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425d958
New updates to the nuclear thermal plant model
Apr 14, 2026
3d0af8e
Updates including test location, but test is not ready to be run yet
Apr 21, 2026
902d1ee
Updates with separate nuclear, HTSE, definitions but intending to hav…
Apr 28, 2026
6c8dd2a
May 12 update to nuclear and HTSE new models
May 12, 2026
3831202
Updates to the nuclear-htse system with the new configuration startin…
May 14, 2026
5d148ee
A couple more adjustments that should allow for the HTSE unit to demo…
May 14, 2026
13f00c2
merge in nuclear+htse branch
jaredthomas68 May 19, 2026
7df8f82
update for current h2i develop
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8c0d981
working example, LCOH too low
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89c72e6
general connection splitting
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resolve conflicts
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520ff99
remove split indices work
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aee36a3
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e254417
add tests for nuclear/htse example
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updates to work with new changes to H2I
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add test
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f459eff
add grid sell and demand component, leave heat demand commented out f…
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adjust connections to not include heat demand
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1cc6659
Some modifiers on nuclear units, and step changes to update HTSE unit
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update units of heat
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include h2 storage
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d3580f9
HTSE and nuclear model updates, HTSE system now outputs consumed elec…
Jun 25, 2026
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Continued updates
Jun 25, 2026
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Nuclear & HTSE updates, along with test value updated
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refining nuclear htse example system
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Adding figures to documentation on the thermal nuclear and HTSE models.
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combine nuclear tech model doc pages
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correct rate units from galUS to galUS/h
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1 change: 1 addition & 0 deletions CHANGELOG.md
Original file line number Diff line number Diff line change
Expand Up @@ -73,6 +73,7 @@
- Updated `commodity_sell_price` input to `ProFastNPV` to be per year of the plant life. Also updated `BasicProFASTParameterConfig.as_dict()` so explicitly input escalation values are not overwritten to the general inflation rate [PR 799](https://github.com/NatLabRockies/H2Integrate/pull/799)
- Added `calc_azimuth_angle()` to `PYSAMSolarPlantPerformanceModel` to provide default azimuth angle based on whether the site is in the northern or southern hemisphere [PR 806](https://github.com/NatLabRockies/H2Integrate/pull/806)
- Corrected water rate units in pipe feedstock from galUS to galUS/h [PR 813](https://github.com/NatLabRockies/H2Integrate/pull/813)
- Added a thermal-nuclear (light-water reactor) model and a high-temperature steam electrolysis model. [PR 807](https://github.com/NatLabRockies/H2Integrate/pull/807)

## 0.8 [April 15, 2026]

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4 changes: 2 additions & 2 deletions docs/_static/class_hierarchy.html

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103 changes: 103 additions & 0 deletions docs/technology_models/h2_htse.md
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@@ -0,0 +1,103 @@
# High-Temperature Steam Electrolysis (HTSE) Model

The HTSE model in H2Integrate represents hydrogen production from high-temperature steam electrolysis using electricity and thermal input. It is implemented as two components:

- `HTSEPerformanceModel`
- `HTSECostModel`

The performance model converts electricity and heat into hydrogen, water demand, and operating signals for connected technologies. The cost model computes installed capital cost and fixed operating cost from installed HTSE size.

## Model Overview

This is a simplified HTSE representation with constant nominal specific energy requirements:

- `nominal_electricity_required` in `kWh/kg`
- `nominal_heat_required` in `kWh/kg`

At each timestep, hydrogen production is determined from:

- installed HTSE size
- available `electricity_in`
- available `heat_in`
- optional `hydrogen_command_value` when system-level control is enabled
- turndown behavior

The model also exposes internal operating signals that are useful for coupled systems, including:

- `heat_demand`
- `electricity_demand`
- `electricity_consumed`
- `water_demand`

```{note}
The current implementation uses `electricity_demand` to report installed electrical demand equal to nameplate size, while `electricity_consumed` reports the timestep electricity required by the energy balance. For coupled analyses, `electricity_consumed` is the more literal consumption signal.
```

## Performance Model

Use this model by setting:

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Use this model by setting:
To use this model, within your `tech_config.yaml` file set:


- performance model: `HTSEPerformanceModel`

The HTSE performance model inherits from the electrolyzer base classes, so it is treated as a hydrogen-producing, dispatchable technology with an `electricity_in` input and a `hydrogen_out` output.

```{figure} images/HTSE.png
:alt: HTSE schematic
:width: 100%
:align: center
```

### Dispatch and sizing behavior

Installed size is first inferred from:

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Installed size is first inferred from:
Installed size is first calculated as:


$$
\text{electrolyzer\_size\_mw} = n_{clusters} \times cluster\_rating\_MW
$$

The model supports additional sizing modes inherited from the resizeable performance base class:

- `normal`
- `resize_by_max_feedstock`
- `resize_by_max_commodity`

In the current implementation:

- `resize_by_max_feedstock` supports sizing from `electricity`
- `resize_by_max_commodity` supports sizing from `hydrogen`

When system-level control is enabled, hydrogen demand is taken from `hydrogen_command_value`. Otherwise, the model assumes demand equal to rated hydrogen production implied by installed electrical size.

