Bids and Offers Recommendation - Product Overview

OPTIMIZATION

1 min read

Product Brief

Maximizing the performance of generation or load assets - whether operating individually or aggregated in the form of hybrid assets, distributed energy resources or virtual power plants requires a robust, advanced platform. This platform integrates artificial intelligence, predictive algorithms, and convex optimization, along with the following inputs:

  • Generation Data: Historical and real time generation data, asset-specific metadata (capacity, location, and technical specifications), and weather data (radiation, temperature, wind speed, cloud cover, and more).

  • Load Data: Individual or aggregated meter data, forward meter counts, and usage trends.

  • Price Data: Historical, real time and market-projected locational pricing.

  • Asset Status: Current operating conditions of the asset (usage, state of charge, elevation, ...)

  • Market Data: Historical, real time and forecast data for similar and relevant substations across North America.

Outputs

The platform provides bids and offers optimized to your goal of maximizing revenue or reducing costs. Bids and offers are updated for every time you participate in the market for either automated submission to the market or verification through:

  • Platform Dashboards

  • Platform CSV Export

  • API Export

Performance

With this proprietary blend of tools, Bright Grid Analytics has already demonstrated its ability to enhance asset performance, increasing revenue for solar and battery assets by 1.5x in energy markets and doubling revenue in energy and regulation markets in California. We are confident in our capacity to significantly optimize your asset revenue/cost as well. Connect with the Bright Grid Analytics team to benchmark the performance of our optimization engine.

Coverage Across North America: AESO, IESO, CAISO, ERCOT, ISONE, MISO, NYISO, PJM, SPP and bilateral markets.

For more information, contact Bright Grid Analytics at info@brightgridanalytics.com.