# REopt Inputs

Inputs to `run_reopt`

can be provided in one of four formats:

- a file path (string) to a JSON file,
- a
`Dict`

, - using the
`Scenario`

struct, or - using the
`REoptInputs`

struct

Any one of these types can be passed to the run_reopt method as shown in Examples.

The first option is perhaps the most straightforward. For example, the minimum requirements for a JSON scenario file would look like:

```
{
"Site": {
"longitude": -118.1164613,
"latitude": 34.5794343
},
"ElectricLoad": {
"doe_reference_name": "MidriseApartment",
"annual_kwh": 1000000.0
},
"ElectricTariff": {
"urdb_label": "5ed6c1a15457a3367add15ae"
}
}
```

The order of the keys does not matter. Note that this scenario does not include any energy generation technologies and therefore the results can be used as a baseline for comparison to scenarios that result in cost-optimal generation technologies (alternatively, a user could include a BAUScenario as shown in Examples).

To add PV to the analysis simply add a PV key with an empty dictionary (to use default values):

```
{
"Site": {
"longitude": -118.1164613,
"latitude": 34.5794343
},
"ElectricLoad": {
"doe_reference_name": "MidriseApartment",
"annual_kwh": 1000000.0
},
"ElectricTariff": {
"urdb_label": "5ed6c1a15457a3367add15ae"
},
"PV": {}
}
```

This scenario will consider the option to purchase a solar PV system to reduce energy costs, and if solar PV can reduce the energy costs then REopt will provide the optimal PV capacity (assuming perfect foresight!). See PV for all available input keys and default values for `PV`

. To override a default value, simply specify a value for a given key. For example, the site under consideration might have some existing PV capacity to account for, which can be done by setting the `existing_kw`

key to the appropriate value.

## Scenario

The `Scenario`

struct captures all of the possible user input keys (see REopt Inputs for potential input formats). A Scenario struct will be automatically created if a `Dict`

or file path are supplied to the run_reopt method. Alternatively, a user can create a `Scenario`

struct and supply this to run_reopt.

`REopt.Scenario`

— Type`Scenario(d::Dict; flex_hvac_from_json=false)`

A Scenario struct can contain the following keys:

- Site (required)
- Financial (optional)
- ElectricTariff (required when
`off_grid_flag=false`

) - ElectricLoad (required)
- PV (optional, can be Array)
- Wind (optional)
- ElectricStorage (optional)
- ElectricUtility (optional)
- Generator (optional)
- DomesticHotWaterLoad (optional)
- SpaceHeatingLoad (optional)
- ExistingBoiler (optional)
- Boiler (optional)
- CHP (optional)
- FlexibleHVAC (optional)
- ExistingChiller (optional)
- AbsorptionChiller (optional)
- GHP (optional, can be Array)
- SteamTurbine (optional)

All values of `d`

are expected to be `Dicts`

except for `PV`

and `GHP`

, which can be either a `Dict`

or `Dict[]`

(for multiple PV arrays or GHP options).

Set `flex_hvac_from_json=true`

if `FlexibleHVAC`

values were loaded in from JSON (necessary to handle conversion of Vector of Vectors from JSON to a Matrix in Julia).

`Scenario(fp::String)`

Consruct Scenario from filepath `fp`

to JSON with keys aligned with the `Scenario(d::Dict)`

method.

## BAUScenario

The Business-as-usual (BAU) inputs are automatically created based on the `BAUScenario`

struct when a user supplies two `JuMP.Model`

s to `run_reopt()`

(as shown in Examples). The outputs of the BAU scenario are used to calculate comparative results such as the `Financial`

net present value (`npv`

).

`REopt.BAUInputs`

— Function`BAUInputs(p::REoptInputs)`

The`BAUInputs`

(REoptInputs for the Business As Usual scenario) are created based on the `BAUScenario`

, which is in turn created based on the optimized-case `Scenario`

.

The following assumptions are made for the BAU Inputs:

`PV`

and`Generator`

`min_kw`

and`max_kw`

set to the`existing_kw`

values`ExistingBoiler`

and`ExistingChiller`

# TODO- All other generation and storage tech sizes set to zero
- Capital costs are assumed to be zero for existing
`PV`

and`Generator`

- O&M costs and all other tech inputs are assumed to be the same for existing
`PV`

and`Generator`

as those specified for the optimized case - Outage assumptions for deterministic vs stochastic # TODO

## Settings

`REopt.Settings`

— TypeCaptures high-level inputs affecting the optimization.

`Settings`

is an optional REopt input with the following keys and default values:

```
time_steps_per_hour::Int = 1 # corresponds to the time steps per hour for user-provided time series (e.g., `ElectricLoad.loads_kw` and `DomesticHotWaterLoad.fuel_loads_mmbtu_per_hour`)
add_soc_incentive::Bool = true # when true, an incentive is added to the model's objective function to keep the ElectricStorage SOC high
off_grid_flag::Bool = false # true if modeling an off-grid system, not connected to bulk power system
include_climate_in_objective::Bool = false # true if climate costs of emissions should be included in the model's objective function
include_health_in_objective::Bool = false # true if health costs of emissions should be included in the model's objective function
```

## Site

`REopt.Site`

— TypeInputs related to the physical location:

`Site`

is a required REopt input with the following keys and default values:

```
latitude::Real,
longitude::Real,
land_acres::Union{Real, Nothing} = nothing, # acres of land available for PV panels and/or Wind turbines. Constraint applied separately to PV and Wind, meaning the two technologies are assumed to be able to be co-located.
roof_squarefeet::Union{Real, Nothing} = nothing,
min_resil_time_steps::Int=0,
mg_tech_sizes_equal_grid_sizes::Bool = true,
node::Int = 1,
CO2_emissions_reduction_min_fraction::Union{Float64, Nothing} = nothing,
CO2_emissions_reduction_max_fraction::Union{Float64, Nothing} = nothing,
bau_emissions_lb_CO2_per_year::Union{Float64, Nothing} = nothing, # Auto-populated based on BAU run. This input will be overwritten if the BAU scenario is run, but can be user-provided if no BAU scenario is run.
bau_grid_emissions_lb_CO2_per_year::Union{Float64, Nothing} = nothing,
renewable_electricity_min_fraction::Real = 0.0,
renewable_electricity_max_fraction::Union{Float64, Nothing} = nothing,
include_exported_elec_emissions_in_total::Bool = true,
include_exported_renewable_electricity_in_total::Bool = true,
```

## ElectricLoad

`REopt.ElectricLoad`

— Type`ElectricLoad`

is a required REopt input with the following keys and default values:

```
loads_kw::Array{<:Real,1} = Real[],
path_to_csv::String = "", # for csv containing loads_kw
doe_reference_name::String = "",
blended_doe_reference_names::Array{String, 1} = String[],
blended_doe_reference_percents::Array{<:Real,1} = Real[],
year::Int = doe_reference_name ≠ "" || blended_doe_reference_names ≠ String[] ? 2017 : 2022, # used in ElectricTariff to align rate schedule with weekdays/weekends. DOE CRB profiles must use 2017. If providing load data, specify year of data.
city::String = "",
annual_kwh::Union{Real, Nothing} = nothing,
monthly_totals_kwh::Array{<:Real,1} = Real[],
critical_loads_kw::Union{Nothing, Array{Real,1}} = nothing,
loads_kw_is_net::Bool = true,
critical_loads_kw_is_net::Bool = false,
critical_load_fraction::Real = off_grid_flag ? 1.0 : 0.5, # if off grid must be 1.0, else 0.5
operating_reserve_required_fraction::Real = off_grid_flag ? 0.1 : 0.0, # if off grid, 10%, else must be 0%. Applied to each time_step as a % of electric load.
min_load_met_annual_fraction::Real = off_grid_flag ? 0.99999 : 1.0 # if off grid, 99.999%, else must be 100%. Applied to each time_step as a % of electric load.
```

Must provide either `loads_kw`

or `path_to_csv`

or [`doe_reference_name`

and `city`

] or `doe_reference_name`

or [`blended_doe_reference_names`

and `blended_doe_reference_percents`

].