### Energy balance behavior

The model forms:

$$
\text{total\_specific\_energy} = nominal\_heat\_required + nominal\_electricity\_required

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Specific energy has certain meaning in some contexts, like energy per mass (energy density). Is that the expected meaning here? If not, I'd suggest a different phrase, like total_energy_required or similar for clarity.

$$

and computes a nominal heat-to-electricity ratio:

$$
\text{ratio\_heat\_elec\_nom} = \frac{nominal\_heat\_required}{nominal\_electricity\_required}
$$

Available heat is used first up to the requested `heat_demand`. The remaining required energy is supplied electrically when possible. Hydrogen production is then limited by the combined energy available and by the turndown threshold.

```{note}
The current implementation is intentionally simple and should be interpreted as a reduced-order plant representation, not a detailed SOEC stack model with thermal transients, degradation coupling, startup dynamics, or detailed balance-of-plant behavior.

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For those unfamiliar with SOEC, could you please define it somewhere on this page? It's used here and in one diagram

```

### API details
For API details, see the [`HTSEPerformanceModel` and `HTSECostModel` API documentation](../_autosummary/h2integrate.converters.hydrogen.htse_electrolyzer).

## Cost Model

Use this model by setting:

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Use this model by setting:
To use this model, in your `tech_config.yaml` file, set:


- cost model: `HTSECostModel`

The cost model is size-based and currently depends only on installed HTSE size.

### API details
For API details, see the [`HTSEPerformanceModel` and `HTSECostModel` API documentation](../_autosummary/h2integrate.converters.hydrogen.htse_electrolyzer).
Binary file added docs/technology_models/images/HTSE.png

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Would be nice to have the pump and heat exchanger labeled for those not as familiar with the setup.

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Done

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Label the heat exchanger? Also, what does the red dashed line represent?

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Done. I also made a note in the doc page that the red dashed arrow represents the heat extraction (upstream of the LPT).

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132 changes: 63 additions & 69 deletions docs/technology_models/nuclear.md
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@@ -1,83 +1,33 @@
# Nuclear power plant model

The nuclear power plant model provides a simple, size-based performance model and a type-based cost model.
Cost defaults are intended to be populated from literature, such as Quinn et al. (2023) on SMR LWR techno-economic analysis.
See the paper here: [Quinn et al. (2023)](#references).

To use this model, set the performance model to `QuinnNuclearPerformanceModel` and the cost model to `QuinnNuclearCostModel` in your `tech_config`.

## Performance model

The performance model limits electricity production by the rated capacity and an optional demand signal.

**Inputs**
| Name | Shape | Units | Description |
| --- | --- | --- | --- |
| `system_capacity` | scalar | kW | Rated electrical capacity. |
| `electricity_set_point` | array[n_timesteps] | kW | Optional set point profile; defaults to rated capacity. |

**Outputs**
| Name | Shape | Units | Description |
| --- | --- | --- | --- |
| `electricity_out` | array[n_timesteps] | kW | Electricity produced, capped at `system_capacity`. |
| `rated_electricity_production` | scalar | kW | Rated production (capacity). |
| `total_electricity_produced` | scalar | kW*h | Sum of production over the simulation. |
| `annual_electricity_produced` | array[plant_life] | kW*h/year | Annualized production. |
| `capacity_factor` | array[plant_life] | unitless | Ratio of actual to maximum production. |
| `replacement_schedule` | array[plant_life] | unitless | Placeholder replacement schedule (zeros). |
| `operational_life` | scalar | yr | Operational life (defaults to plant life). |

## Cost model

The cost model uses direct cost parameters to compute capital and operating costs.
It supports optional scaling of capex with size using a reference capacity and scaling exponent.

