REopt Inputs

Inputs to run_reopt can be provided in one of four formats:

  1. a file path (string) to a JSON file,
  2. a Dict,
  3. using the Scenario struct, or
  4. 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.ScenarioType
Scenario(d::Dict; flex_hvac_from_json=false)

A Scenario struct can contain the following keys:

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).

Note

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).

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Scenario(fp::String)

Consruct Scenario from filepath fp to JSON with keys aligned with the Scenario(d::Dict) method.

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BAUScenario

The Business-as-usual (BAU) inputs are automatically created based on the BAUScenario struct when a user supplies two JuMP.Models 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.BAUInputsFunction
BAUInputs(p::REoptInputs)

TheBAUInputs (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
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Settings

REopt.SettingsType

Captures 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
    solver_name::String = "HiGHS" # solver used to obtain a solution to model instance. available options: ["HiGHS", "Cbc", "CPLEX", "Xpress"]
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Site

REopt.SiteType

Inputs 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, # The minimum number consecutive timesteps that load must be fully met once an outage begins. Only applies to multiple outage modeling using inputs outage_start_time_steps and outage_durations.
    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,
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ElectricLoad

REopt.ElectricLoadType

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[], # Values should be between 0-1 and sum to 1.0
    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.
Required inputs

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
  • LasVegas
  • 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
  • FlatLoad245 # constant load all hours of the weekdays
  • FlatLoad167 # two 8-hour shifts for all days of the year; 6-10 a.m.
  • FlatLoad165 # two 8-hour shifts for the weekdays; 6-10 a.m.
  • FlatLoad87 # one 8-hour shift for all days of the year; 9 a.m.-5 p.m.
  • FlatLoad85 # 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.

Year

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.

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ElectricTariff

REopt.ElectricTariffMethod

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}
    }
Export Rates

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

  1. NEM (Net Energy Metering) - set to the energy rate (or tier with the lowest energy rate, if tiered)
  2. WHL (Wholesale) - set to wholesale_rate
  3. EXC (Excess, beyond NEM) - set to exportratebeyondnetmetering_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.

NEM input

The NEM boolean is determined by the ElectricUtility.net_metering_limit_kw. There is no need to pass in a NEM value.

Demand Lookback Inputs

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 demandlookbackpercent.

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Financial

REopt.FinancialType

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 = 0.017,
    existing_boiler_fuel_cost_escalation_rate_fraction::Float64 = 0.015, 
    boiler_fuel_cost_escalation_rate_fraction::Real = 0.015,
    chp_fuel_cost_escalation_rate_fraction::Real = 0.015,
    generator_fuel_cost_escalation_rate_fraction::Real = 0.012,
    offtaker_tax_rate_fraction::Real = 0.26, # combined state and federal tax rate
    offtaker_discount_rate_fraction::Real = 0.0638,
    third_party_ownership::Bool = false,
    owner_tax_rate_fraction::Real = 0.26, # combined state and federal tax rate
    owner_discount_rate_fraction::Real = 0.0638,
    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, # Default data from EASIUR based on location
    SO2_onsite_fuelburn_cost_per_tonne::Union{Nothing,Real} = nothing, # Default data from EASIUR based on location
    PM25_onsite_fuelburn_cost_per_tonne::Union{Nothing,Real} = nothing, # Default data from EASIUR based on location
    NOx_cost_escalation_rate_fraction::Union{Nothing,Real} = nothing, # Default data from EASIUR based on location
    SO2_cost_escalation_rate_fraction::Union{Nothing,Real} = nothing, # Default data from EASIUR based on location
    PM25_cost_escalation_rate_fraction::Union{Nothing,Real} = nothing # Default data from EASIUR based on location
Third party financing

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
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ElectricUtility

REopt.ElectricUtilityType

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

    net_metering_limit_kw::Real = 0, # Upper limit on the total capacity of technologies that can participate in net metering agreement.
    interconnection_limit_kw::Real = 1.0e9, # Limit on total electric system capacity size that can be interconnected to the grid 
    allow_simultaneous_export_import::Bool = true,  # if true the site has two meters (in effect). Set to false if the export rate is greater than the cost of energy (otherwise, REopt will export before meeting site load).
    
