AI software to predict and intelligently control building energy assets, creating a new form of dynamic flexibility within the customer's optimal comfort, carbon and cost profile.

About

At Grid Edge, we want to change the way that people use energy by putting intelligent control into the hands of commercial energy consumers, creating new value on their side of the meter. Formed as a spin-out company from Aston University, Grid Edge is an artificial intelligence (AI) start-up company that provides cloud-based AI software services that empower these commercial energy consumers to PREDICT, OPTIMISE and CONTROL their building energy loads. Specialising in hybrid deep-learning and artificial neural networks algorithms, our cloud-based software services work in harmony with building energy management systems to reduce energy costs, cut carbon emissions and unlock the revenue-generating potential of flexible energy assets, enabling consumers to become active and intelligent participants in the energy system. We know that public and commercial building owners are looking for a better way to manage energy and engage with energy markets, DNOs and suppliers on their terms. As flexibility becomes the most valuable commodity in the 21st century energy system, building operators are now looking to unlock the value of their flexible and dispatchable energy assets (HVAC, CHP, EVs, Heat Pumps, PV with storage) on their terms. A key application for this new form of consumer-empowered flexibility is to forge a new relationship between consumer and DNO. We know that DNOs face significant network challenges arising from connecting more distributed generation and customers to their network, dealing with issues including undesirable reverse power flow, changing load demand curves, increasing voltage and unpredictable thermal constraints on the network. The traditional DNO approach to these challenges is to carry out expensive network upgrades to protect their network assets or to undertake active network management schemes, with the costs passed to bill payers in the form of DuoS (and other) charges. Looking farther ahead, the implementation of RIIO-ED2 (2nd regulatory price control policy for electricity distribution) from 2023 will drive these charges upwards and require DNOs to procure additional innovative services in order to manage and control power demand as well as distributed energy resources such as wind turbines, solar panels and energy stored in batteries and electric vehicles. Grid Edge is able to offer an alternative approach to active network management schemes by shifting our customers’ demand out of peak periods to enable avoidance of ‘red band’ DUoS charges based on consumption during peak times.

Key Benefits

Commercial building operators are on the front line of an energy system in a state of flux, with their building’s energy and carbon costs becoming more dynamic, volatile and harder to control. This means smart energy management is no longer about how much energy you use, it’s about when you use it. At Grid Edge, we want to put intelligent, data-driven control into the hands of commercial energy consumers. We provide AI software services that apply hybrid deep-learning and neural network algorithms to predict, optimise and control building energy loads. Our software is designed to sit at the nexus of the building management and energy systems ‘worlds’ and aims to enable a better flow of information across the meter to connect consumers with upstream actors on their terms. Through our predictive load forecasting innovation, we are able to turn buildings into batteries and unlock the value of unconventional and underutilised energy storage assets (such as a building’s thermal inertia) to create dynamic flexibility within a customer’s optimal energy profile and make this flexibility available for balancing services, DNO services and dynamic tariff products. With our AI technology, you can create a unique foresight-driven approach to building energy management and dynamically optimise your building’s day-ahead energy, carbon and comfort profile. Beyond flexibility, real-time optimisation of building energy profiles can create significant financial savings through efficiency gains and load-shifting demand out of peak-pricing periods. Furthermore, by optimising a building’s energy profile we can reduce its operational carbon footprint, enhance sustainability credentials and avoid CRC payments.

Applications

Our target customers are public and commercial building owners that face pressure to optimise their energy profiles and who offer multiple sites for deployment. Target market segments include high-density housing; commercial buildings; infrastructure sites; and public sector buildings. We have successfully secured contracts with early adopters in each of the segments. In broad terms, our target market is public and commercial building operators that fit the ‘medium’ energy consumption profile as set out by the Digest of UK Energy Statistics (DUKES), which would equate to the typical energy profile of a high-density housing development, retail mall, hotel or office building. Beyond building assets, the UK's forthcoming fleet of smarter, more connected and bi-directional electric vehicles provides a opportunity for vehicle and charge infrastructure owners to enable their assets to participate in energy markets. Our predictive optimisation IP allows this opportunity to be accessed whilst maintaining charge performance and user trust around 'auto-grid-edge' transactions. The Grid Edge Founders have been at the forefront of the UK's development of intelligent electric vehicle charging infrastructure and have commissioned and operate the UK's first Vehicle-to-Grid (V2G) charging system as part of our award-winning ITHECA project. Grid Edge is part of the £1.5million VIGIL project to demonstrate how EVs can be intelligently dispatched to provide load management services for the DNO network.

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