**Inputs**
| Name | Shape | Units | Description |
| --- | --- | --- | --- |
| `system_capacity` | scalar | kW | Plant capacity used for cost scaling. |
| `electricity_out` | array[n_timesteps] | kW | Output from performance model. |

**Cost parameters (tech_config)**
| Key | Type | Description |
| --- | --- | --- |
| `system_capacity_kw` | float | Rated electrical capacity (kW). |
| `capex_per_kw` | float | Capital cost per kW. |
| `fixed_opex_per_kw_year` | float | Fixed O&M per kW per year. |
| `variable_opex_per_mwh` | float | Variable O&M per MWh. |
| `reference_capacity_kw` | float | Reference capacity for capex scaling (defaults to `system_capacity_kw`). |
| `capex_scaling_exponent` | float | Capex scaling exponent (defaults to 1.0). |
| `cost_year` | int | Dollar year for the input costs. |

The capex calculation follows:
# Nuclear power plant models

$$
C_{\text{capex}} = (c_{\text{capex}} \cdot (P / P_{\text{ref}})^{(k-1)}) \cdot P
$$
H2Integrate currently includes two nuclear converter options:

- `QuinnNuclearPerformanceModel` with `QuinnNuclearCostModel` for an electricity-only nuclear plant
- `SimpleThermalNuclearReactorPerformanceModel` with `SimpleThermalNuclearReactorCostModel` for a thermal reactor that can trade off electricity production and process heat delivery

The first model is based on Quinn et al. (2023). The second is a simplified thermal reactor representation intended for coupled workflows such as nuclear plus HTSE.

Where $c_{\text{capex}}$ is `capex_per_kw`, $P$ is plant capacity (kW), $P_{\text{ref}}$ is `reference_capacity_kw`, and $k$ is `capex_scaling_exponent`.
## Quinn electricity-only nuclear model

**Outputs**
| Name | Shape | Units | Description |
| --- | --- | --- | --- |
| `CapEx` | scalar | USD | Total capital expenditure. |
| `OpEx` | scalar | USD/year | Fixed plus variable O&M. |
| `VarOpEx` | array[plant_life] | USD/year | Variable O&M (repeated each year). |
| `cost_year` | scalar | year | Dollar year of costs. |
Use this model by setting:

## Example tech_config
- performance model: `QuinnNuclearPerformanceModel`
- cost model: `QuinnNuclearCostModel`
Comment on lines +12 to +15

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Suggested change
Use this model by setting:
## Example tech_config
- performance model: `QuinnNuclearPerformanceModel`
- cost model: `QuinnNuclearCostModel`

With the example tech_config below I'd say this isn't needed


This model produces electricity only and clips commanded output to rated plant capacity.

### Example `tech_config`

```yaml
technologies:
nuclear:
performance_model:
model: "QuinnNuclearPerformanceModel"
model: QuinnNuclearPerformanceModel
cost_model:
model: "QuinnNuclearCostModel"
model: QuinnNuclearCostModel
model_inputs:
performance_parameters:
system_capacity_kw: 300000.0
capacity_factor: 0.9
cost_parameters:
system_capacity_kw: 450000.0
capex_per_kw: 6000.0
Expand All @@ -88,7 +38,51 @@ technologies:
cost_year: 2023
```

(references)=
## References
### API details
For API details, see the [`QuinnNuclearPerformanceModel` and `QuinnNuclearCostModel` API documentation](../_autosummary/h2integrate.converters.nuclear.nuclear_plant).

(references)=
### References
- Quinn, J. et al., 2023. Small modular reactor light water reactor techno-economic analysis. Applied Energy 120669. https://doi.org/10.1016/j.apenergy.2023.120669

## Simple thermal nuclear reactor model

Use this model by setting:

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Suggested change
Use this model by setting:
You can use this model by setting (in your `tech_config.yaml`):


- performance model: `SimpleThermalNuclearReactorPerformanceModel`
- cost model: `SimpleThermalNuclearReactorCostModel`

This model represents a reactor with:

- a high-pressure electric conversion stage
- a low-pressure electric conversion stage
- an extractable process heat stream, extracted upstream of the low-pressure turbine stages (dashed red arrow in the figure)

It supports two operating modes:

- `heat`: In `heat` mode, delivered heat is limited by available process heat and requested heat demand. Remaining low-pressure heat is converted to electricity.