    # Single Outage Modeling Inputs (Outage Modeling Option 1)
    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
        
    # Multiple Outage Modeling Inputs (Outage Modeling Option 2): 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],
    
    ### Grid Climate Emissions Inputs ### 
    # Climate Option 1 (Default): Use levelized emissions data from NREL's Cambium database by specifying the following fields:
    cambium_scenario::String = "Mid-case", # Cambium Scenario for evolution of electricity sector (see Cambium documentation for descriptions).
        ## Options: ["Mid-case",  "Mid-case with tax credit expiration",  "Low renewable energy cost", "Low renewable energy cost with tax credit expiration",   "High renewable energy cost", "High electrification",  "Low natrual gas prices", "High natrual gas prices", "Mid-case with 95% decarbonization by 2050",  "Mid-case with 100% decarbonization by 2035"]
    cambium_location_type::String =  "GEA Regions", # Geographic boundary at which emissions are calculated. Options: ["Nations", "GEA Regions", "States"] 
    cambium_metric_col::String =  "lrmer_co2e", # Emissions metric used. Default: "lrmer_co2e" - Long-run marginal emissions rate for CO2-equivalant, combined combustion and pre-combustion emissions rates. Options: See metric definitions and names in the Cambium documentation
    cambium_start_year::Int = 2024, # First year of operation of system. Emissions will be levelized starting in this year for the duration of cambium_levelization_years. # Options: any year 2023 through 2050.
    cambium_levelization_years::Int = analysis_years, # Expected lifetime or analysis period of the intervention being studied. Emissions will be averaged over this period.
    cambium_grid_level::String = "enduse", # Options: ["enduse", "busbar"]. Busbar refers to point where bulk generating stations connect to grid; enduse refers to point of consumption (includes distribution loss rate). 

    # Climate Option 2: Use CO2 emissions data from the EPA's AVERT based on the AVERT emissions region and specify annual percent decrease
    co2_from_avert::Bool = false, # Default is to use Cambium data for CO2 grid emissions. Set to `true` to instead use data from the EPA's AVERT database. 

    # Climate Option 3: Provide your own custom emissions factors for CO2 and specify annual percent decrease  
    emissions_factor_series_lb_CO2_per_kwh::Union{Real,Array{<:Real,1}} = Float64[], # Custom CO2 emissions profile. Can be scalar or timeseries (aligned with time_steps_per_hour). Ensure emissions year aligns with load year.

    # Used with Climate Options 2 or 3: Annual percent decrease in CO2 emissions factors
    emissions_factor_CO2_decrease_fraction::Union{Nothing, Real} = co2_from_avert || length(emissions_factor_series_lb_CO2_per_kwh) > 0  ? EMISSIONS_DECREASE_DEFAULTS["CO2e"] : nothing , # Annual percent decrease in the total annual CO2 emissions rate of the grid. A negative value indicates an annual increase.

    ### Grid Health Emissions Inputs ###
    # Health Option 1 (Default): Use health emissions data from the EPA's AVERT based on the AVERT emissions region and specify annual percent decrease
    avert_emissions_region::String = "", # AVERT emissions region. Default is based on location, or can be overriden by providing region here.

    # Health Option 2: Provide your own custom emissions factors for health emissions and specify annual percent decrease:
    emissions_factor_series_lb_NOx_per_kwh::Union{Real,Array{<:Real,1}} = Float64[], # Custom NOx emissions profile. Can be scalar or timeseries (aligned with time_steps_per_hour). Ensure emissions year aligns with load year.
    emissions_factor_series_lb_SO2_per_kwh::Union{Real,Array{<:Real,1}} = Float64[], # Custom SO2 emissions profile. Can be scalar or timeseries (aligned with time_steps_per_hour). Ensure emissions year aligns with load year.
    emissions_factor_series_lb_PM25_per_kwh::Union{Real,Array{<:Real,1}} = Float64[], # Custom PM2.5 emissions profile. Can be scalar or timeseries (aligned with time_steps_per_hour). Ensure emissions year aligns with load year.

    # Used with Health Options 1 or 2: Annual percent decrease in health emissions factors: 
    emissions_factor_NOx_decrease_fraction::Real = EMISSIONS_DECREASE_DEFAULTS["NOx"], 
    emissions_factor_SO2_decrease_fraction::Real = EMISSIONS_DECREASE_DEFAULTS["SO2"],
    emissions_factor_PM25_decrease_fraction::Real = EMISSIONS_DECREASE_DEFAULTS["PM25"]
Outage modeling

Indexing

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, outagestarttimestep = 1 and outageendtimestep = 3. To model a 1-hour outage from 6AM to 7AM on Jan 1, outagestarttimestep = 7 and outageendtimestep = 7.

