site-calc-investment 1.2.2

Python client for Site-Calc investment planning (capacity sizing, ROI analysis)

Site-Calc Investment Client

Python client for Site-Calc investment planning API - long-term capacity planning and ROI analysis.

Installation

pip install site-calc-investment

Quick Start

from datetime import datetime
from zoneinfo import ZoneInfo
from site_calc_investment import InvestmentClient
from site_calc_investment.models import (
    Resolution, Site, Battery, ElectricityImport, ElectricityExport,
    InvestmentPlanningRequest, InvestmentParameters, OptimizationConfig
)
from site_calc_investment.models.requests import TimeSpanInvestment

# Initialize client
client = InvestmentClient(
    base_url="https://api.site-calc.example.com",
    api_key="inv_your_api_key_here"
)

# Create 1-week planning horizon (1-hour resolution)
timespan = TimeSpanInvestment(
    start=datetime(2025, 1, 1, tzinfo=ZoneInfo("Europe/Prague")),
    intervals=168,  # 1 week = 7 days × 24 hours
    resolution=Resolution.HOUR_1
)

# Generate hourly prices (example: day/night pattern)
prices = [30.0 if h % 24 < 6 else 80.0 if 8 <= h % 24 < 20 else 50.0 for h in range(168)]

# Define devices (NO ancillary_services field)
battery = Battery(
    name="Battery1",
    properties={
        "capacity": 10.0,
        "max_power": 5.0,
        "efficiency": 0.90,
        "initial_soc": 0.5
    }
)

grid_import = ElectricityImport(
    name="GridImport",
    properties={"price": prices, "max_import": 10.0}
)

grid_export = ElectricityExport(
    name="GridExport",
    properties={"price": prices, "max_export": 10.0}
)

site = Site(site_id="investment_site", devices=[battery, grid_import, grid_export])

# Investment parameters
inv_params = InvestmentParameters(
    discount_rate=0.05,
    project_lifetime_years=10,                  # Required field
    device_capital_costs={"Battery1": 500000},  # €500k CAPEX
    device_annual_opex={"Battery1": 5000}       # €5k/year O&M
)

# Create and submit optimization request
request = InvestmentPlanningRequest(
    sites=[site],
    timespan=timespan,
    investment_parameters=inv_params,
    optimization_config=OptimizationConfig(
        objective="maximize_profit",  # Options: maximize_profit, minimize_cost, maximize_self_consumption
        time_limit_seconds=300        # Max 900 seconds (15 min)
    )
)

job = client.create_planning_job(request)
result = client.wait_for_completion(job.job_id, poll_interval=5, timeout=600)

print(f"Status: {result.status}")
print(f"Solver: {result.summary.solver_status}")
print(f"Profit: €{result.summary.expected_profit:,.2f}")

Features

• ✅ Long-term capacity planning (1-10 years)
• ✅ Investment ROI analysis (NPV, IRR, payback)
• ✅ Scenario comparison utilities
• ✅ Financial analysis helpers
• ✅ 1-hour resolution optimization
• ✅ Multi-site optimization
• ✅ Type-safe Pydantic models
• ✅ Automatic retry and error handling
• ✅ Job management (cancel single or all jobs)

Capabilities

Feature	Value
Max Horizon	100,000 intervals (~11 years at 1-hour)
Resolution	1-hour only
ANS Support	No
Binary Variables	Relaxed to continuous
Timeout	900 seconds (15 minutes) max

Supported Devices

• Battery (NO ANS)
• CHP - Combined Heat and Power (continuous operation)
• Heat Accumulator
• Photovoltaic
• Heat Demand
• Electricity Demand
• Electricity Import/Export (market interface)
• Gas Import (market interface)
• Heat Export (market interface)

Job Management

The client provides methods for managing optimization jobs:

# Create a job
job = client.create_planning_job(request)
print(f"Job ID: {job.job_id}")

# Check job status
status = client.get_job_status(job.job_id)
print(f"Status: {status.status}, Progress: {status.progress}%")

# Wait for completion
result = client.wait_for_completion(job.job_id, poll_interval=30, timeout=7200)

# Cancel a single job
cancelled = client.cancel_job(job.job_id)

# Cancel all pending/running jobs (bulk cancel)
result = client.cancel_all_jobs()
print(f"Cancelled {result['cancelled_count']} jobs")

Financial Analysis

from site_calc_investment.analysis import (
    calculate_npv,
    calculate_irr,
    calculate_payback_period,
    compare_scenarios
)

# NPV calculation
npv = calculate_npv(
    cash_flows=annual_revenues,
    discount_rate=0.05,
    initial_investment=-1500000
)

# IRR calculation
irr = calculate_irr([-1500000] + annual_revenues)

# Scenario comparison
comparison = compare_scenarios(
    [result_5mw, result_10mw, result_15mw],
    names=["5 MW", "10 MW", "15 MW"]
)
print(comparison)  # DataFrame with NPV, IRR, costs, revenues

Documentation

Full documentation available at: https://github.com/stranma/site-calc-investment#readme

Examples

See examples/ directory for complete examples:

• capacity_planning.py - 10-year capacity planning workflow
• roi_analysis.py - Investment ROI calculation
• scenario_comparison.py - Compare device configurations

Requirements

• Python ≥ 3.10
• API key with inv_ prefix (investment client)

Key Differences from Operational Client

• ❌ No /optimal-bidding endpoint
• ❌ No ancillary_services on devices
• ❌ No 15-minute resolution (1-hour only)
• ✅ Up to 100,000 intervals (vs. 296)
• ✅ Investment metrics (NPV, IRR, payback)
• ✅ Financial analysis helpers

Development

# Install with dev dependencies
pip install -e ".[dev]"

# Run tests
pytest

# Format code
ruff format .

# Type check
mypy site_calc_investment

License

MIT License

Support

• Issues: https://github.com/stranma/site-calc-investment/issues
• Documentation: https://github.com/stranma/site-calc-investment#readme

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Part of the Site-Calc platform.