Digital Twin: Energy Optimization at Chicago Skyscraper

This case study reflects an ongoing energy analytics initiative I lead in partnership with an ambitious Class A commercial office building in downtown Chicago.

Introduction

A long-time partner and customer of my company Cohesion - a large class A commercial office building in downtown Chicago - ambitiously intends to be a leader in energy performance. Not just for cost savings, but to solidify their reputation as a sustainability leader. While the building has already achieved near-maximum efficiency through various other initiatives and upgrades, my team, the building’s leadership and I saw a massive opportunity in energy intelligence driven by real-time data, tenant visibility, and behavioral change.

This project emerged from strategic planning conversations I led alongside a Cohesion VP, collaborating directly with building management, engineering, and operations leadership. We aligned on a shared goal: Give the building the tools and intelligence to see, model, and act on energy use like they have never been able to before.

We created a plan to combine submeters, occupancy data, weather modeling, and equipment integrations into a single system of insight - a live digital twin containing data on building performance and operations.

This project is still ongoing, and my role is to lead this effort end-to-end, including product definition, data engineering/modeling, and technical coordination.

Problem Statement

How do you make meaningful energy improvements when your systems are already optimized?

That’s the question this building team posed but well, it’s a trick question. Their systems aren’t completely optimized, they just didn’t have the visibility and insight available to optimize beyond the traditional approaches.

So we planned beyond the traditional:

  • Monitor energy consumption by tenant and floor

  • Isolate equipment-level inefficiencies

  • Model energy performance relative to occupancy and weather

  • Quantify the ROI of equipment upgrades

  • And use that visibility to encourage behavioral change among tenants

Breakdown

We broke down the project into several parts, including these currently active solutions:

  • Floor-level energy insights for tenant behavioral changes

  • Chiller upgrade analysis

  • Building performance baselining and health gauge

Tenant-Level Energy Insights

We coordinated closely with building engineering to install tenant- and floor-level submeters across multiple phases. This effort aligned with a large tenant move-in and included the integration of CPower metering infrastructure. My job was to integrate with CPower and ensure the incoming submeter data flowed into Cohesion’s platform, mapped accurately to our space hierarchy (building > floor > space > equipment, etc).

The execution of this plan went as follows:

  • CPower data ingestion

    • Met with the CPower team to gather technical details.

    • Managed our internal engineering teams to integrate with their system via API and build a reliable data pipeline for ingestion.

  • Data modeling and alignment

    • In parallel I added the building’s equipment details to the Cohesion infrastructure, creating mappings of the HVAC equipment to spaces, zones or floors in Cohesion model of the building.

  • Reporting

    • Created tools and live dashboards with visibility into each tenant suite:

      • Occupancy

      • Indoor Air Quality

      • Maintenance Requests

      • Associated Equipment

      • Power / Energy Performance

This mapping unlocks per-suite energy analysis and enables real-time feedback loops for tenant engagement.

Equipment Telemetry & Chiller Upgrade Analysis

The building provided a large data dump of an aging chiller: power draw, current, voltage, phase angle and other data across multiple chillers. Shortly after, they replaced the chillers with new unit in a phased approach.

I spearheaded the analysis to compare old and new performance using power data normalized by degree days and occupancy. Our regression models control for:

  • Heating/Cooling degree days (sourced from NOAA)

  • Occupancy trends (from access control swipes + elevator usage data)

  • Equipment runtime profiles

By isolating weather and occupancy variables, we can estimate true performance improvement from the upgrade. This is key to building the business case for further capital investment.

Energy Health Gauge

Working with engineering and analytics teams, I helped define a new concept: a real-time “energy performance gauge”. This visualization shows whether current building energy usage is:

  • Within expected range (based on modeled baseline)

  • Above baseline by a measurable %

  • Below baseline (good performance)

This live feedback allows both engineering and property management to detect when something is "off"—whether due to equipment faults or unusual tenant behavior.

Results (So Far)

  • Full mapping of floor/tenant submeters to building model

  • Chiller replacement monitoring framework to calculate ROI

  • Regression baseline model combining weather + occupancy

  • Real-time performance gauge piloted and actively used by site team

  • Platform ready for future tenant engagement tools like energy scorecards

Quantifiable metrics are still emerging, but early analysis shows the new chiller reduced normalized energy use by 12-15%, with an estimated payback period of under 3 years.

Takeaways

This project represents a shift in mindset for buildings that have already “done everything right.” Once physical systems are optimized, human behavior and equipment-level telemetry become the new frontier.

Digital Twin is more than just dashboards—it’s a real-time decision support system for asset managers, engineers, and tenants alike.

As Cohesion’s product lead on this initiative, I translated building goals into real platform capabilities: from meter mapping to regression modeling to equipment ROI justification. This work has created a replicable model we’re now using to guide other energy-ambitious buildings across our portfolio.