BC_Nexus Integration

BC_Nexus Integration#

Overview#

BC_Nexus is the CLEWs (Climate, Land-use, Energy, Water, and Food Security Nexus) component of the BC Combined Modelling framework. It provides comprehensive renewable energy resource assessment and system-wide analysis for British Columbia.

Key Features#

Renewable Energy Resource Assessment#

  • Solar Resource Mapping: High-resolution solar irradiance and photovoltaic potential analysis

  • Wind Resource Analysis: Wind speed and wind power generation potential assessment

  • Hydro Resource Evaluation: Existing and potential hydroelectric generation capacity

  • Storage Integration: Battery and pumped hydro storage modeling

Land Use and Constraints#

  • Protected Areas: Integration of conservation and protected land designations

  • Infrastructure Constraints: Transmission line proximity and grid connection costs

  • Environmental Factors: Ecological and environmental constraint mapping

  • Urban and Agricultural Land: Exclusion of incompatible land uses

Temporal Analysis#

  • Multi-Year Assessment: Analysis across multiple meteorological years

  • Seasonal Patterns: Seasonal renewable energy generation patterns

  • Hourly Resolution: High temporal resolution for detailed system analysis

  • Extreme Events: Assessment of extreme weather impacts on renewable generation

Integration with Combined Framework#

Data Outputs to Linking Tool#

BC_Nexus provides several key data products that are processed by the linking tool:

# Example BC_Nexus outputs
bc_nexus_outputs = {
    'renewable_profiles': {
        'solar_pv': 'hourly generation profiles by region',
        'wind_onshore': 'hourly generation profiles by wind class',
        'hydro_run_of_river': 'hourly generation profiles'
    },
    'capacity_potentials': {
        'technical_potential': 'MW by technology and region',
        'economic_potential': 'MW considering cost constraints',
        'constrained_potential': 'MW after land use constraints'
    },
    'cost_parameters': {
        'capex': 'Capital costs by technology',
        'opex': 'Operating costs by technology',
        'connection_costs': 'Grid connection costs by location'
    }
}

Scenario Framework#

BC_Nexus supports multiple scenario dimensions:

Technology Scenarios#

  • Current Technology: Based on existing technology performance

  • Advanced Technology: Improved efficiency and reduced costs

  • Breakthrough Technology: Emerging technologies with high potential

Policy Scenarios#

  • Business as Usual: Current policy framework

  • Enhanced Targets: Increased renewable energy targets

  • Carbon Pricing: Various carbon price trajectories

Infrastructure Scenarios#

  • Existing Grid: Analysis with current transmission infrastructure

  • Enhanced Grid: Planned transmission expansions

  • Optimized Grid: Optimal transmission development

Model Configuration#

Basic Configuration#

bc_nexus:
  region: "BC"
  base_year: 2020
  analysis_years: [2020, 2025, 2030, 2035, 2040, 2045, 2050]
  
  technologies:
    solar_pv:
      enabled: true
      efficiency_improvement: 0.02  # per year
      cost_reduction: 0.05  # per year
    
    wind_onshore:
      enabled: true
      turbine_classes: ["IEC_1", "IEC_2", "IEC_3"]
      hub_heights: [80, 100, 120]  # meters
    
    hydro:
      run_of_river: true
      small_hydro: true
      storage_hydro: true
  
  constraints:
    protected_areas: true
    urban_exclusion: true
    transmission_distance_limit: 50  # km

Advanced Configuration#

bc_nexus:
  spatial_resolution: 1  # km
  temporal_resolution: "hourly"
  weather_years: [2012, 2013, 2014, 2015, 2016]
  
  land_use:
    exclusion_layers:
      - protected_areas
      - urban_areas
      - agricultural_land_reserve
      - water_bodies
    
    buffer_distances:
      airports: 3000  # meters
      urban_areas: 500  # meters
      highways: 100  # meters
  
  economics:
    discount_rate: 0.07
    project_lifetime: 25  # years
    capacity_factor_threshold: 0.15  # minimum CF

