Digital Twin to Analyse Energy Consumption Launches

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14 July 2021

A digital platform that allows users to simulate and analyse building portfolios' energy consumption has launched.

The Energy Open Piazza (EOP) allows businesses to look at the potential economic savings and reduction of carbon emissions introduced by solar generation and energy storage and compile the business plans needed to implement energy transformations.

 

Digital Twins and Carbon Emissions

 

The built environment today is responsible for 30 per cent of total emissions globally. Real-estate owners and developers are aware of incoming regulations that will translate to punitive measures for non-compliant assets, but making the right decisions to plan the required investments can be a challenge. Energy transformation for the built environment is slowed down by uncertainty on costs versus benefits, as well as the general complexity of markets and regulations.

Simplifying the assessment process with the adoption of a digital twin of the building and its foreseen energy transformation is the starting point to understand what are the contributing factors to the reduction of carbon emissions and their economics.

EOP is the only online solution that provides programmatic access to a powerful set of algorithms with knowledge of the grid's energy pricing and carbon intensity. It takes minutes, instead of weeks, to prepare a business plan that enables decision-makers to invest in the transformation of their built assets.

BEIS and NRCan have invested £1.5 million on the platform to prove that hybrid buildings are the best CSR investment for a net-zero future.

 

How Does the Technology Work?

 

The onboarding starts by entering a UK building address, postcode or building name. The map geo-coding functionality allows to retrieve the building’s main characteristics - like size and type - and customise input where needed.

The platform simulates and analyses the building load profile based on total consumption, as well as detailed building information such as flooring and type of HVAC used. Users can upload their half-hourly smart-meter readings and compare them with simulated data.

The platform creates an initial recommendation for storage and generation based on the available data. Energy solutions can then be tweaked to better fit the forecasted type of use and consumption. 

When users are happy with their scenarios, the system computes a detailed feasibility analysis.

Picture: a photograph of a wind turbine

Article written by Ella Tansley | Published 14 July 2021

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