Scheduled to start in May, 2020, the EV Fleet-Centred Local Energy Systems (EFLES) project is aimed at optimising logistics companies’ growing electric vehicle (EV) fleets, with the added benefits of cutting carbon emissions, air pollution and energy costs.
Moixa intend to show how its GridShare artificial intelligence (AI) software can maximise the cost and carbon savings from EVs. GridShare will analyse hundreds of data sources at UPS’ Camden depot – including energy prices, power demand and the weather – to optimise EV charging, as well as power supply and demand in order to demonstrate how to effectively cut costs. Vehicles will be able to charge when power is cheapest and cleanest by using onsite energy storage and solar at the most cost-effective times.
Simon Daniel, CEO of Moixa, told The Engineer that GridShare learns patterns in driver behaviour, and monitors and plans for variables, such as the cost of energy, to enable smart charging of EVs.
“We optimise these assets to charge and discharge at the most effective times to deliver cost-savings, cut carbon emissions and reduce air pollution,” he said. “GridShare can also aggregate and manage these assets to respond to signals from the power grid to enhance the resilience of local power networks and prevent overloading and blackouts.”
There are said to be over five million vans, trucks and buses on UK roads and by 2040 87 per cent of these are expected to be electric.
“Our ever-growing online shopping rates mean we’re delivering more things than ever before – everything from food shopping to medical supplies – and that’s having a big impact on carbon emissions and air pollution in our cities,” Daniel said in a statement. “Mitigating these impacts is a massive challenge but this project shows how with the help of the AI powered technology, like GridShare, the world’s biggest fleet operators can go electric and achieve their environmental ambitions.”