Running BC_Nexus Analysis#

Command Line Interface#

# Run BC_Nexus analysis
make nexus

# Run specific scenario
python workflow/scripts/BCNexus.py --scenario CNZ_1 --timeslices 96

# Generate BC_Nexus plots
make nexus_plots SCENARIO=Base_CNZ_noCCS TIMESLICES=24

Python API#

from bc_combined_modelling.bc_nexus import BCNexusInterface

# Initialize BC_Nexus interface
nexus = BCNexusInterface(
    config_file='config/bc_nexus_config.yaml',
    scenario='high_renewable'
)

# Run renewable resource assessment
results = nexus.run_resource_assessment(
    technologies=['solar_pv', 'wind_onshore'],
    regions=['lower_mainland', 'vancouver_island', 'peace_river']
)

# Access results
solar_potential = results['solar_pv']['technical_potential']
wind_profiles = results['wind_onshore']['generation_profiles']
constraint_maps = results['spatial_constraints']

Output Data Structure#

Generation Profiles#

# Hourly generation profiles by technology and region
generation_profiles = {
    'solar_pv': pd.DataFrame({
        'datetime': pd.date_range('2020-01-01', periods=8760, freq='H'),
        'lower_mainland': [0.45, 0.52, ...],  # Capacity factors
        'vancouver_island': [0.38, 0.44, ...],
        'interior': [0.52, 0.61, ...]
    }),
    'wind_onshore': pd.DataFrame({
        'datetime': pd.date_range('2020-01-01', periods=8760, freq='H'),
        'coastal': [0.35, 0.42, ...],
        'interior': [0.28, 0.31, ...],
        'peace_river': [0.41, 0.48, ...]
    })
}

Capacity Potentials#

# Regional capacity potentials by technology
capacity_potentials = {
    'solar_pv': {
        'lower_mainland': {'technical': 15000, 'economic': 8000, 'constrained': 5000},  # MW
        'vancouver_island': {'technical': 8000, 'economic': 4500, 'constrained': 3000},
        'interior': {'technical': 45000, 'economic': 25000, 'constrained': 18000}
    },
    'wind_onshore': {
        'coastal': {'technical': 12000, 'economic': 7000, 'constrained': 5500},
        'interior': {'technical': 35000, 'economic': 20000, 'constrained': 15000},
        'peace_river': {'technical': 18000, 'economic': 12000, 'constrained': 9000}
    }
}

Cost Data#

# Technology cost parameters
cost_parameters = {
    'solar_pv': {
        'capex': {'2020': 1500, '2030': 1000, '2040': 800},  # CAD/kW
        'opex_fixed': 15,  # CAD/kW/year
        'opex_variable': 0,  # CAD/MWh
        'lifetime': 25  # years
    },
    'wind_onshore': {
        'capex': {'2020': 2000, '2030': 1700, '2040': 1500},  # CAD/kW
        'opex_fixed': 35,  # CAD/kW/year
        'opex_variable': 5,  # CAD/MWh
        'lifetime': 20  # years
    }
}

Quality Assurance and Validation#

Data Validation#

  • Resource Data: Validation against measured meteorological data

  • Capacity Factors: Comparison with existing renewable energy facilities

  • Cost Data: Benchmarking against industry surveys and databases

Sensitivity Analysis#

  • Weather Year Sensitivity: Analysis across multiple meteorological years

  • Technology Parameter Sensitivity: Impact of cost and performance variations

  • Constraint Sensitivity: Effect of different land use restriction scenarios

Model Validation#

  • Historical Comparison: Validation against historical renewable energy deployment

  • Expert Review: Regular review by industry and academic experts

  • Cross-Model Validation: Consistency checks with other modeling frameworks

Future Enhancements#

Planned Improvements#

  • Offshore Wind: Integration of offshore wind resource assessment

  • Floating Solar: Assessment of floating photovoltaic potential

  • Agrivoltaics: Co-location of solar and agricultural activities

  • Green Hydrogen: Renewable hydrogen production potential

Advanced Features#

  • Machine Learning: AI-enhanced resource assessment and forecasting

  • Real-time Data: Integration of real-time meteorological and grid data

  • Climate Change: Assessment of climate change impacts on renewable resources

  • Social Acceptance: Integration of social and community factors

For technical details on data linking, see Linking Methodology. For PyPSA integration, see PyPSA Integration.

Contents