- `electricity`: In `electricity` mode, electricity is limited by the command value and rated capacity. Remaining process heat is then sent as `heat_out`.

```{figure} images/ThermalNucReactor-H2I.png
:alt: Thermal nuclear reactor schematic
:width: 100%
:align: center
```

### Thermal reactor dispatch logic

The model computes a combined electric efficiency:

$$
\eta_{combined} = \eta_{hp} + (1 - \eta_{hp}) \eta_{lp}
$$

Then infers thermal capacity from rated electrical capacity:

$$
P_{thermal} = \frac{P_{electric,rated}}{\eta_{combined}}
$$

### API details
For API details, see the [`SimpleThermalNuclearReactorPerformanceModel` and `SimpleThermalNuclearReactorCostModel` API documentation](../_autosummary/h2integrate.converters.nuclear.nuclear_plant_thermal).
4 changes: 4 additions & 0 deletions docs/user_guide/model_overview.md
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Expand Up @@ -150,12 +150,14 @@ auto-generated API page.
- `hydrogen`: hydrogen production
- performance models:
+ {py:class}`~h2integrate.converters.hydrogen.pem_electrolyzer.ECOElectrolyzerPerformanceModel` - An OpenMDAO component that wraps the PEM electrolyzer model.
+ {py:class}`~h2integrate.converters.hydrogen.htse_electrolyzer.HTSEPerformanceModel` - A simplified high-temperature steam electrolysis (HTSE) model.
+ {py:class}`~h2integrate.converters.hydrogen.h2_fuel_cell.LinearH2FuelCellPerformanceModel` - Performance model for a hydrogen fuel cell.
+ {py:class}`~h2integrate.converters.hydrogen.steam_methane_reformer.SteamMethaneReformerPerformanceModel` - Performance model for steam methane reforming (SMR) hydrogen production plants.
- cost models:
+ {py:class}`~h2integrate.converters.hydrogen.basic_cost_model.BasicElectrolyzerCostModel` - An OpenMDAO component that computes the cost of a PEM electrolyzer.
+ {py:class}`~h2integrate.converters.hydrogen.custom_electrolyzer_cost_model.CustomElectrolyzerCostModel` - An OpenMDAO component that computes the cost of a PEM electrolyzer.
+ {py:class}`~h2integrate.converters.hydrogen.h2_fuel_cell.H2FuelCellCostModel` - Cost model for a hydrogen fuel cell system.
+ {py:class}`~h2integrate.converters.hydrogen.htse_electrolyzer.HTSECostModel` - A simple size-based cost model for HTSE.
+ {py:class}`~h2integrate.converters.hydrogen.singlitico_cost_model.SingliticoCostModel` - An OpenMDAO component that computes the cost of a PEM electrolyzer.
+ {py:class}`~h2integrate.converters.hydrogen.steam_methane_reformer.SteamMethaneReformerCostModel` - Cost model for steam methane reforming hydrogen production plants.
- combined performance and cost models:
Expand Down Expand Up @@ -202,8 +204,10 @@ auto-generated API page.
- `nuclear`: nuclear power plants
- performance models:
+ {py:class}`~h2integrate.converters.nuclear.nuclear_plant.QuinnNuclearPerformanceModel` - Simple nuclear performance model producing electricity.
+ {py:class}`~h2integrate.converters.nuclear.nuclear_plant_thermal.SimpleThermalNuclearReactorPerformanceModel` - Simple thermal nuclear reactor model with heat and electricity outputs.
- cost models:
+ {py:class}`~h2integrate.converters.nuclear.nuclear_plant.QuinnNuclearCostModel` - Cost model for nuclear power plants.
+ {py:class}`~h2integrate.converters.nuclear.nuclear_plant_thermal.SimpleThermalNuclearReactorCostModel` - Simple cost model for the thermal nuclear reactor.

- `solar`: solar-PV panels
- performance models:
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52 changes: 52 additions & 0 deletions examples/36_nuclear_reactor_htse/driver_config.yaml
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name: driver_config
description: Runs a thermal nuclear plant with simple optimization
general:
folder_output: nuclear_thermal_plant
### Use This For Parameter Sweep
# driver:
# design_of_experiments:
# flag: true
# generator: "FullFact" #type of generator to use
# levels: 3 # input is specific to this generator
# debug_print: true
driver:
optimization:
flag: false
solver: COBYLA
tol: 0.1
catol: 100000
max_iter: 100
rhobeg: 0.1
disp: 3
debug_print: true
design_variables:
nuclear:
electricity_command_value:
flag: true
lower: 1000
upper: 500000
units: kW
htse:
n_clusters:
flag: true
lower: 2.0
upper: 40.0
units: unitless
# Add constraints later to the code
# constraints:
# nuclear:
# electricity_out:
# flag: true
# upper: 5000.0
# units: MW
# ramping_rate:
# flag: true
# upper: 500
# units: kW/hr
# electrolyzer:
# total_hydrogen_produced:
# flag: false
# lower: 60500000.
# units: kg/year
objective:
name: finance_subgroup_hydrogen.LCOH
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name: H2Integrate_config
system_summary: This is an example plant with a nuclear plant capable of dispatching thermal and electrical energy to an HTSE
system
driver_config: driver_config.yaml
technology_config: tech_config.yaml
plant_config: plant_config.yaml
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