff file and see exactly what component of the tariff incurs what charges at what time. This table breaks out "original" charges, which are what the charge would be without any DER, from the charges themselves, which are with all DER.

capacity_factor.csv

This file contains the Capacity Factor for each active Technology (except for EVs and Controllable Loads). The capacity factor (unitless) is calculated using the time series results from DER-VET

       CF = sum(the DER's power) / ( the number of timesteps * the DER's rated power) 

The net Capacity Factor is the unitless ratio of actual electrical energy output over a given period of time to the theoretical maximum electrical energy output over that period. The theoretical maximum energy output of a given installation is defined as that due to its continuous operation at full nameplate capacity over the relevant period.

cost_benefit.csv

This file contains lifetime present value costs and benefits for each benefit and cost component of the analysis, along with a row called "Lifetime Present Value", which is the total present value for both the cost and benefit column.

dervet_log.log

This is a log file, useful for diagnosing problems. If a DER-VET case fails to complete, search this log file for 'ERROR' for more information about what went wrong.

energyp_map.csv

This file shows a rectangular table of the price of energy, whether from a time series input or a retail tariff. This is useful for making a heatmap of energy prices, showing hour of the day along the y-axis, day of the year along the x-axis, and the price of energy in color.

equipment_lifetimes.csv

This file contains a column for each DER with rows showing the DER's beginning of life (start of construction), beginning of operation, end of life, and its expected lifetime.

Electrolyzer System Degradation

ez1_cycle_counting.csv

This file contains information on how electrolzyer systems are cycled. This is the results of a rainflow counting algorithm, which counts the number of half-cycles at what depth (power fluctuation, as a percentage of rated power) the electrolyzer system executes in every optimization window. Each row represents a new cycle (count=1) or half-cycle (count=.5).

• "rng" - effective power fluctuation (after degradation) of the electrolyzer system in this optimization window.
• "mean" - average power fluctuation of the electrolyzer system in the half-cycle.
• "count" - is the cycle represented in this row a full (both charge and discharge) cycle or a half cycle (only charge or only discharge)?
• "i_start" - the time step in the optimization window when the (half) cycle starts
• "i_end" - the time step in the optimization window when the (half) cycle ends
• "Opt window" - the optimization window number. (1 is the first opt window)
• "Input_cycle_Depth_mapping" - depth (power fluctuation) of the (half) cycle in kW
• "Cycle Life Value" - this comes from the input cycle life file. It is the number of cycles at the depth (power fluctuation) of the cycle until replacement (if starting SOH = 100%)

ez1_degradation_data.csv

This file processes the cycle counting data (above) into degradation outcomes.

• "Optimization Start" - The optimization window number
• "degradation" - The change in SOH of the electrolyzer system over the optimization window.
• "soh" - The remaining state of health at the end of the optimization window

ez1_yearly_degradation.csv

This shows the change in SOH of the electrolyzer system in each year of the analysis.

Energy Storage Degradation

es_cycle_counting.csv

This file contains information on how energy storage systems are cycled. This is the results of a rainflow counting algorithm, which counts the number of half-cycles at what depth of discharge the storage system executes in every optimization window. Each row represents a new cycle (count=1) or half-cycle (count=.5).

• "rng" - effective energy capacity (after degradation) of the energy storage system in this optimization window.
• "mean" - average SOE of the storage system in the half-cycle.
• "count" - is the cycle represented in this row a full (both charge and discharge) cycle or a half cycle (only charge or only discharge)?
• "i_start" - the time step in the optimization window when the (half) cycle starts
• "i_end" - the time step in the optimization window when the (half) cycle ends
• "Opt window" - the optimization window number. (1 is the first opt window)
• "Input_cycle_DoD_mapping" - depth of discharge of the (half) cycle in kWh
• "Cycle Life Value" - this comes from the input cycle life file. It is the number of cycles at the depth of discharge of the cycle until replacement (if starting SOH = 100%)

es_degradation_data.csv

This file processes the cycle counting data (above) into degradation outcomes.

• "Optimization Start" - The optimization window number
• "degradation" - The change in SOH of the storage system over the optimization window.
• "soh" - The remaining state of health at the end of the optimization window
• "effective energy capacity" - The remaining useful energy capacity at the end of the optimization window.

es_yearly_degradation.csv

This shows the change in SOH of the storage system in each year of the analysis.

es_dispatch_map.csv

This is a rectangular data file used to make heatmaps of energy storage system charge and discharge profiles.

model_parameters.csv

This file is a copy of the input Model Parameter CSV file (if used).

model_parameters.json

This file is a copy of the input Model Parameter JSON file (if used). If the input Model Parameter was a CSV file, then it gets converted to JSON format in this file.

npv.csv

Similar to the cost_benefit.csv file, this expresses the present value of each cost/benefit category across the analysis window, but does not break out cost and benefits separately. Instead, costs are negative numbers and benefits are positive numbers.

objective_values.csv

This provides a detailed look under the hood of the optimization. This expresses every term of the objective function and the values they take in every optimization window.

payback.csv

This file expresses some financial metrics of the project - Payback Period, Discounted Payback Period, Lifetime Net Present Value, Modified Internal Rate of Return, and Benefit-Cost Ratio. For projects with an active Electrolyzer System, this file will include a Levelized Cost of Hydrogen.

peak_day_load.csv

Where applicable, this file finds the day with the peak site_load and simply expresses the site load vs time for that day. This is just used to quickly identify when the peak load occurs, what the peak load is, and make a plot accordingly.

pro_forma.csv

This is a full nominal cash flows pro forma document that expresses the nominal cost (-) or benefit (+) of each cost/benefit category in every year of the analysis window. This document shows how cash flows are escalated/interpolated, when DER are constructed, become operational, and fail, and all other detailed benefit-cost analysis mechanisms.

simple_monthly_bill.csv

Similar to the advanced monthly bill file, this expresses the energy and demand charges associated with a retail tariff. Unlike the advanced file, this aggregates each months charges into demand charges, energy charges, original (read: without DER) demand charges, and original energy charges.

size.csv

This returns the size of each DER, whether it was input by the user or determined optimally in DER-VET.

technology_summary.csv

This file simply contains a list of all DERs present and their unique name.

timeseries_results.csv

This is the heaviest output of DER-VET. It shows detailed information on all timeseries inputs and how DERs are operated in every time step of every optimization year. Column names will vary depending on which Technologies are active.