Deep changes are happening in the supply side of energy systems. The UK has halved carbon emissions from electricity system from over 150 million tonnes in 2012 to under 70 in 2018 and China is adding about 20 GW of wind generation capacity per year and has replaced all buses in the city of Shenzhen with electric busses. Very clearly there is much more to do: the remaining decarbonisation of electricity, the electrification of other sectors and sourcing alternative, zero-carbon fuels. Cities have traditionally been huge consumers of energy brought in from their hinterland and yet load growth in energy networks is inevitable as more services, notably transport, are decarbonised through electrification and building density increases through re-development of with taller buildings. The traditional response to this, adding more plant and equipment, is recognised as being an inefficient. An interesting trend is the emergence of Local Energy Systems (LES) and Multi-Energy Micro-Grids (MEMG). LES and MEMG are a means for raising self-consumption of local energy resources; tapping into sources of flexibility in how the services derived from energy; using local services for both local and national control and moving to a smart ways of ensuring resilience. The recent power outage in the UK (9/8/19) highlighted that transport systems and other urban infrastructure are particularly vulnerable. A re-imagining of how resilience is provided in the urban setting could hugely reduce that vulnerability. Despite the differences between the histories and geographies of cities in China and the UK, we find common challenges and a complementary set of research expertise. This project brings together experts in power electronics, optimisation, control and fault-management from UK and China. Existing energy networks, especially electricity networks, were designed assuming power enters a city from remote power stations and the network inside the city distributes this. This led to a radial set of lines spreading out from substations. This structure is unable to support the formation of flexible microgrids around local generation and storage resources. We propose to re-structure the legacy networks using power electronics devices that give controlled power flows between previously unconnected networks points. This opens up dynamically restructuring the power flow in urban areas to allow greater local self-consumption of energy, for instance moving solar power residential properties to work-place charging of electric vehicles. It also allows islands to be formed in reaction to power cuts that keep essential services running while placing non-essential services on hold. We also look at hardware and control issues. The hardware for electronic routing of power has been discussed in principle but it is too large and not efficient enough to be used in urban settings. We will work on new forms of modular power converter that raise efficiency, reduce physical volume and provide resilience to component failures. Control systems for energy networks are centralised: they gather data from across large areas, make decisions and then issue commands. The microgrid concept changes this to a decentralised approach. A key benefit of decentralisation is the ready access to information about flexibility in energy consumption, e.g which electrical vehicles could delay charging or might supply power to aid with a power cut. Local control also gives opportunities to run the heat/cooling of buildings, the transport energy system and the electricity system as an integrated whole. This can lead better integration of renewable energy and therefore deep decarbonisation but requires a major step forward in managing uncertainty over the local energy resources and demands. We will bring the techniques of stochastic optimisation and machine learning to bear on this problem and devise a control and operations framework for smart urban energy systems.