When only `doe_reference_name`

is provided the `Site.latitude`

and `Site.longitude`

are used to look up the ASHRAE climate zone, which determines the appropriate DoE Commercial Reference Building profile.

When using the [`doe_reference_name`

and `city`

] option, choose `city`

from one of the cities used to represent the ASHRAE climate zones:

- Albuquerque
- Atlanta
- Baltimore
- Boulder
- Chicago
- Duluth
- Fairbanks
- Helena
- Houston
- LosAngeles
- Miami
- Minneapolis
- Phoenix
- SanFrancisco
- Seattle

and `doe_reference_name`

from:

- FastFoodRest
- FullServiceRest
- Hospital
- LargeHotel
- LargeOffice
- MediumOffice
- MidriseApartment
- Outpatient
- PrimarySchool
- RetailStore
- SecondarySchool
- SmallHotel
- SmallOffice
- StripMall
- Supermarket
- Warehouse
- FlatLoad # constant load year-round
- FlatLoad
*24*5 # constant load all hours of the weekdays - FlatLoad
*16*7 # two 8-hour shifts for all days of the year; 6-10 a.m. - FlatLoad
*16*5 # two 8-hour shifts for the weekdays; 6-10 a.m. - FlatLoad
*8*7 # one 8-hour shift for all days of the year; 9 a.m.-5 p.m. - FlatLoad
*8*5 # one 8-hour shift for the weekdays; 9 a.m.-5 p.m.

Each `city`

and `doe_reference_name`

combination has a default `annual_kwh`

, or you can provide your own `annual_kwh`

or `monthly_totals_kwh`

and the reference profile will be scaled appropriately.

The ElectricLoad `year`

is used in ElectricTariff to align rate schedules with weekdays/weekends. If providing your own `loads_kw`

, ensure the `year`

matches the year of your data. If utilizing `doe_reference_name`

or `blended_doe_reference_names`

, the default year of 2017 is used because these load profiles start on a Sunday.

## ElectricTariff

`REopt.ElectricTariff`

— Method`ElectricTariff`

is a required REopt input for on-grid scenarios only (it cannot be supplied when `Settings.off_grid_flag`

is true) with the following keys and default values:

```
urdb_label::String="",
urdb_response::Dict=Dict(),
urdb_utility_name::String="",
urdb_rate_name::String="",
wholesale_rate::T1=nothing, # Price of electricity sold back to the grid in absence of net metering. Can be a scalar value, which applies for all-time, or an array with time-sensitive values. If an array is input then it must have a length of 8760, 17520, or 35040. The inputed array values are up/down-sampled using mean values to match the Settings.time_steps_per_hour.
export_rate_beyond_net_metering_limit::T2=nothing, # Price of electricity sold back to the grid beyond total annual grid purchases, regardless of net metering. Can be a scalar value, which applies for all-time, or an array with time-sensitive values. If an array is input then it must have a length of 8760, 17520, or 35040. The inputed array values are up/down-sampled using mean values to match the Settings.time_steps_per_hour
monthly_energy_rates::Array=[], # Array (length of 12) of blended energy rates in dollars per kWh
monthly_demand_rates::Array=[], # Array (length of 12) of blended demand charges in dollars per kW
blended_annual_energy_rate::S=nothing, # Annual blended energy rate [$ per kWh] (total annual energy in kWh divided by annual cost in dollars)
blended_annual_demand_rate::R=nothing, # Average monthly demand charge [$ per kW per month]. Rate will be applied to monthly peak demand.
add_monthly_rates_to_urdb_rate::Bool=false, # Set to 'true' to add the monthly blended energy rates and demand charges to the URDB rate schedule. Otherwise, blended rates will only be considered if a URDB rate is not provided.
tou_energy_rates_per_kwh::Array=[], # Time-of-use energy rates, provided by user. Must be an array with length equal to number of timesteps per year.
add_tou_energy_rates_to_urdb_rate::Bool=false, # Set to 'true' to add the tou energy rates to the URDB rate schedule. Otherwise, tou energy rates will only be considered if a URDB rate is not provided.
remove_tiers::Bool=false,
demand_lookback_months::AbstractArray{Int64, 1}=Int64[], # Array of 12 binary values, indicating months in which `demand_lookback_percent` applies. If any of these is true, `demand_lookback_range` should be zero.
demand_lookback_percent::Real=0.0, # Lookback percentage. Applies to either `demand_lookback_months` with value=1, or months in `demand_lookback_range`.
demand_lookback_range::Int=0, # Number of months for which `demand_lookback_percent` applies. If not 0, `demand_lookback_months` should not be supplied.
coincident_peak_load_active_time_steps::Vector{Vector{Int64}}=[Int64[]], # The optional coincident_peak_load_charge_per_kw will apply at the max grid-purchased power during these timesteps. Note timesteps are indexed to a base of 1 not 0.
coincident_peak_load_charge_per_kw::AbstractVector{<:Real}=Real[] # Optional coincident peak demand charge that is applied to the max load during the timesteps specified in coincident_peak_load_active_time_steps.
) where {
T1 <: Union{Nothing, Real, Array{<:Real}},
T2 <: Union{Nothing, Real, Array{<:Real}},
S <: Union{Nothing, Real},
R <: Union{Nothing, Real}
}
```

There are three Export tiers and their associated export rates (negative cost values):

- NEM (Net Energy Metering) - set to the energy rate (or tier with the lowest energy rate, if tiered)
- WHL (Wholesale) - set to wholesale_rate
- EXC (Excess, beyond NEM) - set to export
*rate*beyond*net*metering_limit

Only one of NEM and Wholesale can be exported into due to the binary constraints. Excess can be exported into in the same time step as NEM.

Excess is meant to be combined with NEM: NEM export is limited to the total grid purchased energy in a year and some utilities offer a compensation mechanism for export beyond the site load. The Excess tier is not available with the Wholesale tier.

The `NEM`

boolean is determined by the `ElectricUtility.net_metering_limit_kw`

. There is no need to pass in a `NEM`

value.

Cannot use both `demand_lookback_months`

and `demand_lookback_range`

inputs, only one or the other. When using lookbacks, the peak demand in each month will be the greater of the peak kW in that month and the peak kW in the lookback months times the demand*lookback*percent.

