# NYISOToolkit

Access data, statistics, and visualizations about New York's electricity grid.Documentation Contribute

##### For questions or data requests email: viosimosllc@gmail.com

### Carbon-free Year (CLCPA Status)

A bar graph of the percent of annual electrical demand served by energy source. As required by the CLCPA legislation, 100% of New York State's electrical demand will need to come from carbon-free energy sources by 2040, and 70% from renewable energy sources by 2030.

### Carbon-free Time Series (CLCPA Status)

A time series of the percent of daily electrical demand served by carbon-free energy sources (nuclear and renewables), overlayed by the aggregate annual percentages. The dotted contour shows what the total would be if all the imported energy into the state came from carbon-free sources (which it doesn't currently, but might in the future). As required by the CLCPA legislation, 100% of New York State's electrical demand will need to come from carbon-free energy sources by 2040, and 70% from renewable energy sources by 2030. Note: This figure was inspired by NYISO Power Trends 2020 - Figure 12: Production of In-State Renewables & Zero-Emission Resources Relative to 2019 Load.

### Decarbonization Heat Map

A heatmap showing the hourly and seasonal variation in carbon-free operation of the electric grid. In the summer months when there is peak electrical demand, the grid typically relies more on carbon emitting energy sources to meet the load than it does in other seasons. In the evening hours when load is relatively low, a significant portion of that energy can be met by carbon-free energy sources.

### Energy Generation

A time series of the daily electric energy demand served by each energy source.

### Demand Probability Distribution

The probability distribution of the state-wide electrical demand by season. Demand on a 5-minute basis is used.

### Demand Probability Distribution (Cumulative)

The cumulative probability distribution of the state-wide electrical demand by season (aka: percentile). Demand on a 5-minute demand is used.

### Demand Forecast Error Probability Distribution

The probability distribution of the state-wide electrical demand forecast error by season. The error calculated as the difference between the day-ahead demand forecast and the actual demand.

### Demand Forecast Error Probability Distribution (Cumulative)

The cumulative probability distribution of the state-wide electrical demand forecast error by season (aka: percentile). The error calculated as the difference between the day-ahead demand forecast and the actual demand.

### Day-Ahead Energy Price Probability Distribution

The probability distribution of the state-wide average day-ahead energy price by season. State-wide average is calculated by weighting each zonal prices with its associated forecasted demand.

### Day-Ahead Energy Price Probability Distribution (Cumulative)

The cumulative probability distribution of the state-wide average day-ahead energy price by season (aka: percentile). State-wide average is calculated by weighting each zonal prices with its associated forecasted demand.

### Real-time Energy Price Probability Distribution

The probability distribution of the state-wide average real-time energy price by season. State-wide average is calculated by weighting the zonal price with its associated actual (non-forecasted) demand.

### Real-time Energy Price Probability Distribution (Cumulative)

The cumulative probability distribution of the state-wide average real-time energy price by season (aka: percentile). State-wide average is calculated by weighting each zonal prices with its associated actual (non-forecasted) demand.

### Energy Price Discount Probability Distribution

The probability distribution of difference between the state-wide day-ahead and real-time energy prices by season. It can be interpreted as the day-ahead price discount relative to the real-time price. The difference is calculated by subtracting the hourly averaged state-wide real-time energy price from the state-wide day-ahead price. Baseload includes all hours of the day.

### Energy Price Discount Probability Distribution (Cumulative)

The cumulative probability distribution of difference between the state-wide day-ahead and real-time energy prices by season. It can be interpreted as the day-ahead price discount relative to the real-time price. The difference is calculated by subtracting the hourly averaged state-wide real-time energy price from the state-wide day-ahead price. Baseload includes all hours of the day.