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Biological Components

Components for biological conversion processes in biogas plants.

Digester

The main fermenter that implements the ADM1 model for anaerobic digestion.

Parameters

from pyadm1.configurator.plant_configurator import PlantConfigurator

configurator.add_digester(
    digester_id="main_digester",      # Unique identifier
    V_liq=2000.0,                     # Liquid volume [m³]
    V_gas=300.0,                      # Gas headspace [m³]
    T_ad=308.15,                      # Operating temperature [K]
    name="Main Digester",             # Readable name
    load_initial_state=True,          # Load steady-state initialization
    initial_state_file=None,          # Custom initial-state CSV (optional)
    Q_substrates=[15, 10, 0, ...]    # Substrate feed rates [m³/d]
)

Sizing Guidelines

Plant size V_liq [m³] V_gas [m³] Feed rate [m³/d] HRT [days]
Small 300–800 50–120 10–25 20–40
Medium 1000–3000 150–450 25–75 25–45
Large 3000–8000 450–1200 75–200 30–50

Temperature Options

# Psychrophilic (rare in practice)
T_psychro = 298.15  # 25 °C

# Mesophilic (most common)
T_meso = 308.15     # 35 °C

# Thermophilic (fiber-rich substrates)
T_thermo = 328.15   # 55 °C

Outputs

outputs = digester.step(t, dt, inputs)
# Returns:
{
    'Q_out': 25.0,              # Outflow [m³/d]
    'state_out': [...],         # ADM1 state for next digester
    'Q_gas': 1250.5,           # Biogas production [m³/d]
    'Q_ch4': 750.3,            # Methane production [m³/d]
    'Q_co2': 475.2,            # CO2 production [m³/d]
    'pH': 7.32,                # pH value
    'VFA': 2.45,               # Volatile fatty acids [g/L]
    'TAC': 8.50,               # Total alkalinity [g CaCO3/L]
    'gas_storage': {           # Attached gas storage info
        'stored_volume_m3': 150.0,
        'pressure_bar': 1.02,
        'vented_volume_m3': 0.0
    }
}

Advanced Usage

Multiple digesters in series:

# Hydrolysis + methanogenesis
configurator.add_digester("hydro", V_liq=500, T_ad=318.15,
                         Q_substrates=[15, 10, 0, 0, 0, 0, 0, 0, 0, 0])
configurator.add_digester("main", V_liq=2000, T_ad=308.15,
                         Q_substrates=[0, 0, 0, 0, 0, 0, 0, 0, 0, 0])
configurator.connect("hydro", "main", "liquid")

Custom initial state:

import pandas as pd

# Create custom state
initial = pd.DataFrame({
    'S_su': [0.01], 'S_aa': [0.001], # ... all 41 state variables
})
initial.to_csv('custom_state.csv', index=False)

# Use in digester
configurator.add_digester(
    "dig1", V_liq=2000,
    initial_state_file='custom_state.csv'
)

Calibration Parameters

The digester supports applying calibration parameters for model fitting:

from pyadm1.components.biological import Digester

digester = Digester("dig1", feedstock, V_liq=2000)

# Apply calibration parameters
digester.apply_calibration_parameters({
    'k_dis': 0.55,      # Disintegration rate
    'Y_su': 0.105,      # Yield coefficient for sugars
    'k_hyd_ch': 11.0    # Hydrolysis rate for carbohydrates
})

# Retrieve current parameters
params = digester.get_calibration_parameters()
print(params)

# Clear parameters (back to defaults)
digester.clear_calibration_parameters()

Separator

Solid–liquid separation for digestate processing (stub for future implementation).

from pyadm1.components.biological import Separator

separator = Separator(
    component_id="sep1",
    separation_efficiency=0.95  # 95% solids separation
)

Use case: Models mechanical (screw press, centrifuge) or gravity separation with configurable separation efficiency.

Example: Two-Stage Digestion System

from pyadm1.configurator import BiogasPlant, PlantConfigurator
from pyadm1.substrates import Feedstock

# Setup
feedstock = Feedstock(feeding_freq=48)
plant = BiogasPlant("Two-Stage Plant")
config = PlantConfigurator(plant, feedstock)

# Stage 1: Thermophilic hydrolysis
hydro, hydro_storage = config.add_digester(
    "hydrolysis",
    V_liq=500,
    V_gas=75,
    T_ad=328.15,  # 55 °C
    Q_substrates=[15, 10, 0, 0, 0, 0, 0, 0, 0, 0]
)

# Stage 2: Mesophilic methanogenesis
main, main_storage = config.add_digester(
    "methanogenesis",
    V_liq=2000,
    V_gas=300,
    T_ad=308.15,  # 35 °C
    Q_substrates=[0, 0, 0, 0, 0, 0, 0, 0, 0, 0]  # Input only from stage 1
)

# Connect digesters
config.connect("hydrolysis", "methanogenesis", "liquid")

# Energy system
config.add_chp("chp1", P_el_nom=500)
config.add_heating("heat_hydro", target_temperature=328.15, heat_loss_coefficient=0.3)
config.add_heating("heat_main", target_temperature=308.15, heat_loss_coefficient=0.5)

