Capacity Outage Probability Table (COPT) Maker

Fast Capacity Outage Probability Table (COPT) generator powered by NumPy.

App in Binder

Notebook in Colab

Feature

1. Calculate Loss of Load Probability (COPT).

2. Calculate Expected Energy Not Served (EENS).

3. Calculate Load Shedding Cost.

Psuedocode

Program structure:

Forced Outage Data
└── Individual Generator Capacity Outage Probability Table
    └── Combined Capacity Outage Probability Table
        ├── Loss of Load Probability
        │   └── Loss Of Load Expectation
        └────── Expected Energy Not Served
                └── Expected Unserved Energy Cost

Step by step pseudocode

# Individual Generator Capacity Outage Probability Table
i = 1
for i in generatorNumbers:
    tables[i] = [capacity[i], [0, 1 - outage_rate[i]]]
    i = i + 1

# Combined Capacity Outage Probability Table
for table in tables:
    COPT = [
        (COPT_capacities + table_capacity)
        (COPT_probabilities * table_probability)
    ]
COPT_cumulativeProbabilities = sum(COPT_probabilities)

# Loss of Load Probability
LOLP = COPT_cumulativeProbabilities(
    min(
        where(
            capacity < demand
            )
        )
)

# Loss Of Load Expectation
LOLE = LOLP * 365

# Expected Energy Not Served
for demand in demands:
EENS = sum(
    COPT_probabilities * (COPT_capacities < demand) * (demand - COPT_capacities)
)

# Expected Unserved Energy Cost
cost = EENS * VOLL

Contributing

1. We use nb-clean to clean notebooks metadata. It should not be added as filter since Colab metadata will be added later.

   pip install nb-clean
   nb-clean clean notebooks/app.ipynb --preserve-cell-outputs --preserve-cell-metadata

2. To better support colab, add below metadata (after clean) to hide cell in colab (only on the UI cell):

      "metadata": {
       "cellView": "form",
       "colab": {}
      },