Time Series for Intelligent Sustainability

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As the world continues to face unparalleled uncertainties due to climate change, using energy efficiently is more important than ever. Time series data plays a critical role in helping organizations operate in a greener and more sustainable way.

In Finland, EnerKey operates a platform that drives sustainability and energy management to unearth savings from consumption data. It helps organizations reduce their environmental footprint by combining weather, time series and geospatial data to monitor energy consumption, indoor air quality, waste and emissions. Real-time access to this information helps its clients to detect fluctuations in energy usage and make informed decisions on how to improve efficiency.

A focus on efficiency

EnerKey works with a variety of clients, including energy providers, local government entities, retail operators and commercial real estate owners. Many of these clients have many properties distributed across multiple cities. In total, the platform measures energy consumption from more than 140,000 meters deployed across more than 20,000 properties. The platform also needs to be able to handle utility data (i.e. water, electrical, heating) in over ninety different data formats. Once the EnerKey platform ingests all this data, it provides real-time insights to users that allows them to track energy usage across multiple properties.

In order to optimize performance and cost savings for customers, EnerKey needed a solution that could handle billions of metrics and provide access to historical data (from the previous 10 years in some cases). To handle all this time series data effectively, EnerKey chose InfluxDB.

Turning time series data green

It’s not enough to simply ingest and store time series data. The real magic with EnerKey is the platform’s ability to merge various data sets to actionable insights. EnerKey leverages InfluxDB to combine raw data from utilities with other building and environmental information, such as geospatial location data and external climate data, to deliver real-time analytics and to forecast future energy usage.

For example, EnerKey uses geospatial data to pinpoint the location of a property. It then uses climate data to analyze the impact that external weather has on that property. Tracking this data over time allows EnerKey to predict building energy needs based on the weather. Combining these insights with the actual energy usage of each property allows users to optimize usage so it’s more efficient. Even saving a few hundred Euros per building per month can translate into major savings for companies that own or manage hundreds of properties. EnerKey consolidates all this information in one place, so even users with broadly distributed property holdings can track everything in one place. This creates an additional operational efficiency, especially for real estate owners and management companies that pay close attention to utility usage and costs.

Having access to granular energy data allows EnerKey to help users in other ways, too. In multi-tenant facilities, the platform can distinguish usage for each individual unit, enabling commercial real estate clients to differentiate, and by extension better understand tenant usage. EnerKey’s ability to handle such a broad range of data and use cases improves energy efficiency in commercial buildings around the world.

All we need is less

As a company, EnerKey’s guiding principle is “all we need is less.” The EnerKey platform manifests that idea for clients by identifying areas where excessive energy use occurs and areas where users can improve energy savings. EnerKey helps clients save up to 30 percent on utilities. Not only is this a win for the bottom line, but the subsequent reduction in energy usage is a victory for the planet as well.

InfluxData is proud to be part of such an impactful project and jumps at the opportunity to partner with like-minded, eco-conscious companies because each partnership is a step toward a greener future. We are proud to work with EnerKey, and thrilled to see how its use of time series data makes the world a better (and greener) place.