## Financial

`REopt.Financial`

— Type`Financial`

is an optional REopt input with the following keys and default values:

```
om_cost_escalation_rate_fraction::Real = 0.025,
elec_cost_escalation_rate_fraction::Real = 0.019,
existing_boiler_fuel_cost_escalation_rate_fraction::Float64 = 0.034,
boiler_fuel_cost_escalation_rate_fraction::Real = 0.034,
chp_fuel_cost_escalation_rate_fraction::Real = 0.034,
generator_fuel_cost_escalation_rate_fraction::Real = 0.027,
offtaker_tax_rate_fraction::Real = 0.26,
offtaker_discount_rate_fraction::Real = 0.0564,
third_party_ownership::Bool = false,
owner_tax_rate_fraction::Real = 0.26,
owner_discount_rate_fraction::Real = 0.0564,
analysis_years::Int = 25,
value_of_lost_load_per_kwh::Union{Array{R,1}, R} where R<:Real = 1.00, #only applies to multiple outage modeling
microgrid_upgrade_cost_fraction::Real = 0.0
macrs_five_year::Array{Float64,1} = [0.2, 0.32, 0.192, 0.1152, 0.1152, 0.0576], # IRS pub 946
macrs_seven_year::Array{Float64,1} = [0.1429, 0.2449, 0.1749, 0.1249, 0.0893, 0.0892, 0.0893, 0.0446],
offgrid_other_capital_costs::Real = 0.0, # only applicable when `off_grid_flag` is true. Straight-line depreciation is applied to this capex cost, reducing taxable income.
offgrid_other_annual_costs::Real = 0.0 # only applicable when `off_grid_flag` is true. Considered tax deductible for owner. Costs are per year.
# Emissions cost inputs
CO2_cost_per_tonne::Real = 51.0,
CO2_cost_escalation_rate_fraction::Real = 0.042173,
NOx_grid_cost_per_tonne::Union{Nothing,Real} = nothing,
SO2_grid_cost_per_tonne::Union{Nothing,Real} = nothing,
PM25_grid_cost_per_tonne::Union{Nothing,Real} = nothing,
NOx_onsite_fuelburn_cost_per_tonne::Union{Nothing,Real} = nothing,
SO2_onsite_fuelburn_cost_per_tonne::Union{Nothing,Real} = nothing,
PM25_onsite_fuelburn_cost_per_tonne::Union{Nothing,Real} = nothing,
NOx_cost_escalation_rate_fraction::Union{Nothing,Real} = nothing,
SO2_cost_escalation_rate_fraction::Union{Nothing,Real} = nothing,
PM25_cost_escalation_rate_fraction::Union{Nothing,Real} = nothing
```

When `third_party_ownership`

is `false`

the offtaker's discount and tax percentages are used throughout the model:

```
if !third_party_ownership
owner_tax_rate_fraction = offtaker_tax_rate_fraction
owner_discount_rate_fraction = offtaker_discount_rate_fraction
end
```

## ElectricUtility

`REopt.ElectricUtility`

— Type`ElectricUtility`

is an optional REopt input with the following keys and default values:

```
net_metering_limit_kw::Real = 0,
interconnection_limit_kw::Real = 1.0e9, # Limit on total electric system capacity size that can be interconnected to the grid
outage_start_time_step::Int=0, # for modeling a single outage, with critical load spliced into the baseline load ...
outage_end_time_step::Int=0, # ... utiltity production_factor = 0 during the outage
allow_simultaneous_export_import::Bool = true, # if true the site has two meters (in effect)
# next 5 variables below used for minimax the expected outage cost,
# with max taken over outage start time, expectation taken over outage duration
outage_start_time_steps::Array{Int,1}=Int[], # we minimize the maximum outage cost over outage start times
outage_durations::Array{Int,1}=Int[], # one-to-one with outage_probabilities, outage_durations can be a random variable
outage_probabilities::Array{R,1} where R<:Real = [1.0],
# Emissions and renewable energy inputs:
emissions_region::String = "", # AVERT emissions region. Default is based on location, or can be overriden by providing region here.
emissions_factor_series_lb_CO2_per_kwh::Union{Real,Array{<:Real,1}} = Float64[], # can be scalar or timeseries (aligned with time_steps_per_hour)
emissions_factor_series_lb_NOx_per_kwh::Union{Real,Array{<:Real,1}} = Float64[], # can be scalar or timeseries (aligned with time_steps_per_hour)
emissions_factor_series_lb_SO2_per_kwh::Union{Real,Array{<:Real,1}} = Float64[], # can be scalar or timeseries (aligned with time_steps_per_hour)
emissions_factor_series_lb_PM25_per_kwh::Union{Real,Array{<:Real,1}} = Float64[], # can be scalar or timeseries (aligned with time_steps_per_hour)
emissions_factor_CO2_decrease_fraction::Real = 0.01174, # Annual percent decrease in the total annual CO2 emissions rate of the grid. A negative value indicates an annual increase.
emissions_factor_NOx_decrease_fraction::Real = 0.01174,
emissions_factor_SO2_decrease_fraction::Real = 0.01174,
emissions_factor_PM25_decrease_fraction::Real = 0.01174
```

Outage indexing begins at 1 (not 0) and the outage is inclusive of the outage end time step. For instance, to model a 3-hour outage from 12AM to 3AM on Jan 1, outage*start*time*step = 1 and outage*end*time*step = 3. To model a 1-hour outage from 6AM to 7AM on Jan 1, outage*start*time*step = 7 and outage*end*time*step = 7.

Cannot supply singular outage*start(or end)*time*step and multiple outage*start*time*steps. Must use one or the other.

If a single deterministic outage is modeled using outage*start*time*step and outage*end*time*step, emissions and renewable energy percentage calculations and constraints will factor in this outage. If stochastic outages are modeled using outage*start*time*steps, outage*durations, and outage_probabilities, emissions and renewable energy percentage calculations and constraints will not consider outages.

This constructor is intended to be used with latitude/longitude arguments provided for the non-MPC case and without latitude/longitude arguments provided for the MPC case.

The default `emissions_region`

input is determined by the site's latitude and longitude. Alternatively, you may input the desired AVERT `emissions_region`

, which must be one of: ["California", "Central", "Florida", "Mid-Atlantic", "Midwest", "Carolinas", "New England", "Northwest", "New York", "Rocky Mountains", "Southeast", "Southwest", "Tennessee", "Texas", "Alaska", "Hawaii (except Oahu)", "Hawaii (Oahu)"]

## PV

`REopt.PV`

— Type`PV`

is an optional REopt input with the following keys and default values:

```
array_type::Int=1, # PV Watts array type (0: Ground Mount Fixed (Open Rack); 1: Rooftop, Fixed; 2: Ground Mount 1-Axis Tracking; 3 : 1-Axis Backtracking; 4: Ground Mount, 2-Axis Tracking)
tilt::Real= array_type == 1 ? 10 : abs(latitude), # tilt = 10 deg for rooftop systems, abs(lat) for ground-mount
module_type::Int=0, # PV module type (0: Standard; 1: Premium; 2: Thin Film)
losses::Real=0.14,
azimuth::Real = latitude≥0 ? 180 : 0, # set azimuth to zero for southern hemisphere
gcr::Real=0.4,
radius::Int=0,
name::String="PV",
location::String="both",
existing_kw::Real=0,
min_kw::Real=0,
max_kw::Real=1.0e9,
installed_cost_per_kw::Real=1592.0,
om_cost_per_kw::Real=17.0,
degradation_fraction::Real=0.005,
macrs_option_years::Int = 5,
macrs_bonus_fraction::Real = 0.8,
macrs_itc_reduction::Real = 0.5,
kw_per_square_foot::Real=0.01,
acres_per_kw::Real=6e-3,
inv_eff::Real=0.96,
dc_ac_ratio::Real=1.2,
production_factor_series::Union{Nothing, Array{<:Real,1}} = nothing, # Optional user-defined production factors. Must be normalized to units of kW-AC/kW-DC nameplate. The series must be one year (January through December) of hourly, 30-minute, or 15-minute generation data.
federal_itc_fraction::Real = 0.3,
federal_rebate_per_kw::Real = 0.0,
state_ibi_fraction::Real = 0.0,
state_ibi_max::Real = 1.0e10,
state_rebate_per_kw::Real = 0.0,
state_rebate_max::Real = 1.0e10,
utility_ibi_fraction::Real = 0.0,
utility_ibi_max::Real = 1.0e10,
utility_rebate_per_kw::Real = 0.0,
utility_rebate_max::Real = 1.0e10,
production_incentive_per_kwh::Real = 0.0,
production_incentive_max_benefit::Real = 1.0e9,
production_incentive_years::Int = 1,
production_incentive_max_kw::Real = 1.0e9,
can_net_meter::Bool = off_grid_flag ? false : true,
can_wholesale::Bool = off_grid_flag ? false : true,
can_export_beyond_nem_limit::Bool = off_grid_flag ? false : true,
can_curtail::Bool = true,
operating_reserve_required_fraction::Real = off_grid_flag ? 0.25 : 0.0, # if off grid, 25%, else 0%. Applied to each time_step as a % of PV generation.
```

Multiple PV types can be considered by providing an array of PV inputs. See example in `src/test/scenarios/multiple_pvs.json`

If `tilt`

is not provided, then it is set to the absolute value of `Site.latitude`

for ground-mount systems and is set to 10 degrees for rooftop systems. If `azimuth`

is not provided, then it is set to 180 if the site is in the northern hemisphere and 0 if in the southern hemisphere.