# Auto-connections
config.auto_connect_digester_to_chp("hydrolysis", "chp1")
config.auto_connect_digester_to_chp("methanogenesis", "chp1")
config.auto_connect_chp_to_heating("chp1", "heat_hydro")
config.auto_connect_chp_to_heating("chp1", "heat_main")

# Simulate
plant.initialize()
results = plant.simulate(duration=100, dt=1/24, save_interval=1.0)

# Analyze results
final = results[-1]
print(f"Hydrolysis biogas: {final['components']['hydrolysis']['Q_gas']:.1f} m³/d")
print(f"Main biogas: {final['components']['methanogenesis']['Q_gas']:.1f} m³/d")
print(f"Total methane: {final['components']['hydrolysis']['Q_ch4'] + final['components']['methanogenesis']['Q_ch4']:.1f} m³/d")
print(f"pH hydrolysis: {final['components']['hydrolysis']['pH']:.2f}")
print(f"pH main: {final['components']['methanogenesis']['pH']:.2f}")

Process Monitoring

Key Process Indicators

def monitor_digester_health(results):
    """Monitor digester health via process indicators."""

    for result in results:
        digester_data = result['components']['main_digester']

        # Check pH
        pH = digester_data['pH']
        if pH < 6.8:
            print(f"Warning: Low pH ({pH:.2f}) - acidification risk")
        elif pH > 8.0:
            print(f"Warning: High pH ({pH:.2f}) - possible ammonia inhibition")

        # VFA/TAC ratio
        VFA = digester_data['VFA']  # g HAc-eq/L
        TAC = digester_data['TAC']  # g CaCO3-eq/L

        VFA_TAC = VFA / TAC if TAC > 0 else 0

        if VFA_TAC > 0.4:
            print(f"Warning: High VFA/TAC ratio ({VFA_TAC:.2f}) - process instability")

        # Gas production
        Q_gas = digester_data['Q_gas']
        if Q_gas < 500:  # example threshold
            print(f"Warning: Low gas production ({Q_gas:.1f} m³/d)")

monitor_digester_health(results)

Optimal Operating Ranges

Parameter Optimal Acceptable Critical
pH 7.0–7.5 6.8–8.0 <6.8 or >8.0
VFA [g/L] 0.5–2.0 2.0–4.0 >4.0
VFA/TAC 0.2–0.3 0.3–0.4 >0.4
TAC [g CaCO3/L] 5.0–10.0 4.0–12.0 <4.0
Temp. mesophilic [°C] 35–38 32–40 <30 or >42
Temp. thermophilic [°C] 52–55 48–58 <45 or >60

Troubleshooting

Low pH Value

Causes:
- Organic loading rate (OLR) too high
- Insufficient buffer capacity
- Sudden substrate change

Solutions:

# Reduce organic loading
Q = [10, 8, 0, 0, 0, 0, 0, 0, 0, 0]  # reduced from [15, 10, ...]

# Or add lime buffer
Q = [15, 10, 0, 0, 0, 0, 0, 1, 0, 0]  # 1 m³/d lime

Foaming

Causes:
- High protein content in substrate
- Sudden pH changes
- High VFA concentrations

Solutions:
- Reduce protein-rich substrates
- Stabilize pH via buffering
- Implement anti-foam measures

Low Gas Production

Causes:
- Low organic loading
- Poor substrate quality
- Inhibition (NH3, H2S, heavy metals)
- Hydraulic retention time too short

Diagnosis:

def diagnose_low_gas_production(digester_outputs):
    """Diagnose causes of low gas production."""

    Q_gas = digester_outputs['Q_gas']
    Q_in = sum(Q_substrates)  # total input

    # Specific gas yield
    specific_gas = Q_gas / Q_in if Q_in > 0 else 0

    if specific_gas < 0.5:  # m³ biogas / m³ input
        print("Low specific gas yield - possible causes:")
        print("- Poor substrate quality")
        print("- Inhibition")
        print("- Process instability")

    # Check methane content
    CH4_content = digester_outputs['Q_ch4'] / Q_gas if Q_gas > 0 else 0

    if CH4_content < 0.55:
        print(f"Low methane content ({CH4_content:.1%}) - possible air ingress or CO2 stripping")

diagnose_low_gas_production(digester.outputs_data)

Best Practices

  1. Start with realistic operating parameters
  2. Use typical HRT values (30–40 days)

  3. Start with moderate OLR (2–4 kg VS/m³/d)

  4. Monitor critical parameters

  5. pH should be stable (±0.2)
  6. VFA/TAC ratio < 0.4

  7. Methane content > 55%

  8. Implement buffering systems

  9. Add lime or other buffers at low pH

  10. Maintain TAC > 4 g CaCO3/L

  11. Use two-stage systems for difficult substrates

  12. Thermophilic hydrolysis for fiber-rich substrates

  13. Mesophilic methanogenesis for stable gas production

  14. Calibrate the model with real data

  15. Use calibration parameters for more accurate predictions
  16. Validate against operational data

Next Steps