Power BI

Microsoft's Power BI is a tool I've started using to view data. It and other similar tools, are enriched, simplified, tools for reporting with data.

Listing of published Power BI Reports

US Data

Energy Information Administration (EIA) Electric Generator Inventory mapped and summarized (data from survey form EIA-860M )

US Pricing and Consumption, by state (data from EIA-861 and 861M)


Basic IESO data uses a couple of simple data sets constructed from publicly available files from the Independent Electricity System Operator (IESO).

  • One set of data begins May 1, 2002, the first day of the Ontario market - it includes, Hourly Ontario Energy Price (HOEP), Demand, and import/export data.
  • The second set of data begins January 1, 2010, and is generation by source (ie. wind, nuclear, hydro, gas, solar, biofuel, and in the past coal).

The different pages in the Basic IESO data include two designed to report by IESO week (Wed. - Tues.), and two for for month. Two because one runs back to 2003 as the first full year of the longest data set, and the second goes back to 2010.

The pages are interactive - from the weekly pages one can access hourly data for any date, and below is a screen capture of one view available from manipulating the monthly generation page. I made a YouTube video when I first developed the page to try and demonstrate some of the functionality.

The data on this page is restricted to IESO reporting on generators connected to their grid (Tx = transmission connected), and as such the queries miss an increasing amount of data necessary to build a better understanding of performance, and value. Two big omissions are reporting on distribution-connected resources (which impact these figures by lowering "Ontario Demand" - as that figure is demand for supply from IESO Tx generators), and reporting on curtailment.

Hourly Curtailment, and Generation is a page displaying hourly data for the current date. This display is based on analysis of the IESO's Generator Output and Capability reporting (xml): a created table with generator data is used to map the data. Curtailment can occur for multiple reasons, including a global surplus of supply, local congestion, pricing (negative priced exports are not allowed).

I also created a short youtube video to explain the page.

The two pages linked to here have in common automatically updating. The Basic IESO data is scheduled to update once a day, by noon, but success is dependent on the IESO's files updating each morning, which is not always true. The Hourly Curtailment, and Generation page is scheduled to update every 3 hours.

Ontario Annual Generation and Cost Estimates is a quick, 3 page Power BI report build on a spreadsheet of estimates I've built from many sources over time - without particularly skilled documentation.