## Wind

`REopt.Wind`

— Type`Wind`

is an optional REopt input with the following keys and default values:

```
min_kw = 0.0,
max_kw = 1.0e9,
installed_cost_per_kw = nothing,
om_cost_per_kw = 35.0,
production_factor_series = nothing, # Optional user-defined production factors. Must be normalized to units of kW-AC/kW-DC nameplate. The series must be one year (January through December) of hourly, 30-minute, or 15-minute generation data.
size_class = "",
wind_meters_per_sec = [],
wind_direction_degrees = [],
temperature_celsius = [],
pressure_atmospheres = [],
acres_per_kw = 0.03, # assuming a power density of 30 acres per MW for turbine sizes >= 1.5 MW. No size constraint applied to turbines below 1.5 MW capacity. (not exposed in API)
macrs_option_years = 5,
macrs_bonus_fraction = 0.8,
macrs_itc_reduction = 0.5,
federal_itc_fraction = 0.3,
federal_rebate_per_kw = 0.0,
state_ibi_fraction = 0.0,
state_ibi_max = 1.0e10,
state_rebate_per_kw = 0.0,
state_rebate_max = 1.0e10,
utility_ibi_fraction = 0.0,
utility_ibi_max = 1.0e10,
utility_rebate_per_kw = 0.0,
utility_rebate_max = 1.0e10,
production_incentive_per_kwh = 0.0,
production_incentive_max_benefit = 1.0e9,
production_incentive_years = 1,
production_incentive_max_kw = 1.0e9,
can_net_meter = true,
can_wholesale = true,
can_export_beyond_nem_limit = true
operating_reserve_required_fraction::Real = off_grid_flag ? 0.50 : 0.0, # Only applicable when `off_grid_flag` is true. Applied to each time_step as a % of wind generation serving load.
```

`size_class`

must be one of ["residential", "commercial", "medium", "large"]. If `size_class`

is not provided then it is determined based on the average electric load.

If no `installed_cost_per_kw`

is provided then it is determined from:

```
size_class_to_installed_cost = Dict(
"residential"=> 11950.0,
"commercial"=> 7390.0,
"medium"=> 4440.0,
"large"=> 3450.0
)
```

If the `production_factor_series`

is not provided then NREL's System Advisor Model (SAM) is used to get the wind turbine production factor.

Wind resource values are optional (i.e., `wind_meters_per_sec`

, `wind_direction_degrees`

, `temperature_celsius`

, and `pressure_atmospheres`

). If not provided then the resource values are downloaded from NREL's Wind Toolkit. These values are passed to SAM to get the turbine production factor.

Wind size is constrained by Site.land*acres, assuming a power density of Wind.acres*per_kw for turbine sizes above 1.5 MW (default assumption of 30 acres per MW). If the turbine size recommended is smaller than 1.5 MW, the input for land available will not constrain the system size. If the the land available constrains the system size to less than 1.5 MW, the system will be capped at 1.5 MW (i.e., turbines < 1.5 MW are not subject to the acres/kW limit).

## ElectricStorage

`REopt.ElectricStorageDefaults`

— Type`ElectricStorage`

is an optional optional REopt input with the following keys and default values:

```
min_kw::Real = 0.0
max_kw::Real = 1.0e4
min_kwh::Real = 0.0
max_kwh::Real = 1.0e6
internal_efficiency_fraction::Float64 = 0.975
inverter_efficiency_fraction::Float64 = 0.96
rectifier_efficiency_fraction::Float64 = 0.96
soc_min_fraction::Float64 = 0.2
soc_init_fraction::Float64 = off_grid_flag ? 1.0 : 0.5
can_grid_charge::Bool = off_grid_flag ? false : true
installed_cost_per_kw::Real = 775.0
installed_cost_per_kwh::Real = 388.0
replace_cost_per_kw::Real = 440.0
replace_cost_per_kwh::Real = 220.0
inverter_replacement_year::Int = 10
battery_replacement_year::Int = 10
macrs_option_years::Int = 7
macrs_bonus_fraction::Float64 = 0.8
macrs_itc_reduction::Float64 = 0.5
total_itc_fraction::Float64 = 0.3
total_rebate_per_kw::Real = 0.0
total_rebate_per_kwh::Real = 0.0
charge_efficiency::Float64 = rectifier_efficiency_fraction * internal_efficiency_fraction^0.5
discharge_efficiency::Float64 = inverter_efficiency_fraction * internal_efficiency_fraction^0.5
grid_charge_efficiency::Float64 = can_grid_charge ? charge_efficiency : 0.0
model_degradation::Bool = false
degradation::Dict = Dict()
minimum_avg_soc_fraction::Float64 = 0.0
```

`REopt.Degradation`

— Type`Degradation`

Inputs used when `ElectricStorage.model_degradation`

is `true`

:

```
Base.@kwdef mutable struct Degradation
calendar_fade_coefficient::Real = 2.46E-03
cycle_fade_coefficient::Real = 7.82E-05
time_exponent::Real = 0.5
installed_cost_per_kwh_declination_rate::Float64 = 0.05
maintenance_strategy::String = "augmentation" # one of ["augmentation", "replacement"]
maintenance_cost_per_kwh::Vector{<:Real} = Real[]
end
```

None of the above values are required. If `ElectricStorage.model_degradation`

is `true`

then the defaults above are used. If the `maintenance_cost_per_kwh`

is not provided then it is determined using the `ElectricStorage.installed_cost_per_kwh`

and the `installed_cost_per_kwh_declination_rate`

along with a present worth factor $f$ to account for the present cost of buying a battery in the future. The present worth factor for each day is:

$f(day) = \frac{ (1-r_g)^\frac{day}{365} } { (1+r_d)^\frac{day}{365} }$

where $r_g$ = `installed_cost_per_kwh_declination_rate`

and $r_d$ = `p.s.financial.owner_discount_rate_fraction`

.

Note this day-specific calculation of the present-worth factor accumulates differently from the annually updated discount rate for other net-present value calculations in REopt, and has a higher effective discount rate as a result. The present worth factor is used in two different ways, depending on the `maintenance_strategy`

, which is described below.

When modeling degradation the following ElectricStorage inputs are not used:

`replace_cost_per_kw`

`replace_cost_per_kwh`

`inverter_replacement_year`

`battery_replacement_year`

The are replaced by the `maintenance_cost_per_kwh`

vector.

When providing the `maintenance_cost_per_kwh`

it must have a length equal to `Financial.analysis_years*365`

.

**Battery State Of Health**

The state of health [`SOH`

] is a linear function of the daily average state of charge [`Eavg`

] and the daily equivalent full cycles [`EFC`

]. The initial `SOH`

is set to the optimal battery energy capacity (in kWh). The evolution of the `SOH`

beyond the first day is:

$SOH[d] = SOH[d-1] - h\left( \frac{1}{2} k_{cal} Eavg[d-1] / \sqrt{d} + k_{cyc} EFC[d-1] \quad \forall d \in \{2\dots D\} \right)$

where:

- $k_{cal}$ is the
`calendar_fade_coefficient`

- $k_{cyc}$ is the
`cycle_fade_coefficient`

- $h$ is the hours per time step
- $D$ is the total number of days, 365 *
`analysis_years`

The `SOH`

is used to determine the maintence cost of the storage system, which depends on the `maintenance_strategy`

.