The UK has a commitment to reduce its greenhouse gas emissions by at least 80% by 2050 relative to 1990 levels. DECC's 2050 Pathway Analysis shows the various ways through which we can achieve this target. All feature a high penetration level of renewable generation and a very substantial uptake of electrification of heat and transport, particularly from 2030 onwards. This will place unprecedented demand and distributed generation on electricity supply infrastructure, particularly the distribution systems due to their size. If a business as usual model is to apply, then the costs of de-carbonisation will be very high. Being equally confronted by the pressure of global climate change and sustainable development, the Chinese government has declared that by 2020 the carbon emission per-unit GDP will reduce to 40-45% of that in 2008. However China also needs to meet a 10% annual demand increase which has been on-going for the past 20 years, and this rate of growth is expected to continue for at least another 10 years. Therefore reinforcement of current distribution networks in an economic and sustainable way while meeting customers' rising expectation of supply quality and reliability is one of the basic requirements of Smart Grid development in China. It is a matter of urgency to investigate how to develop and adapt the current distribution network using Smart Grid interventions in order to facilitate timely connection of low carbon and sustainable technologies in a cost-effective manner. This is a global challenge faced by UK, China and many other countries. Our consortium brings together leading researchers from the UK and China to jointly investigate the integrated operation and planning for smart distribution networks to address two key research challenges: (1) Conventional network operational and planning approaches do not address the emerging opportunities offered by increased measurement and control and do not deal with the inevitable uncertainties of smart distribution networks. (2) A general understanding of how national or regional electricity distribution infrastructure should be developed and operated using Smart Grid interventions is required urgently by those making policy within Distribution companies and in Government/Regulators. Such an understanding cannot be gained from running conventional power system analysis tools and then manually assessing the results. New techniques and approaches will be investigated to address these important questions (1) Distribution state estimation and probabilistic predictive control approaches will be used to determine the location and control policies of smart grid interventions including Soft Open Points and electronic embedded hybrid on-load tap changers. (2) Novel dynamic pricing techniques will be proposed to resolve conflicts between energy markets and network operation and find synergies where these exist. (3) A very fast network assessment tool and a rolling planning tool that will bridge the gap between planning and operation will be developed. (4) New visualisation and reporting techniques will be developed to give network planners, operators as well policy makers clear insights as to how Smart Grid interventions can be used most effectively. Complementary, cross-country expertise will allow us to undertake the challenging research with substantially reduced cost, time and effort. The research will build upon the long-time well established collaborations between partner institutions of the two countries. Our ambition is to provide a strategic direction for the future of smart electricity distribution networks in the 2030-2050 time frame and deliver methodologies and technologies of alternative network operation and planning strategies in order to facilitate a cost effective evolution to a low carbon future.

The "SmartGrid" is a concept that has emerged from its initial discussion in engineering circles into the wider public arena because its importance has been recognised for securing future electricity supply and facilitating the de-carbonisation of electricity. Much of the SmartGrid debate has so far focused customers with "smart homes" or "smart appliances" being engaged in managing the electricity system through their reactions to signals about price or availability of renewable energy. Behind the scenes, there is a parallel debate about how new control methods for existing electricity plant and equipment may enable electricity networks to offer the flexibility needed to incorporate low-carbon energy sources. This proposal expands the SmartGrid debate in two directions. First, large numbers of people in developing countries suffer from an intermittent electricity supply. The supply companies use "rota disconnection" schemes to ration the limited energy available in some regions. Having electricity for, say, just 4 hours a day adversely impacts education, health care and economic development. "Micro-grids" able to run "off-gird" with local solar or micro-hydro energy are interesting in this context. Our proposal here is to design "on-off grids" in which supply companies adjust their rota disconnection to account for local resources in the micro-grids and the micro-grids are configured with power electronic interfaces that can manage the frequent transitions between on-grid and off-gird operation. The consortium members in India will build a demonstration version of such a micro-grid to allow control and optimisation ideas to be explored and assessed. The use of energy storage technology will be a key part of this scheme. Second, developed countries do not suffer rota-disconnections except in emergencies. However, the security and adequacy of their existing electricity distribution networks may become compromised by the injection of significant amounts of solar energy at household level and the heavy loading anticipated from electric vehicle charging. Here we propose to develop power electronic equipment that enables the rapid reconfiguration of the possible supply routes in a network in order to optimise the power flows and voltage levels. The questions are not so much on can power electronic devices achieve this (we are confident they can) but rather how is it achieved efficiently and with a good equipment lifetime. The UK members of the consortium will design, build and test new forms of "soft meshing" power electronics to meet these objectives. The "reconfigurable distribution network" presents a great opportunity in both the Indian and UK context. It also present research challenges on a number of fronts: innovation in power electronic equipment to reduce power losses and increase lifetime; the need to design new control algorithms to exploit the new flexible equipment to the benefit of consumers and network operators and the need to create new optimisation and planning tools to indicate where exactly the new equipment should be deployed and to determine how robust its business case can be.

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.