Resilient Operation of Sustainable Energy Systems (ROSES)

Upgrade of UK energy system is at the core of Smart systems and flexibility plan laid out in the Government's Industrial Strategy. Beijing, Shanghai, Guangzhou and Shenzhen are aiming to build up world-class distribution networks as they are among the target areas for export promotion. The massive uptake of renewable generations in both the UK and China offers a huge challenge requiring expensive balancing mechanism. It is only through fundamental research focused on addressing these challenges that truly transformative changes to our energy future beyond 2050 can happen. The purpose of this proposal is to carryout underpinning research with an objective to develop tools that will make our electricity supply system resilient as well as sustainable. It will be both data and model driven activities of a strong consortium of technical experts from both sides. The data driving machine learning tool will deliver operational health index of various components in the system. It will employ dynamic state estimation to develop new network automation procedure to ascertain adequate margin of stability of operation of the network from adverse interactions between the non-synchronous generation and synchronous generation of the system. It will explore novel control and protection technology to safe guard the integrity of the operation of the system with randomly fluctuating output from renewables. The technical competence of the team covers range of expertise in power plant and network modelling, big data, machine learning, system dynamics, estimation, control, and power electronics in the context of interconnected power network operation and protection. Tasks proposed in the program of work will explore several methods of data pre-processing, feature extraction and dimensionality reduction. Faster and accurate identification of the fault location in the cable through impedance transfer function enabled eigen-value approach is revolutionary and so is the ML approach to sensor data optimization in fault location.
This is a consortium involving academic and industrial partners from a range of disciplines and different research environments and cultures. The PIs propose a jointly led project management team comprising of all the investigators. All the work packages involve researchers from both sides requiring regular exchange of researchers to carry on with the technical tasks. The RAs and investigators will spend two weeks in every visit to China with partner's organizations. Each work package has joint WP leaders who will coordinate within his/her group of researcher and reports to the PI. Both the PIs have led multinational consortia of even larger sizes and between them. A project advisory board (PAB) will be set up inviting the members from industry partners and technical experts from GEIRI, UKPN, Elin VERD, MHI, FTI Consulting. The PAB will help facilitate explore opportunity for engaging with industry and other user of the research outcome.
The PIs from both sides will network with other approved projects through a high-level board comprising of all PIs and representatives from RCUK and NSFC. There will be further networking through sponsoring session and technical paper in big conferences such as Power Tech, ISGT, CIGRE, CIRED, Power and Energy Society general meeting (PESGM), and participating in low carbon network innovation (LCNI).
The availability of meaningful data is at times challenging. Our strategy to manage such challenge will be to work on simulation data from model available in public domain, promised by industry supporter and introduce noise, contamination and missed data based on trend and practice in big data analytic domain in the context of power engineering drawing upon the experience and insight of the industry partners.

The research topics are very timely and strongly in line with the green growth and smart grid ambitions of both UK and China. The anticipated impact spans several sectors of the society and economy: it has the potential to make significant contribution to the scientific field; to have industrial impact by allowing for more robust and sustainable operation of electricity networks; to yield socio-environmental benefits by permitting higher integration of renewable energy sources; to make available more skilled personnel to serve the energy sectors of both the countries, to make engineering impact through research translations with industry partners, to foster a long-lasting collaboration and strengthen the two countries' position in the field of electric power systems.
The ambition of the project to reach such a deep level of understating in the interconnected power network modelling, control and protection, has not been attempted before and the results will be useful to the scientific community. Using at its core, the rapidly developing field of machine learning, decentralized control and protection, the consortium will be the first to investigate the impact of these transformative tools for delivering resilient power network operation.
The need for better monitoring in the transmission and distribution network is very timely for the transmission network operator (TNO) and distribution network operators (DNOs), such as our partners UKPN and SGCC, while relay and network automation/simulation vendors (NERC, MHI) are in search of new methods of network protection and faster fault location. The results of this project will contribute to a more robust, secure, and efficient network operation with substantial technical and financial impact to the power network industry; the high interest of our industry partners is a strong indication of this potential.
The expected research outcomes will provide insight to the government and other policy makers on their future investment strategies and how to proceed further towards a decarbonised electricity network. The project is in line with the UK China green energy growth delivery plan and policy and will contribute to meeting the targets in the electric energy sectors of both the countries and far beyond (as evidenced by participations of 11 industry partners from three continents). This will take scientific and technical partnership between the two countries to a new height in post Brexit era. Several investigators across both sides have already collaborated and delivered together through previous and ongoing UK China scientific collaborative research in the sector of energy.