Can use either singular or multiple outage modeling inputs, not both

Cannot supply singular outagestart(or end)timestep and multiple outagestarttimesteps. Must use one or the other.

Using minresiltime_steps to ensure critical load is met

With multiple outage modeling, the model will choose to meet the critical loads only as cost-optimal. This trade-off depends on cost of not meeting load (see Financial | value_of_lost_load_per_kwh) and the costs of meeting load, such as microgrid upgrade cost (see Financial | microgrid_upgrade_cost_fraction), fuel costs, and additional DER capacity. To ensure that REopt recommends a system that can meet critical loads during a defined outage period, specify this duration using Site | min_resil_time_steps.

Outage costs will be included in NPV and LCC

Note that when using multiple outage modeling, the expected outage cost will be included in the net present value and lifecycle cost calculations (for both the BAU and optimized case). You can set Financial | value_of_lost_load_per_kwh to 0 to ignore these costs. However, doing so will remove incentive for the model to meet critical loads during outages, and you should therefore consider also specifying Site | min_resil_time_steps. You can alternatively post-process results to remove lifecycle_outage_cost from the NPV and LCCs.

Outages, Emissions, and Renewable Energy Calculations

If a single deterministic outage is modeled using outagestarttimestep and outageendtimestep, emissions and renewable energy percentage calculations and constraints will factor in this outage. If stochastic outages are modeled using outagestarttimesteps, outagedurations, and outage_probabilities, emissions and renewable energy percentage calculations and constraints will not consider outages.

MPC vs. Non-MPC

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.

Climate and Health Emissions Modeling

Climate and health-related emissions from grid electricity come from two different data sources and have different REopt inputs as described below.

Climate Emissions

  • For sites in the contiguous United States:
    • Default climate-related emissions factors come from NREL's Cambium database (Current version: 2022)
      • By default, REopt uses levelized long-run marginal emission rates for CO2-equivalent (CO2e) emissions for the region in which the site is located. By default, the emissions rates are levelized over the analysis period (e.g., from 2024 through 2048 for a 25-year analysis)
      • The inputs to the Cambium API request can be modified by the user based on emissions accounting needs (e.g., can change "lifetime" to 1 to analyze a single year's emissions)
      • Note for analysis periods extending beyond 2050: Values beyond 2050 are estimated with the 2050 values. Analysts are advised to use caution when selecting values that place significant weight on 2050 (e.g., greater than 50%)
    • Users can alternatively choose to use emissions factors from the EPA's AVERT by setting co2_from_avert to true
  • For Alaska and HI: Grid CO2e emissions rates for AK and HI come from the eGRID database. These are single values repeated throughout the year. The default annual emissionsfactorCO2decreasefraction will be applied to this rate to account for future greening of the grid.
  • For sites outside of the United States: We currently do not have default grid emissions rates for sites outside of the U.S. For these sites, users must supply custom emissions factor series (e.g., emissionsfactorserieslbCO2perkwh) and projected emissions decreases (e.g., emissionsfactorCO2decreasefraction).

Health Emissions

  • For sites in the contiguous United States: health-related emissions factors (PM2.5, SO2, and NOx) come from the EPA's AVERT database.
  • The default avert_emissions_region input is determined by the site's latitude and longitude.

Alternatively, you may input the desired AVERT 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)"]

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PV

REopt.PVType

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 == 0 || array_type == 1) ? 20 : 0, # tilt = 20 for fixed rooftop arrays (1) or ground-mount (2) ; tilt = 0 for everything else (3 and 4)
    module_type::Int=0, # PV module type (0: Standard; 1: Premium; 2: Thin Film)
    losses::Real=0.14, # System losses
    azimuth::Real = latitude≥0 ? 180 : 0, # set azimuth to zero for southern hemisphere
    gcr::Real=0.4,  # Ground coverage ratio
    radius::Int=0, # Radius, in miles, to use when searching for the closest climate data station. Use zero to use the closest station regardless of the distance
    name::String="PV", # for use with multiple pvs 
    location::String="both", # one of ["roof", "ground", "both"]
    existing_kw::Real=0,
    min_kw::Real=0,
    max_kw::Real=1.0e9, # max new capacity (beyond existing_kw)
    installed_cost_per_kw::Real=1790.0,
    om_cost_per_kw::Real=18.0,
    degradation_fraction::Real=0.005,
    macrs_option_years::Int = 5,
    macrs_bonus_fraction::Real = 0.6,
    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

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

PV tilt and aziumth

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.

