How does EMMA AI get its energy data?

Energy efficiency is not just an environmental concern but also an economic imperative. Businesses are increasingly looking for ways to optimise their energy usage, reduce waste, and cut costs. Enter EMMA AI, a revolutionary learning platform that leverages half-hourly energy data to identify trends and anomalies in electricity consumption. But how does it all work? Let’s dive in to understand what’s behind the ‘magic’.

 

What is Half-Hourly Energy Data?

Half-hourly energy data refers to recording electricity and gas (energy) consumption in 30-minute intervals. This provides a detailed view of your energy usage patterns throughout the day. Unlike monthly or daily readings, half-hourly data allows us to understand more precisely where your energy is being consumed.

Importantly, as a business, you can get this data per site from your existing energy supplier or broker – you’ve probably just never needed to ask for it!

This granularity is crucial for spotting inefficiencies and energy-saving opportunities that might go unnoticed, but it’s a lot of data. For example, if you have 500 locations each reporting data every 30 minutes, then that’s 24,000 readings every day or over 700,000 each month. Clearly that amount of data cannot be processed manually – which is why most businesses have no choice but to not use it.

 

How is the Half-Hourly Energy Data Reported to EMMA AI?

The process begins with your existing energy supplier. Most modern energy meters, especially those used by businesses, will capture half-hourly data. EMMA AI securely collects this data using whichever mechanism your supplier employs, with most suppliers now providing secure API access (a mechanism that essentially allows disparate computer systems to talk to each other easily). Typically, we operate on a day+1 model, whereby EMMA AI will collect data from the previous day.

Once the connection between your supplier and EMMA AI is setup, there’s nothing more for you to do.

 

How Does EMMA AI Learn?

Once the half-hourly energy data is connected, EMMA AI gets to work. The platform uses advanced machine learning algorithms to analyse the data, identifying patterns and anomalies. For example, EMMA AI can detect:

Out-of-the-norm usage:

One of the most common errors sites make is simply leaving heating, lighting or other electronics on when they leave for the day.

Spikes in the middle of the night:

If there are unexpected increases in energy usage during off-hours, it could indicate equipment running unnecessarily or other inefficiencies.

HVAC anomalies:

The system can spot, for example, if heating, ventilation, and air conditioning (HVAC) systems are not turning off at the predicted times, suggesting potential malfunctions or scheduling issues.

The machine learning capabilities of EMMA AI also consider things like site size, location and weather – comparing all your unique site data with anonymous data taken from other sites that have similar usage. EMMA AI continuously learns from the data it processes, improving its accuracy and insights. This adaptive learning capability ensures that the platform remains effective despite changing energy usage patterns.

Informing Staff and Creating an Army of Energy Managers

One of the standout features of EMMA AI is its ability to democratise energy management. Instead of relying solely on central headquarters to monitor and manage energy usage, EMMA AI sends email alerts to the staff at your various sites and outlets. This approach empowers on-the-ground personnel to immediately act when anomalies are detected, turning your employees into an army of Energy Managers!

Financial Impact: Saving Up to £1 Million Annually

The financial benefits of using EMMA AI are substantial. By identifying and addressing inefficiencies, businesses can significantly reduce their energy bills. Typically, EMMA AI can identify savings in the hundreds of pounds per site per month – which rolls up to significant savings when running multiple sites. William Hill, for example, recently reported savings of up to £1 million annually.

In addition to the tangible financial energy savings, reducing equipment usage and preventing costly equipment failures also produces additional unquantifiable savings.

In summary

EMMA AI’s innovative use of half-hourly energy data represents a significant advancement in energy management. By harnessing the power of detailed consumption data and machine learning, EMMA AI provides businesses with actionable insights to reduce waste and save money.

The platform’s ability to empower staff at all levels further enhances its effectiveness, creating a comprehensive and decentralised approach to energy management. In an era where sustainability and cost efficiency are paramount, EMMA AI is vital for businesses looking to optimise their energy usage.

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