AI/ML based optimization and prediction of Commercial Buildings Energy Performance Report and Notification

Most of the local Governments are providing funds to reduce energy usage and carbon footprint for their buildings with more energy efficient design, solar panels and more efficient systems. All of these would need predictive modeling on given building data points.

“Clean” and “Curated” Data that we can compliment in your modeling : Our curated data contains various weather, turbine and rotor features. Data has been recorded from January 2018 till March 2020 at every 10-minute interval.

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Buildings Energy Performance Ordinance

The Existing Buildings Energy Performance Ordinance (Environment Code Chapter 20) requires that each non-residential building with at least 10,000 square feet of conditioned (heated or cooled) space and each residential building with at least 50,000 square feet of conditioned space must be benchmarked using Energy Star Portfolio Manager annually. Each non-residential building specified above is also required to undergo an energy audit or retrocommissioning at least once every 5 years.More information can be found at www.sfenvironment.org/ebo.

Private-sector (non-municipal) properties

This dataset lists compliance status for private-sector (non-municipal) properties where the owner has been notified that the building is subject to the ordinance. Fields reported have expanded as of early October 2015 to include energy use intensity, the 1-100 Portfolio Manager rating, and estimated greenhouse gas emissions from annual energy consumption.

Datasets

Annual Energy Consumption from Singapore Buildings

This dataset is from the annual energy consumption of Singapore buildings. It consists of data for energy use intensity (EUI) between 2017 and 2018 for different types of building and the respective Green Mark Rating. EUI is measured by the total electricity used by a building in a year per gross floor area.
This dataset has parameters like

  • building_name
    building_address
    building_type
    green_mark_status
    green_mark_rating
    green_mark_year_awardsort
    Building_size
    gross_floor_area
    2017_energy_use_intensity
    2018_energy_us_intensity
    voluntary_disclosure

USA Commercial Building Energy Models Output

Data is based on Commercial Buildings Energy Consumption Survey (CBECS) based on the 2003 CBECS data, which includes 18 commercial building types in two vintages (pre-1980 and post-1980) from 15 climate locations across the U.S.

SF Commercial Buildings Energy Performance Report

This dataset lists compliance status for private-sector (non-municipal) properties where the owner has been notified a building is subject to the ordinance. Fields reported have expanded as of early October 2015 to include energy use intensity, the 1-100 Portfolio Manager rating, and estimated greenhouse gas emissions from annual energy consumption

Data Cleaning And Data Prep Tools Used By Our Team

The Project team will use the appropriate tools based on volume, location and nature of the client data and deliver the cleaned/formatted data with visualization or ingested in a database-whatever way a client will demand. They can also run initial POC with client suggested tools/machines to do initial QC of the data and feasibility of algorithmic solution.

Data Cleaning and Data Prep Tools used by our team 

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Contact Us

DatacleaningforAIML
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1-650-242-8799
contact@datacleaningforAIML.com