**Augmentation Maintenance Strategy**

The augmentation maintenance strategy assumes that the battery energy capacity is maintained by replacing degraded cells daily in terms of cost. Using the definition of the `SOH`

above the maintenance cost is:

$C_{\text{aug}} = \sum_{d \in \{2\dots D\}} 0.8 C_{\text{install}} f(day) \left( SOH[d-1] - SOH[d] \right)$

where

- the $0.8$ factor accounts for sunk costs that do not need to be paid;
- $C_{\text{install}}$ is the
`ElectricStorage.installed_cost_per_kwh`

; and - $SOH[d-1] - SOH[d]$ is the incremental amount of battery capacity lost in a day.

The $C_{\text{aug}}$ is added to the objective function to be minimized with all other costs.

**Replacement Maintenance Strategy**

Modeling the replacement maintenance strategy is more complex than the augmentation strategy. Effectively the replacement strategy says that the battery has to be replaced once the `SOH`

hits 80% of the optimal, purchased capacity. It is possible that multiple replacements could be required under this strategy.

The "replacement" maintenance strategy requires integer variables and indicator constraints. Not all solvers support indicator constraints and some solvers are slow with integer variables.

The replacement strategy cost is:

$C_{\text{repl}} = B_{\text{kWh}} N_{\text{repl}} f(d_{80}) C_{\text{install}}$

where:

- $B_{\text{kWh}}$ is the optimal battery capacity (
`ElectricStorage.size_kwh`

in the results dictionary); - $N_{\text{repl}}$ is the number of battery replacments required (a function of the month in which the
`SOH`

reaches 80% of original capacity); - $f(d_{80})$ is the present worth factor at approximately the 15th day of the month that the
`SOH`

reaches 80% of original capacity.

The $C_{\text{repl}}$ is added to the objective function to be minimized with all other costs.

**Example of inputs**

The following shows how one would use the degradation model in REopt via the Scenario inputs:

```
{
...
"ElectricStorage": {
"installed_cost_per_kwh": 390,
...
"model_degradation": true,
"degradation": {
"calendar_fade_coefficient": 2.86E-03,
"cycle_fade_coefficient": 6.22E-05,
"installed_cost_per_kwh_declination_rate": 0.06,
"maintenance_strategy": "replacement",
...
}
},
...
}
```

Note that not all of the above inputs are necessary. When not providing `calendar_fade_coefficient`

for example the default value will be used.

## Generator

`REopt.Generator`

— Type`Generator`

is an optional REopt input with the following keys and default values:

```
existing_kw::Real = 0,
min_kw::Real = 0,
max_kw::Real = 1.0e6,
installed_cost_per_kw::Real = 500.0,
om_cost_per_kw::Real = off_grid_flag ? 20.0 : 10.0,
om_cost_per_kwh::Real = 0.0,
fuel_cost_per_gallon::Real = 3.0,
electric_efficiency_full_load::Real = 0.3233,
electric_efficiency_half_load::Real = electric_efficiency_full_load,
fuel_avail_gal::Real = off_grid_flag ? 1.0e9 : 660.0,
fuel_higher_heating_value_kwh_per_gal::Real = 40.7,
min_turn_down_fraction::Real = off_grid_flag ? 0.15 : 0.0,
only_runs_during_grid_outage::Bool = true,
sells_energy_back_to_grid::Bool = false,
can_net_meter::Bool = false,
can_wholesale::Bool = false,
can_export_beyond_nem_limit = false,
can_curtail::Bool = false,
macrs_option_years::Int = 0,
macrs_bonus_fraction::Real = 1.0,
macrs_itc_reduction::Real = 0.0,
federal_itc_fraction::Real = 0.0,
federal_rebate_per_kw::Real = 0.0,
state_ibi_fraction::Real = 0.0,
state_ibi_max::Real = 1.0e10,
state_rebate_per_kw::Real = 0.0,
state_rebate_max::Real = 1.0e10,
utility_ibi_fraction::Real = 0.0,
utility_ibi_max::Real = 1.0e10,
utility_rebate_per_kw::Real = 0.0,
utility_rebate_max::Real = 1.0e10,
production_incentive_per_kwh::Real = 0.0,
production_incentive_max_benefit::Real = 1.0e9,
production_incentive_years::Int = 0,
production_incentive_max_kw::Real = 1.0e9,
fuel_renewable_energy_fraction::Real = 0.0,
emissions_factor_lb_CO2_per_gal::Real = 22.51,
emissions_factor_lb_NOx_per_gal::Real = 0.0775544,
emissions_factor_lb_SO2_per_gal::Real = 0.040020476,
emissions_factor_lb_PM25_per_gal::Real = 0.0,
replacement_year::Int = off_grid_flag ? 10 : analysis_years,
replace_cost_per_kw::Real = off_grid_flag ? installed_cost_per_kw : 0.0
```

Generator replacement costs will not be considered if `Generator.replacement_year`

>= `Financial.analysis_years`

.

## ExistingBoiler

`REopt.ExistingBoiler`

— Type`ExistingBoiler`

is an optional REopt input with the following keys and default values:

```
max_heat_demand_kw::Real=0, # Auto-populated based on SpaceHeatingLoad and DomesticHotWaterLoad inputs
production_type::String = "hot_water", # Can be "steam" or "hot_water"
max_thermal_factor_on_peak_load::Real = 1.25,
efficiency::Real = NaN, # Existing boiler system efficiency - conversion of fuel to usable heating thermal energy. See note below.
fuel_cost_per_mmbtu::Union{<:Real, AbstractVector{<:Real}} = [], # REQUIRED. Can be a scalar, a list of 12 monthly values, or a time series of values for every time step
fuel_type::String = "natural_gas", # "restrict_to": ["natural_gas", "landfill_bio_gas", "propane", "diesel_oil"]
can_supply_steam_turbine::Bool = false,
fuel_renewable_energy_fraction::Real = get(FUEL_DEFAULTS["fuel_renewable_energy_fraction"],fuel_type,0),
emissions_factor_lb_CO2_per_mmbtu::Real = get(FUEL_DEFAULTS["emissions_factor_lb_CO2_per_mmbtu"],fuel_type,0),
emissions_factor_lb_NOx_per_mmbtu::Real = get(FUEL_DEFAULTS["emissions_factor_lb_NOx_per_mmbtu"],fuel_type,0),
emissions_factor_lb_SO2_per_mmbtu::Real = get(FUEL_DEFAULTS["emissions_factor_lb_SO2_per_mmbtu"],fuel_type,0),
emissions_factor_lb_PM25_per_mmbtu::Real = get(FUEL_DEFAULTS["emissions_factor_lb_PM25_per_mmbtu"],fuel_type,0)
```

The maximum size [kW] of the `ExistingBoiler`

will be set based on the peak heat demand as follows:

`max_kw = max_heat_demand_kw * max_thermal_factor_on_peak_load`

The `ExistingBoiler`

's `fuel_cost_per_mmbtu`

field is a required input. The `fuel_cost_per_mmbtu`

can be a scalar, a list of 12 monthly values, or a time series of values for every time step.

Must supply either: `efficiency`

or `production_type`

.

