Managing energy performance across large property portfolios

Background

In response to their 2050 net zero goals, and increased scrutiny on ESG reporting, the sustainability team at a UK Real Estate Investment Trust (REIT) developed a net zero strategy to assess portfolio energy consumption. The aims of the strategy included identifying opportunities for improved environmental performance through energy efficiency, reduced operating costs, reduced emissions and enhanced property value.

A key challenge for meeting these aims was accessing reliable data – cost-effectively and at scale – to inform investment decisions.

Analyzing operational energy consumption across a commercial property portfolio

The REIT approached arbnco to trial our Energy Optimization Suite (EOS) due to the uniqueness of the platform and its ability to analyze consumption interval data to baseline the performance of each building. The ability to perform such granular analysis, through our state-of-the-art disaggregation algorithm, provided actionable analysis for the REIT to act quickly on.

The EOS provided a single source for managing energy performance and compliance across the REIT’s large and diverse property portfolios. It centralized large data sets for continuous monitoring and delivered bespoke retrofit strategies to ensure that the REIT’s asset values were protected. By providing enhanced understanding of the relationship between building energy models and compliance ratings, this allowed for capital expenditure savings and effective investment planning. The EOS delivered a real time interface showing the current status of the REIT’s buildings at portfolio level. Filter options then enabled information to be segmented to instantly generate bespoke risk reporting from asset / property manager to tenant type and more.
By viewing their entire portfolio at a glance, the sustainability team was able to efficiently target energy performance improvements and manage compliance risk. In order to do this effectively, the EOS automatically generated energy conservation measures which allowed the team to identify energy saving methods across their portfolio of buildings and to reduce carbon, therefore, working towards the ultimate goal of achieving net zero. The advanced and patented machine learning techniques also delivered deep insight into consumption patterns and behaviours, allowing the REIT to closely identify detailed methods to reduce future energy consumption.

This informed data driven decision-making for retrofit works to reduce energy consumption and to bring properties closer to achieving the overall net zero goals.

Outcomes

The deployment of our EOS to analyze operational energy consumption at scale enabled:

• Cost-effective risk analysis of portfolio
• Prioritization of at-risk properties for further investigation and action
• Informed investment decisions on the most appropriate compliance route
• Tracking and benchmarking to determine future energy consumption
• Enhanced portfolio resilience
• Contribution to ESG reporting through detailed Energy Conservation Measures

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