Verdigris Technologies > Case Studies > Automating the Measurement & Verification of Energy Efficiency

Automating the Measurement & Verification of Energy Efficiency

Customer Company Size

Large Corporate

Region

Pacific

Country

United States

Product

DeltaMeter
Verdigris
eQUEST

Tech Stack

Cloud Computing
Machine Learning
Big Data Analytics

Implementation Scale

Pilot projects

Impact Metrics

Cost Savings
Customer Satisfaction
Productivity Improvements

Technology Category

Analytics & Modeling - Big Data Analytics
Analytics & Modeling - Machine Learning
Functional Applications - Remote Monitoring & Control Systems

Applicable Industries

Buildings
Utilities

Applicable Functions

Facility Management
Maintenance

Use Cases

Building Energy Management
Energy Management System
Predictive Maintenance

Services

System Integration
Software Design & Engineering Services

About The Customer

The case study focuses on building owners in the Pacific Northwest who are increasingly prioritizing energy efficiency due to rising energy costs and a competitive rental market. These building owners face challenges in tracking the return on investment (ROI) from energy efficiency upgrades due to the dynamic nature of buildings. Factors such as shifting weather patterns, changes in occupancy, and varying equipment lifespans complicate the isolation of savings from energy efficiency investments. Traditional methods of verifying savings, such as hiring energy engineers to create predictive thermodynamic energy models, are often complicated and expensive. The case study discusses two low-cost methods available to building owners to improve the tracking of ROI from energy efficiency efforts.

The Challenge

Building owners and property managers face significant challenges in verifying the return on investment (ROI) from energy efficiency measures due to the dynamic nature of buildings. Factors such as shifting weather patterns, changes in occupancy, and varying equipment lifespans complicate the isolation of savings from energy efficiency investments. Traditional methods of verifying savings, such as hiring energy engineers to create predictive thermodynamic energy models, are often complicated and expensive. These methods involve intensive data collection and calibration processes, which can cost between $0.10 to $0.50 per square foot, making them cost-prohibitive for many building owners. Additionally, traditional methods have limited capability for tracking ongoing performance, which is crucial for identifying failures or below-average performance of energy efficiency measures.

The Solution

The case study explores two low-cost automated measurement and verification (M&V) technologies: DeltaMeter and Verdigris. DeltaMeter, developed by EnergyRM, is a software platform that uses patented algorithms and monthly energy bills to create a thermodynamic model at the end-use level. This model estimates the baseline energy use and tracks the actual building performance to reveal the savings achieved. DeltaMeter does not require physical deployment at the building site and offers diagnostic analysis, savings potential recommendations, and ongoing M&V crosschecks. Verdigris, developed by a Northern California-based company, uses advanced analytics and in-house M&V technology to analyze high-resolution electricity consumption data from building circuits. Verdigris employs custom machine learning algorithms to predict a baseline and disaggregate energy by end use. The platform provides real-time data streams, energy efficiency recommendations, peak demand analysis, and equipment-level monitoring. Both technologies were deployed in a pilot project at eight high-profile commercial buildings in Seattle, commissioned by the Smart Buildings Center (SBC) in partnership with the Northwest Energy Efficiency Alliance (NEEA). The pilot aimed to evaluate the accuracy, ease of installation, scalability, and training time for operations staff.

Operational Impact

Both DeltaMeter and Verdigris provided ongoing low-cost options for evaluation, measurement, and verification (EM&V) of energy efficiency measures.
The technologies generated regular monthly reports, allowing building managers to track energy use and savings against a baseline throughout the year.
The pilot project demonstrated that both technologies could offer a cost-effective alternative to traditional energy modeling and sub-metering processes.
The regularity of reports and granular real-time interval data added value to building owners, enabling them to respond to trends and undertake performance-driven course corrections.
The use of cloud storage alleviated the burden of increasing on-site data storage for traditional sub-metering efforts.

Quantitative Benefit

DeltaMeter's single building product pricing is approximately $300-$500 per month, with larger portfolios dropping to below $100/building.
Verdigris technology cost is approximately $1,500 per building, assuming 8-10 panels with detailed monitoring installed.
Traditional comprehensive modeling and analysis process costs range from $0.10/sq ft to $0.50/sq ft, with additional annual costs of $5,000-$8,000 for calibration and analysis.
The predictions from both technologies were within +/- 0-10% of actual monthly energy use and within 5% of actual annual energy use for most buildings in the pilot project.