If `efficiency`

is not supplied, the `efficiency`

will be determined based on the `production_type`

. If `production_type`

is not supplied, it defaults to `hot_water`

. The following defaults are used:

```
existing_boiler_efficiency_defaults = Dict(
"hot_water" => 0.8,
"steam" => 0.75
)
```

## CHP

`REopt.CHP`

— Type`CHP`

is an optional REopt input with the following keys and default values:

```
prime_mover::Union{String, Nothing} = nothing # Suggested to inform applicable default cost and performance. "restrict_to": ["recip_engine", "micro_turbine", "combustion_turbine", "fuel_cell"]
fuel_cost_per_mmbtu::Union{<:Real, AbstractVector{<:Real}} = [] # REQUIRED. Can be a scalar, a list of 12 monthly values, or a time series of values for every time step
# Required "custom inputs" if not providing prime_mover:
installed_cost_per_kw::Union{Float64, AbstractVector{Float64}} = NaN # Installed CHP system cost in $/kW (based on rated electric power)
tech_sizes_for_cost_curve::Union{Float64, AbstractVector{Float64}} = NaN # Size of CHP systems corresponding to installed cost input points"
om_cost_per_kwh::Float64 = NaN # CHP non-fuel variable operations and maintenance costs in $/kwh
electric_efficiency_full_load::Float64 = NaN # Electric efficiency of CHP prime-mover at full-load, HHV-basis
electric_efficiency_half_load::Float64 = NaN # Electric efficiency of CHP prime-mover at half-load, HHV-basis
min_turn_down_fraction::Float64 = NaN # Minimum CHP electric loading in fraction of capacity (size_kw)
thermal_efficiency_full_load::Float64 = NaN # CHP fraction of fuel energy converted to hot-thermal energy at full electric load
thermal_efficiency_half_load::Float64 = NaN # CHP fraction of fuel energy converted to hot-thermal energy at half electric load
min_allowable_kw::Float64 = NaN # Minimum CHP size (based on electric) that still allows the model to choose zero (e.g. no CHP system)
cooling_thermal_factor::Float64 = NaN # only needed with cooling load
unavailability_periods::AbstractVector{Dict} = Dict[] # CHP unavailability periods for scheduled and unscheduled maintenance, list of dictionaries with keys of "['month', 'start_week_of_month', 'start_day_of_week', 'start_hour', 'duration_hours'] all values are one-indexed and start_day_of_week uses 1 for Monday, 7 for Sunday
# Optional inputs:
size_class::Union{Int, Nothing} = nothing # CHP size class for using appropriate default inputs, with size_class=0 using an average of all other size class data
min_kw::Float64 = 0.0 # Minimum CHP size (based on electric) constraint for optimization
max_kw::Float64 = NaN # Maximum CHP size (based on electric) constraint for optimization. Determined by heuristic sizing based on heating load or electric load.
fuel_type::String = "natural_gas" # "restrict_to": ["natural_gas", "landfill_bio_gas", "propane", "diesel_oil"]
om_cost_per_kw::Float64 = 0.0 # Annual CHP fixed operations and maintenance costs in $/kw-yr
om_cost_per_hr_per_kw_rated::Float64 = 0.0 # CHP non-fuel variable operations and maintenance costs in $/hr/kw_rated
supplementary_firing_capital_cost_per_kw::Float64 = 150.0 # Installed CHP supplementary firing system cost in $/kW (based on rated electric power)
supplementary_firing_max_steam_ratio::Float64 = 1.0 # Ratio of max fired steam to un-fired steam production. Relevant only for combustion_turbine prime_mover
supplementary_firing_efficiency::Float64 = 0.92 # Thermal efficiency of the incremental steam production from supplementary firing. Relevant only for combustion_turbine prime_mover
standby_rate_per_kw_per_month::Float64 = 0.0 # Standby rate charged to CHP based on CHP electric power size
reduces_demand_charges::Bool = true # Boolean indicator if CHP does not reduce demand charges
can_supply_steam_turbine::Bool=false # If CHP can supply steam to the steam turbine for electric production
macrs_option_years::Int = 5
macrs_bonus_fraction::Float64 = 0.8
macrs_itc_reduction::Float64 = 0.5
federal_itc_fraction::Float64 = 0.3
federal_rebate_per_kw::Float64 = 0.0
state_ibi_fraction::Float64 = 0.0
state_ibi_max::Float64 = 1.0e10
state_rebate_per_kw::Float64 = 0.0
state_rebate_max::Float64 = 1.0e10
utility_ibi_fraction::Float64 = 0.0
utility_ibi_max::Float64 = 1.0e10
utility_rebate_per_kw::Float64 = 0.0
utility_rebate_max::Float64 = 1.0e10
production_incentive_per_kwh::Float64 = 0.0
production_incentive_max_benefit::Float64 = 1.0e9
production_incentive_years::Int = 0
production_incentive_max_kw::Float64 = 1.0e9
can_net_meter::Bool = false
can_wholesale::Bool = false
can_export_beyond_nem_limit::Bool = false
can_curtail::Bool = false
fuel_renewable_energy_fraction::Float64 = FUEL_DEFAULTS["fuel_renewable_energy_fraction"][fuel_type]
emissions_factor_lb_CO2_per_mmbtu::Float64 = FUEL_DEFAULTS["emissions_factor_lb_CO2_per_mmbtu"][fuel_type]
emissions_factor_lb_NOx_per_mmbtu::Float64 = FUEL_DEFAULTS["emissions_factor_lb_NOx_per_mmbtu"][fuel_type]
emissions_factor_lb_SO2_per_mmbtu::Float64 = FUEL_DEFAULTS["emissions_factor_lb_SO2_per_mmbtu"][fuel_type]
emissions_factor_lb_PM25_per_mmbtu::Float64 = FUEL_DEFAULTS["emissions_factor_lb_PM25_per_mmbtu"][fuel_type]
```

See the `get_chp_defaults_prime_mover_size_class()`

function docstring for details on the logic of choosing the type of CHP that is modeled If no information is provided, the default `prime_mover`

is `recip_engine`

and the `size_class`

is 0 which represents the widest range of sizes available.

`fuel_cost_per_mmbtu`

is always required and can be a scalar, a list of 12 monthly values, or a time series of values for every time step

## AbsorptionChiller

`REopt.AbsorptionChiller`

— Type`AbsorptionChiller`

is an optional REopt input with the following keys and default values:

```
thermal_consumption_hot_water_or_steam::Union{String, Nothing} = nothing # Defaults to "hot_water" if chp_prime_mover or boiler_type are not provided
chp_prime_mover::String = "" # Informs thermal_consumption_hot_water_or_steam if not provided
# Defaults for fields below are dependent on thermal_consumption_hot_water_or_steam and max cooling load
installed_cost_per_ton::Union{Float64, Nothing} = nothing # Thermal power-based cost of absorption chiller (3.5 to 1 ton to kwt)
om_cost_per_ton::Union{Float64, Nothing} = nothing # Yearly fixed O&M cost on a thermal power (ton) basis
min_ton::Float64 = 0.0, # Minimum thermal power size constraint for optimization
max_ton::Float64 = BIG_NUMBER, # Maximum thermal power size constraint for optimization
cop_thermal::Union{Float64, Nothing} = nothing, # Absorption chiller system coefficient of performance - conversion of hot thermal power input to usable cooling thermal energy output
cop_electric::Float64 = 14.1, # Absorption chiller electric consumption CoP from cooling tower heat rejection - conversion of electric power input to usable cooling thermal energy outpu
macrs_option_years::Float64 = 0, # MACRS schedule for financial analysis. Set to zero to disable
macrs_bonus_fraction::Float64 = 0 # Percent of upfront project costs to depreciate under MACRS
```

!!! Note To model AbsorptionChiller, there is logic which informs defaults for costs and COP: (i) `thermal_consumption_hot_water_or_steam`

from ["steam", "hot*water"], (ii) `chp*prime*mover` from ["recip*engine", "micro*turbine", "combustion*turbine", "fuel*cell"], or (iii) if (i) and (ii) are not provided, the default `thermal*consumption*hot*water*or*steam`is`

hot*water` The defaults for costs and COP will be populated from data/absorption*chiller/defaults.json, based on the `thermal_consumption_hot_water_or_steam`

or `chp_prime_mover`

. `boiler_type`

is "steam" if `prime_mover`

is "combustion*turbine" and is "hot*water" for all other `chp_prime_mover`

types.

