Tackling the Complex and Global Issue of Climate Change
On a global scale, governments have expedited their objectives toward effective mitigation of climate change.
Integrated Energy System Illustration. Image Credit: Heriot-Watt University.
In this fight to handle the complicated and universal problem of climate change, what is evident is that no single technology or stakeholder can power the entire, timely decarbonization that is needed by the world and its people.
Thus, under this global energy transition, there is an unparalleled rise in decarbonization investments along with new levels of accessibility to both markets and energy systems. Therefore, the main research question is how well to comprehend and maximize the value proposition for various stakeholders.
Heriot-Watt University
Governments throughout the world have accelerated their ambitions towards effective climate change mitigation. What is clear, in this challenge of how to tackle the complex and global issue of climate change, is that there is no one technology or stakeholder that will drive the full and timely decarbonisation that the world and its citizens require.
Therefore, as part of this global energy transition, there is an unprecedent increase in decarbonisation investments accompanied with new levels of accessibility to both energy systems and markets. So, a key research question is how best to understand and optimise the value proposition for different stakeholders. Due to the need to fast track decarbonisation and to ensure that this is an inclusive energy transition with social justice and equity at its core, we need to understand the dynamics and interdependencies across people, technology and economics.
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Researchers Develop New Machine Learning Method to Estimate Battery Health
Written by AZoRoboticsApr 12 2021
Electrical batteries are increasingly crucial in a variety of applications, from integration of intermittent energy sources with demand, to unlocking carbon-free power for the transportation sector through electric vehicles (EVs), trains and ships, to a host of advanced electronics and robotic applications.
A key challenge however is that batteries degrade quickly with operating conditions. It is currently difficult to estimate battery health without interrupting the operation of the battery or without going through a lengthy procedure of charge-discharge that requires specialised equipment.
In work recently published by
Researchers at Edinburgh’s Heriot-Watt University have developed an AI framework to accurately predict battery health using simple voltage and current data.