Renewable Energy Forecasts for ISO-NE Region & Sites – Sample

Vaisala Xweather provides accurate energy forecasts for utility-scale wind and solar projects in North American RTO/ISO regions.

This high-quality data set for the ISO New England (ISO-NE) region helps asset owners, project managers, and energy traders make confident, data-driven decisions at the site-specific and regional level to effectively manage investments, reduce future risks, and gain a competitive edge in energy markets.

- Look ahead with 7-day power forecasts at 1-hour intervals at the plant and regional level for real-time and day-ahead markets.

- Look back at site-level estimated actual power data in 15-minute intervals for the last two days.

Xweather combines cutting-edge weather and environmental modeling, robust data science, and powerful supercomputing to produce accurate energy forecasts and actual power estimates for wind and solar projects.

This sample data set contains 1 day of forecast data and 1 day of estimated actual power data for sites in the ERCOT Solar region in our database.

All data provided is interval ending.

Please contact us using the Contact Vaisala link in the listing if you would like to purchase a regularly updated data feed for the ISO-NE region.

Tables included:

LATEST 7-DAY FORECAST
LAST 2 DAYS ESTIMATED ACTUAL POWER
REGIONAL SITES METADATA

Fields included:

LATEST 7-DAY FORECAST
- NAME — renewable energy project name
- TIME — date and time for the forecast
- FORECAST — forecasted estimated power in MW
- INTERVAL — the time between forecasts
- TIME ZONE — local time zone for time values
- FORECAST CREATION TIME — date and time the forecast was created
- MODEL INITIALIZATION TIME — date and time when the forecast model was initiated

LAST 2 DAYS ESTIMATED ACTUAL POWER
- NAME — renewable energy project name
- TIME — date and time for the observation
- ESTIMATED ACTUAL POWER — estimated actual power in MW
- INTERVAL — the time between observations
- TIME ZONE — local time zone for time values
- FILE CREATION TIME — date and time the file was created

REGIONAL SITES METADATA
- NAME — renewable energy project name
- ALTERNATE_NAME — alternative name
- EIA_PLANT_CODE — U.S. Energy Information Administration project ID
- MAX_CAPACITY — project capacity in MW
- MODEL — turbine model used in wind projects
- ONLINE_DATE — operational start date
- LATITUDE — location of the project
- LONGITUDE — location of the project
- STATE — location of the project
- COUNTY — location of the project

**DATA FORMAT AND GRANULARITY**

Data is provided for projects and sites within the ISO-NE region in our database.

The data set includes three CSV files.

1) The first file contains site-specific metadata about each project in the region such as name, location, and capacity.

2) The second file provides a 7-day energy forecast (168 hours) in 1-hour intervals for each site in the region and a forecast for the ISO-NE region as a whole.

3) The third file contains the estimated actual power output from each site in the region and for the region as a whole over the last 2 days in 15-minute intervals.

**SOURCES**

The total actual power for the region as a whole comes from ISO-NE. The estimated actual power for each site in the region and the 7-day energy forecasts are produced using Vaisala's proprietary blend of numerical weather prediction trained models, statistical data modeling, and sophisticated machine-learning algorithms. Wind energy estimates and forecasts combine the actual operating characteristics of each project with the most advanced weather forecasts available.

**Business Needs**
**Risk Analysis**
Asset owners, power marketers, and energy traders use power estimates for regional transmission grids to take a position on balancing reserves and congestion mitigation.
**Asset Valuation**
Asset owners and project managers use power estimates for regional sites to take a position on managing each project’s operations and the budgetary impact on their farms.
**Demand Forecasting**
Grid operators and balancing authorities use these data sets to run forecasts per site in their area to understand how demand is being met by the energy they produce and supply.
Pricing Analysis
Power marketers, energy traders, and nodal traders use these data sets to see the power estimates from farms within the same transmission line to get insights into congestion and determine negative locational marginal prices.
**Market Analysis**
Asset owners, power marketers, and energy traders use these data sets to capitalize on opportunities, mitigate risk, and make better investment decisions in real-time and day-ahead energy trading markets.
**Machine Learning**
Data scientists and market analysts combine these data sets with weather data and other sources to train machine learning models for forecasting renewable energy production.