## Boiler

`REopt.Boiler`

— Type`Boiler`

When modeling a heating load an `ExistingBoiler`

model is created even if user does not provide the `ExistingBoiler`

key. The `Boiler`

model is not created by default. If a user provides the `Boiler`

key then the optimal scenario has the option to purchase this new `Boiler`

to meet the heating load in addition to using the `ExistingBoiler`

to meet the heating load.

```
function Boiler(;
min_mmbtu_per_hour::Real = 0.0, # Minimum thermal power size
max_mmbtu_per_hour::Real = 0.0, # Maximum thermal power size
efficiency::Real = 0.8, # boiler system efficiency - conversion of fuel to usable heating thermal energy
fuel_cost_per_mmbtu::Union{<:Real, AbstractVector{<:Real}} = 0.0,
macrs_option_years::Int = 0, # MACRS schedule for financial analysis. Set to zero to disable
macrs_bonus_fraction::Real = 0.0, # Fraction of upfront project costs to depreciate under MACRS
installed_cost_per_mmbtu_per_hour::Real = 293000.0, # Thermal power-based cost
om_cost_per_mmbtu_per_hour::Real = 2930.0, # Thermal power-based fixed O&M cost
om_cost_per_mmbtu::Real = 0.0, # Thermal energy-based variable O&M cost
fuel_type::String = "natural_gas", # "restrict_to": ["natural_gas", "landfill_bio_gas", "propane", "diesel_oil", "uranium"]
can_supply_steam_turbine::Bool = true # If the boiler can supply steam to the steam turbine for electric production
)
```

## HotThermalStorage

`REopt.HotThermalStorageDefaults`

— Type`HotThermalStorage`

is an optional REopt input with the following keys and default values:

```
min_gal::Float64 = 0.0
max_gal::Float64 = 0.0
hot_water_temp_degF::Float64 = 180.0
cool_water_temp_degF::Float64 = 160.0
internal_efficiency_fraction::Float64 = 0.999999
soc_min_fraction::Float64 = 0.1
soc_init_fraction::Float64 = 0.5
installed_cost_per_gal::Float64 = 1.50
thermal_decay_rate_fraction::Float64 = 0.0004
om_cost_per_gal::Float64 = 0.0
macrs_option_years::Int = 7
macrs_bonus_fraction::Float64 = 0.8
macrs_itc_reduction::Float64 = 0.5
total_itc_fraction::Float64 = 0.3
total_rebate_per_kwh::Float64 = 0.0
```

## ColdThermalStorage

`REopt.ColdThermalStorageDefaults`

— TypeCold thermal energy storage sytem; specifically, a chilled water system used to meet thermal cooling loads.

`ColdThermalStorage`

is an optional REopt input with the following keys and default values:

```
min_gal::Float64 = 0.0
max_gal::Float64 = 0.0
hot_water_temp_degF::Float64 = 56.0 # Warmed-side return water temperature from the cooling load to the ColdTES (top of tank)
cool_water_temp_degF::Float64 = 44.0 # Chilled-side supply water temperature from ColdTES (bottom of tank) to the cooling load
internal_efficiency_fraction::Float64 = 0.999999 # Thermal losses due to mixing from thermal power entering or leaving tank
soc_min_fraction::Float64 = 0.1 # Minimum allowable TES thermal state of charge
soc_init_fraction::Float64 = 0.5 # TES thermal state of charge at first hour of optimization
installed_cost_per_gal::Float64 = 1.50 # Thermal energy-based cost of TES (e.g. volume of the tank)
thermal_decay_rate_fraction::Float64 = 0.0004 # Thermal loss (gain) rate as a fraction of energy storage capacity, per hour (frac*energy_capacity/hr = kw_thermal)
om_cost_per_gal::Float64 = 0.0 # Yearly fixed O&M cost dependent on storage energy size
macrs_option_years::Int = 7
macrs_bonus_fraction::Float64 = 0.8
macrs_itc_reduction::Float64 = 0.5
total_itc_fraction::Float64 = 0.3
total_rebate_per_kwh::Float64 = 0.0
```

## DomesticHotWaterLoad

`REopt.DomesticHotWaterLoad`

— Type`DomesticHotWaterLoad`

is an optional REopt input with the following keys and default values:

```
doe_reference_name::String = "",
blended_doe_reference_names::Array{String, 1} = String[],
blended_doe_reference_percents::Array{<:Real,1} = Real[],
addressable_load_fraction::Union{<:Real, AbstractVector{<:Real}} = 1.0, # Fraction of input fuel load which is addressable by heating technologies. Can be a scalar or vector with length aligned with use of monthly_mmbtu or fuel_loads_mmbtu_per_hour.
annual_mmbtu::Union{Real, Nothing} = nothing,
monthly_mmbtu::Array{<:Real,1} = Real[],
fuel_loads_mmbtu_per_hour::Array{<:Real,1} = Real[] # Vector of hot water fuel loads [mmbtu/hour]. Length must equal 8760 * `Settings.time_steps_per_hour`
```

There are many ways in which a DomesticHotWaterLoad can be defined:

- When using either
`doe_reference_name`

or`blended_doe_reference_names`

in an`ElectricLoad`

one only needs to provide the input key "DomesticHotWaterLoad" in the`Scenario`

(JSON or Dict). In this case the values from DoE reference names from the`ElectricLoad`

will be used to define the`DomesticHotWaterLoad`

. - One can provide the
`doe_reference_name`

or`blended_doe_reference_names`

directly in the`DomesticHotWaterLoad`

key within the`Scenario`

. These values can be combined with the`annual_mmbtu`

or`monthly_mmbtu`

inputs to scale the DoE reference profile(s). - One can provide the
`fuel_loads_mmbtu_per_hour`

value in the`DomesticHotWaterLoad`

key within the`Scenario`

.

Hot water and space heating thermal "load" inputs are in terms of energy input required (boiler fuel), not the actual energy demand. The fuel energy is multiplied by the boiler_efficiency to get the actual energy demand.

## SpaceHeatingLoad

`REopt.SpaceHeatingLoad`

— Type`SpaceHeatingLoad`

is an optional REopt input with the following keys and default values:

```
doe_reference_name::String = "",
blended_doe_reference_names::Array{String, 1} = String[],
blended_doe_reference_percents::Array{<:Real,1} = Real[],
addressable_load_fraction::Union{<:Real, AbstractVector{<:Real}} = 1.0, # Fraction of input fuel load which is addressable by heating technologies. Can be a scalar or vector with length aligned with use of monthly_mmbtu or fuel_loads_mmbtu_per_hour.
annual_mmbtu::Union{Real, Nothing} = nothing,
monthly_mmbtu::Array{<:Real,1} = Real[],
fuel_loads_mmbtu_per_hour::Array{<:Real,1} = Real[] # Vector of space heating fuel loads [mmbtu/hr]. Length must equal 8760 * `Settings.time_steps_per_hour`
```

There are many ways to define a `SpaceHeatingLoad`

:

- a time-series via the
`fuel_loads_mmbtu_per_hour`

, - scaling a DoE Commercial Reference Building (CRB) profile or a blend of CRB profiles to either the
`annual_mmbtu`

or`monthly_mmbtu`

values; - or using the
`doe_reference_name`

or`blended_doe_reference_names`

from the`ElectricLoad`

.

