{"id":312,"date":"2024-11-22T18:31:58","date_gmt":"2024-11-22T18:31:58","guid":{"rendered":"https:\/\/wp.lancs.ac.uk\/energy-group-self-aware-power-networks\/?p=312"},"modified":"2024-11-28T16:10:50","modified_gmt":"2024-11-28T16:10:50","slug":"200000-award-for-engineering-research-into-self-aware-power-networks-2","status":"publish","type":"post","link":"https:\/\/wp.lancs.ac.uk\/energy-group-self-aware-power-networks\/2024\/11\/22\/200000-award-for-engineering-research-into-self-aware-power-networks-2\/","title":{"rendered":"\u00a3200,000 award for Engineering research into self-aware power networks"},"content":{"rendered":"

Lancaster University has been awarded a \u00a3200,000 Research Project Grant from the\u00a0Leverhulme Trust<\/a>\u00a0to develop autonomous power and energy systems modelled on the self-organisation of living systems.<\/p>\n

The project led by Dr Xiandong Ma<\/a> from the School of Engineering is entitled \u201cSelf-Aware Power Networks: Autonomous Operation at Scale.\u201d.<\/p>\n

Dr Xiandong Ma<\/a>, a Reader in Power and Energy Systems at the School of Engineering, said: \u201cThis project aims to provide a sustainable system operation with optimised conditions. The research will support the autonomous operation of modern power grid systems to achieve self-maintenance, self-healing, and self-reconfiguration capabilities.\u201d<\/p>\n

The modern power grid is a complex and interconnected cyber-physical system comprising physical components such as power generators and cyber components that control the grid’s operation. Taming the complexity in such dynamic systems is an open research problem, while traditional approaches to addressing this are primarily limited to conventional decentralised and multi-objective resource management.<\/p>\n

This project explores a radically new holistic approach to power grid operation by developing a paradigm shift approach\u2014aided by advanced machine and deep learning – to mimic the self-organisation of living organisms.<\/p>\n

Our research seeks to understand the fundamentals: how a complex and dynamic energy system can autonomously monitor, search, configure, and subsequently optimise itself for future generation power systems. Our machine learning-assisted approach would mimic the innate and spontaneous self-healing systems in many living organisms, thereby maintaining their healthy state and avoiding the loss of vitality under disorders and attacks.<\/p><\/blockquote>\n

The modern power grid system has fundamentally changed from a classical hierarchical generation-transmission-distribution approach to an on-demand dynamic geo-distributed cyber-physical system. It also experiences various operating conditions as power generation profiles from renewable energy sources and user consumption patterns vary dynamically across physical locations and over time.<\/p>\n

The success of the project would transform future generation power systems to ensure their safe, stable, and optimised operation.<\/p>\n

\u201cThe proposed research will address a set of vital and yet-to-be-addressed challenges in the modern power grid system. The successful outcome of this research would open a door for developing new and innovative theories and tools for operating the power grid system in uncertain and unknown environments. The research would make key fundamental contributions to a range of disciplines concerning self-adaptive systems, applied machine learning, energy security, and power grid planning and operation.\u201d<\/p>\n

The project is a collaboration between the School of Engineering and Security Lancaster at Lancaster University.<\/p>\n","protected":false},"excerpt":{"rendered":"

Lancaster University has been awarded a \u00a3200,000 Research Project Grant from the\u00a0Leverhulme Trust\u00a0to develop autonomous power and energy systems modelled on the self-organisation of living systems. The project led by Dr Xiandong Ma from the School of Engineering is entitled \u201cSelf-Aware Power Networks: Autonomous Operation at Scale.\u201d. Dr Xiandong Ma, […]<\/p>\n","protected":false},"author":1857,"featured_media":0,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"activitypub_content_warning":"","activitypub_content_visibility":"","activitypub_max_image_attachments":4,"activitypub_interaction_policy_quote":"anyone","activitypub_status":"federate","footnotes":""},"categories":[14],"tags":[],"class_list":["post-312","post","type-post","status-publish","format-standard","hentry","category-news"],"jetpack_featured_media_url":"","_links":{"self":[{"href":"https:\/\/wp.lancs.ac.uk\/energy-group-self-aware-power-networks\/wp-json\/wp\/v2\/posts\/312","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/wp.lancs.ac.uk\/energy-group-self-aware-power-networks\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/wp.lancs.ac.uk\/energy-group-self-aware-power-networks\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/wp.lancs.ac.uk\/energy-group-self-aware-power-networks\/wp-json\/wp\/v2\/users\/1857"}],"replies":[{"embeddable":true,"href":"https:\/\/wp.lancs.ac.uk\/energy-group-self-aware-power-networks\/wp-json\/wp\/v2\/comments?post=312"}],"version-history":[{"count":1,"href":"https:\/\/wp.lancs.ac.uk\/energy-group-self-aware-power-networks\/wp-json\/wp\/v2\/posts\/312\/revisions"}],"predecessor-version":[{"id":314,"href":"https:\/\/wp.lancs.ac.uk\/energy-group-self-aware-power-networks\/wp-json\/wp\/v2\/posts\/312\/revisions\/314"}],"wp:attachment":[{"href":"https:\/\/wp.lancs.ac.uk\/energy-group-self-aware-power-networks\/wp-json\/wp\/v2\/media?parent=312"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/wp.lancs.ac.uk\/energy-group-self-aware-power-networks\/wp-json\/wp\/v2\/categories?post=312"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/wp.lancs.ac.uk\/energy-group-self-aware-power-networks\/wp-json\/wp\/v2\/tags?post=312"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}