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Wind

REopt.WindType

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 = 36.0,
    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 = 0.6,
    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.
Default assumptions

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"=> 6339.0,
    "commercial"=> 4760.0,
    "medium"=> 3137.0,
    "large"=> 2386.0
)

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 value inputs

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 sizing and land constraint

Wind size is constrained by Site.landacres, assuming a power density of Wind.acresper_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).

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ElectricStorage

REopt.ElectricStorageDefaultsType

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_min_applies_during_outages::Bool = false
    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 = 910.0
    installed_cost_per_kwh::Real = 455.0
    replace_cost_per_kw::Real = 715.0
    replace_cost_per_kwh::Real = 318.0
    inverter_replacement_year::Int = 10
    battery_replacement_year::Int = 10
    macrs_option_years::Int = 7
    macrs_bonus_fraction::Float64 = 0.6
    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
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REopt.DegradationType
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.

Warn

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.

Note

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.

Warn

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.

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Generator

REopt.GeneratorType

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

    only_runs_during_grid_outage::Bool = true,
    existing_kw::Real = 0,
    min_kw::Real = 0,
    max_kw::Real = 1.0e6,
    installed_cost_per_kw::Real = off_grid_flag ? 880 : only_runs_during_grid_outage ? 650.0 : 800.0,
    om_cost_per_kw::Real = off_grid_flag ? 10.0 : 20.0,
    om_cost_per_kwh::Real = 0.0,
    fuel_cost_per_gallon::Real = 3.61,
    electric_efficiency_full_load::Real = 0.322,
    electric_efficiency_half_load::Real = electric_efficiency_full_load,
    fuel_avail_gal::Real = 1.0e9,
    fuel_higher_heating_value_kwh_per_gal::Real = 40.7,
    min_turn_down_fraction::Real = off_grid_flag ? 0.15 : 0.0,
    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 = 0.0,
    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 = 22.58, # CO2e
    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
Replacement costs

Generator replacement costs will not be considered if Generator.replacement_year >= Financial.analysis_years.

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ExistingBoiler

REopt.ExistingBoilerType

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,
    retire_in_optimal::Bool = false,  # Do NOT use in the optimal case (still used in BAU)
    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)
    can_serve_dhw::Bool = true # If ExistingBoiler can supply heat to the domestic hot water load
    can_serve_space_heating::Bool = true # If ExistingBoiler can supply heat to the space heating load
    can_serve_process_heat::Bool = true # If ExistingBoiler can supply heat to the space heating load
Max ExistingBoiler size

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
ExistingBoiler operating costs

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.

Determining `efficiency`

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
)
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CHP

REopt.CHPType

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
    unavailability_hourly::AbstractVector{Int64} = Int64[] # Hourly 8760 profile of unavailability (1) and availability (0)

    # 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 
    can_serve_dhw::Bool = true # If CHP can supply heat to the domestic hot water load
    can_serve_space_heating::Bool = true # If CHP can supply heat to the space heating load
    can_serve_process_heat::Bool = true # If CHP can supply heat to the process heating load
    is_electric_only::Bool = false # If CHP is a prime generator that does not supply heat

    macrs_option_years::Int = 5
    macrs_bonus_fraction::Float64 = 0.6
    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]
Defaults and required inputs

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

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AbsorptionChiller

REopt.AbsorptionChillerType

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
    heating_load_input::Union{String, Nothing} = nothing # heating load that serves as input to absorption chiller

!!! Note To model AbsorptionChiller, there is logic which informs defaults for costs and COP: (i) thermal_consumption_hot_water_or_steam from ["steam", "hotwater"], (ii) `chpprimemover` from ["recipengine", "microturbine", "combustionturbine", "fuelcell"], or (iii) if (i) and (ii) are not provided, the default `thermalconsumptionhotwaterorsteamishotwater` The defaults for costs and COP will be populated from data/absorptionchiller/defaults.json, based on the thermal_consumption_hot_water_or_steam or chp_prime_mover. boiler_type is "steam" if prime_mover is "combustionturbine" and is "hotwater" for all other chp_prime_mover types.