When using an `ElectricLoad`

defined from a `doe_reference_name`

or `blended_doe_reference_names`

one only needs to provide an empty Dict in the scenario JSON to add a `SpaceHeatingLoad`

to a `Scenario`

, i.e.:

```
...
"ElectricLoad": {"doe_reference_name": "MidriseApartment"},
"SpaceHeatingLoad" : {},
...
```

In this case the values provided for `doe_reference_name`

, or `blended_doe_reference_names`

and `blended_doe_reference_percents`

are copied from the `ElectricLoad`

to the `SpaceHeatingLoad`

.

Hot water and space heating thermal "load" inputs are in terms of energy input required (boiler fuel), not the actual energy demand. The fuel energy is multiplied by the boiler_efficiency to get the actual energy demand.

## FlexibleHVAC

`REopt.FlexibleHVAC`

— Type`FlexibleHVAC`

is an optional REopt input with the following keys and default values:

```
system_matrix::AbstractMatrix{Float64} # N x N, with N states (temperatures in RC network)
input_matrix::AbstractMatrix{Float64} # N x M, with M inputs
exogenous_inputs::AbstractMatrix{Float64} # M x T, with T time steps
control_node::Int64
initial_temperatures::AbstractVector{Float64}
temperature_upper_bound_degC::Union{Real, Nothing}
temperature_lower_bound_degC::Union{Real, Nothing}
installed_cost::Float64
```

Every model with `FlexibleHVAC`

includes a preprocessing step to calculate the business-as-usual (BAU) cost of meeting the thermal loads using a dead-band controller. The BAU cost is then used in the binary decision for purchasing the `FlexibleHVAC`

system: if the `FlexibleHVAC`

system is purchased then the heating and cooling costs are determined by the HVAC dispatch that minimizes the lifecycle cost of energy. If the `FlexibleHVAC`

system is not purchased then the BAU heating and cooling costs must be paid.

There are two construction methods for `FlexibleHVAC`

, which depend on whether or not the data was loaded in from a JSON file. The issue with data from JSON is that the vector-of-vectors from the JSON file must be appropriately converted to Julia Matrices. When loading in a Scenario from JSON that includes a `FlexibleHVAC`

model, if you include the `flex_hvac_from_json`

argument to the `Scenario`

constructor then the conversion to Matrices will be done appropriately.

At least one of the inputs for `temperature_upper_bound_degC`

or `temperature_lower_bound_degC`

must be provided to evaluate the `FlexibleHVAC`

option. For example, if only `temperature_lower_bound_degC`

is provided then only a heating system will be evaluated. Also, the heating system will only be used (or purchased) if the `exogenous_inputs`

lead to the temperature at the `control_node`

going below the `temperature_lower_bound_degC`

.

The `ExistingChiller`

is electric and so its operating cost is determined by the `ElectricTariff`

.

BAU heating costs will be determined by the `ExistingBoiler`

inputs, including`fuel_cost_per_mmbtu`

.

## ExistingChiller

`REopt.ExistingChiller`

— Type`ExistingChiller`

is an optional REopt input with the following keys and default values:

```
loads_kw_thermal::Vector{<:Real},
cop::Union{Real, Nothing} = nothing,
max_thermal_factor_on_peak_load::Real=1.25
```

The maximum size [kW] of the `ExistingChiller`

will be set based on the peak thermal load as follows:

`max_kw = maximum(loads_kw_thermal) * max_thermal_factor_on_peak_load`

## GHP

`REopt.GHP`

— TypeGHP evaluations typically require the `GhpGhx.jl`

package to be loaded unless the `GhpGhx.jl`

package was already used externally to create `inputs_dict["GHP"]["ghpghx_responses"]`

. See the Home page under "Additional package loading for GHP" for instructions. This `GHP`

struct uses the response from `GhpGhx.jl`

to process input parameters for REopt including additional cost parameters for `GHP`

.

`GHP`

struct with outer constructor:

```
require_ghp_purchase::Union{Bool, Int64} = false # 0 = false, 1 = true
installed_cost_heatpump_per_ton::Float64 = 1075.0
heatpump_capacity_sizing_factor_on_peak_load::Float64 = 1.1
installed_cost_ghx_per_ft::Float64 = 14.0
installed_cost_building_hydronic_loop_per_sqft = 1.70
om_cost_per_sqft_year::Float64 = -0.51
building_sqft::Float64 # Required input
space_heating_efficiency_thermal_factor::Float64 = NaN # Default depends on building and location
cooling_efficiency_thermal_factor::Float64 = NaN # Default depends on building and location
ghpghx_response::Dict = Dict()
can_serve_dhw::Bool = false
macrs_option_years::Int = 5
macrs_bonus_fraction::Float64 = 0.8
macrs_itc_reduction::Float64 = 0.5
federal_itc_fraction::Float64 = 0.3
federal_rebate_per_ton::Float64 = 0.0
federal_rebate_per_kw::Float64 = 0.0
state_ibi_fraction::Float64 = 0.0
state_ibi_max::Float64 = 1.0e10
state_rebate_per_ton::Float64 = 0.0
state_rebate_per_kw::Float64 = 0.0
state_rebate_max::Float64 = 1.0e10
utility_ibi_fraction::Float64 = 0.0
utility_ibi_max::Float64 = 1.0e10
utility_rebate_per_ton::Float64 = 0.0
utility_rebate_per_kw::Float64 = 0.0
utility_rebate_max::Float64 = 1.0e10
# Processed data from inputs and results of GhpGhx.jl
heating_thermal_kw::Vector{Float64} = []
cooling_thermal_kw::Vector{Float64} = []
yearly_electric_consumption_kw::Vector{Float64} = []
peak_combined_heatpump_thermal_ton::Float64 = NaN
# Intermediate parameters for cost processing
tech_sizes_for_cost_curve::Union{Float64, AbstractVector{Float64}} = NaN
installed_cost_per_kw::Union{Float64, AbstractVector{Float64}} = NaN
heatpump_capacity_ton::Float64 = NaN
# Process and populate these parameters needed more directly by the model
installed_cost::Float64 = NaN
om_cost_year_one::Float64 = NaN
```

## SteamTurbine

`REopt.SteamTurbine`

— Type`SteamTurbine`

is an optional REopt input with the following keys and default values:

```
size_class::Union{Int64, Nothing} = nothing
min_kw::Float64 = 0.0
max_kw::Float64 = 0.0
electric_produced_to_thermal_consumed_ratio::Float64 = NaN
thermal_produced_to_thermal_consumed_ratio::Float64 = NaN
is_condensing::Bool = false
inlet_steam_pressure_psig::Float64 = NaN
inlet_steam_temperature_degF::Float64 = NaN
inlet_steam_superheat_degF::Float64 = 0.0
outlet_steam_pressure_psig::Float64 = NaN
outlet_steam_min_vapor_fraction::Float64 = 0.8 # Minimum practical vapor fraction of steam at the exit of the steam turbine
isentropic_efficiency::Float64 = NaN
gearbox_generator_efficiency::Float64 = NaN # Combined gearbox (if applicable) and electric motor/generator efficiency
net_to_gross_electric_ratio::Float64 = NaN # Efficiency factor to account for auxiliary loads such as pumps, controls, lights, etc
installed_cost_per_kw::Float64 = NaN # Installed cost based on electric power capacity
om_cost_per_kw::Float64 = 0.0 # Fixed O&M cost based on electric power capacity
om_cost_per_kwh::Float64 = NaN # Variable O&M based on electric energy produced
can_net_meter::Bool = false
can_wholesale::Bool = false
can_export_beyond_nem_limit::Bool = false
can_curtail::Bool = false
macrs_option_years::Int = 0
macrs_bonus_fraction::Float64 = 1.0
```