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Boiler

REopt.BoilerType
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
    can_serve_dhw::Bool = true # If Boiler can supply heat to the domestic hot water load
    can_serve_space_heating::Bool = true # If Boiler can supply heat to the space heating load
    can_serve_process_heat::Bool = true # If Boiler can supply heat to the process heating load
    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)
)
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HotThermalStorage

REopt.HotThermalStorageDefaultsType

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 = 0.6
    macrs_itc_reduction::Float64 = 0.5
    total_itc_fraction::Float64 = 0.3
    total_rebate_per_kwh::Float64 = 0.0
    can_serve_dhw::Bool = true
    can_serve_space_heating:Bool = true
    can_serve_process_heat::Bool = false
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ColdThermalStorage

REopt.ColdThermalStorageDefaultsType

Cold 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 = 0.6
    macrs_itc_reduction::Float64 = 0.5
    total_itc_fraction::Float64 = 0.3
    total_rebate_per_kwh::Float64 = 0.0
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DomesticHotWaterLoad

REopt.DomesticHotWaterLoadType

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::Any = 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`
    existing_boiler_efficiency::Real = NaN

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

  1. 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.
  2. 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).
  3. One can provide the fuel_loads_mmbtu_per_hour value in the DomesticHotWaterLoad key within the Scenario.
Hot water loads

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.

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SpaceHeatingLoad

REopt.SpaceHeatingLoadType

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::Any = 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`
    existing_boiler_efficiency::Real = NaN

There are many ways to define a SpaceHeatingLoad:

  1. a time-series via the fuel_loads_mmbtu_per_hour,
  2. scaling a DoE Commercial Reference Building (CRB) profile or a blend of CRB profiles to either the annual_mmbtu or monthly_mmbtu values;
  3. 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.

Space heating loads

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.

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ProcessHeatLoad

REopt.ProcessHeatLoadType

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

    annual_mmbtu::Union{Real, Nothing} = nothing
    fuel_loads_mmbtu_per_hour::Array{<:Real,1} = Real[]

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

  1. One can provide the fuel_loads_mmbtu_per_hour value in the ProcessHeatLoad key within the Scenario.
  2. One can provide the annual_mmbtu value in the ProcessHeatLoad key within the Scenario; this assumes a flat load.
Process heat loads

These loads are presented in terms of process heat required without regard to the efficiency of the input heating, unlike the hot-water and space heating loads which are provided in terms of fuel input.

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FlexibleHVAC

REopt.FlexibleHVACType

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.

Note

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.

Note

The ExistingChiller is electric and so its operating cost is determined by the ElectricTariff.

Note

BAU heating costs will be determined by the ExistingBoiler inputs, includingfuel_cost_per_mmbtu.

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ExistingChiller

REopt.ExistingChillerType

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
Max ExistingChiller size

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
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GHP

Missing docstring.

Missing docstring for REopt.GHP. Check Documenter's build log for details.

SteamTurbine

REopt.SteamTurbineType

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 = 1.0e9
    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
    can_serve_dhw::Bool = true
    can_serve_space_heating::Bool = true
    can_serve_process_heat::Bool = true

    macrs_option_years::Int = 0
    macrs_bonus_fraction::Float64 = 0.0    
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ElectricHeater

REopt.ElectricHeaterType

ElectricHeater

If a user provides the ElectricHeater key then the optimal scenario has the option to purchase this new ElectricHeater to meet the heating load in addition to using the ExistingBoiler to meet the heating load.

function ElectricHeater(;
    min_mmbtu_per_hour::Real = 0.0, # Minimum thermal power size
    max_mmbtu_per_hour::Real = BIG_NUMBER, # Maximum thermal power size
    installed_cost_per_mmbtu_per_hour::Union{Real, nothing} = nothing, # Thermal power-based cost
    om_cost_per_mmbtu_per_hour::Union{Real, nothing} = nothing, # Thermal power-based fixed O&M cost
    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
    can_supply_steam_turbine::Union{Bool, nothing} = nothing # If the boiler can supply steam to the steam turbine for electric production
    cop::Union{Real, nothing} = nothing # COP of the heating (i.e., thermal produced / electricity consumed)
    can_serve_dhw::Bool = true # If electric heater can supply heat to the domestic hot water load
    can_serve_space_heating::Bool = true # If electric heater can supply heat to the space heating load
    can_serve_process_heat::Bool = true # If electric heater can supply heat to the process heating load
)
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