Imperial College, United Kingdom

Imperial College London is consistently rated amongst the world’s best universities and is a science-based institution with a reputation for excellence in teaching and research. Imperial embodies and delivers world class scholarship, education and research in science, engineering, medicine and business, with particular regard to their application in industry, commerce and healthcare.
The Control and Power group at Imperial has a long and outstanding track record of research and innovation in the field of Energy Systems which includes the investigation of innovative concepts, technologies, and software and hardware applications to achieve cost-effective integration of renewable generation, responsive demand and energy storage technologies into operation and development of future electricity systems. The group has also provided leadership in the area of market integration, economics and regulatory aspects of future energy systems. The research team led by Prof Goran Strbac developed novel advanced whole-system based approaches and methodologies that have been extensively used to inform electricity industry, governments and regulatory bodies about the system integration costs, role and value of emerging new technologies and systems in supporting effective evolution to smart low-carbon future in an integrated energy system. In particular, significant recent developments have been carried out in the area of assessing the role and value of flexibility across different energy vectors in facilitating cost-effective decarbonisation of energy supply.

Key Investigators

Prof. Goran Strbac is a Professor of Energy Systems at Imperial College London, with extensive experience in modelling and analysis of operation, planning, investment and economics of electricity systems. He led the development of novel advanced whole system based approaches and methodologies that have been extensively used to inform electricity industry, governments and regulatory bodies about the system integration costs, role and value of emerging new technologies and systems in supporting effective evolution to smart low carbon future. He is a member of the Steering Committee of the SmartGrids European Technology Platform, Member of DECC Panel of Technical Experts for EMR implementation, Co-chair of Sustainable Districts & Built Environment of the EU Smart Cities and participates in working groups and committees within CIGRE, CIRED IET, IEEE and IEA. He has co-authored 4 books and published over 180 technical papers.

Dr. Marko Aunedi
is a Research Associate at the Control and Power research group at Imperial College London. His research interests cover generation scheduling under uncertainty, system operation with high penetration of renewable and less flexible generation and the impact of flexible technologies on energy system operation. He has almost 15 years of research experience in energy systems modelling analysis and optimisation and has been involved in a number of European and UK-based research projects. He also contributed significantly to a number of studies on the transition towards the low-carbon energy system. As part of his project work, he has developed and applied models to study the contribution of smart grid technologies to power system operation and design. He has published a number of scientific publications as well as delivered invited lectures on benefits of smart grid and energy storage in many events throughout the world.

Dr. Danny Pudjianto
has expertise in power system modelling, analysis and optimisation, power system economics, regulation, system operation, strategic planning, system security and technology integration from power system perspective including smart grids, active network management, demand response, distributed generation, energy storage, and energy networks. He has more than 10 years’ experience with public and private sector research projects at the international level. He led the development of the Whole Electricity System Investment Model (WeSIM) that has been applied in a number of recent projects. His research interests include impact assessment of implementing alternative network design, standards and operation strategies, e.g. active network management, demand response and network control technologies on the system performance. He has published more than 55 technical papers.

Completed and on-going projects

  • EPSRC, “Whole Systems Energy Modelling Consortium (wholeSEM)”. Imperial leads the multi-energy infrastructure modelling theme in the EPSRC wholeSEM project. Total £4.6m with £800k to Imperial team: G. Strbac (Co-Investigator) and M. Aunedi, 2013-17.
  • EPSRC, “Energy Storage for Low Carbon Grids”. Total £5.6m with £1.2m to Imperial team: G. Strbac (Principal Investigator), M. Aunedi and D. Pudjianto, 2012-17.
  • EC FP7, “eStorage: Solution for cost-effective integration of renewable intermittent generation by demonstrating the feasibility of flexible large-scale energy storage with innovative market and grid control approach”. Total £13.3m with £0.825m to Imperial team: G. Strbac, M. Aunedi and D. Pudjianto, 2012-17.
  • EC FP7, “Green eMotion: Development and demonstration of a unique and user‐friendly framework for green electromobility in Europe”. Total £13.3m with £0.707m to Imperial team: G. Strbac, M. Aunedi and D. Pudjianto, 2011-15.
  • EC Horizon 2020, “IndustRE: Using the flexibility potential in energy intensive industries to facilitate further grid integration of variable renewable energy sources”. Total £2.4m with £0.353m to Imperial team: G. Strbac and D. Pudjianto, 2015-18.

Other recent EU projects include: FENIX (SES6-518272), SMART-A (EIE/06/185//SI2.447477), DG Grid (EIE/04/015/S07.38553), MICROGRIDS (ENK5-CT-2002-00610), More-Microgrids (PL019864), IRENE-40 (218903), G4V (241295), Green eMotion (265499), eStorage (295367), ClusterDesign (283145), IndustRE (646191) and UPGRID (xx). Recent EPSRC projects include Top and Tail, Aura-NMS, SUPERGEN HiDEF, FlexNet, HDPS, Realising Transition Pathways, Energy Storage for Low-Carbon Grids. Imperial also leads one UK-China Smart Grid project and contribute to another 3 UK-China and 2 UK-India Smart Grid projects funded by the Research Council of the UK.

The Imperial team has been researching integrated energy networks and the interaction between electricity, gas, heat, cooling, hydrogen and electrified transport systems for a number of years and has developed a number of bottom-up models of heat and transport demand. More recently a novel whole-system modelling concept has been developed that co-optimises investment in energy infrastructure (supply, transport, distribution) as well as the operation of this infrastructure in the future largely decarbonised energy systems. The tools that have been developed previously, and which will be further developed and applied in the course of the project include:

    • WeSIM (Whole-electricity System Investment Model) is capable of capturing the interactions between different time scales (investment vs. short-term operation) as well as across different asset types in the electricity system, while also considering the flexible technologies such as energy storage or demand-side response. By simultaneously balancing long-term investment decisions against short-term operation decisions, WeSIM is able to identify overall optimal strategies for the electricity system, with the potential to expand it to other energy vectors. WeSIM co-optimises the provision of energy and ancillary services in the system (operating reserve and frequency regulation), and also allows for imposing an explicit carbon emission constraint. The model is also able to quantify the necessary investments in distribution networks based on the concept of statistically representative networks. The model has been implemented in the FICO Xpress platform and the diagram of the model is shown in Figure X (Pudjianto et al, 2014).

    • Fractal energy distribution network model: This model generates statistically representative networks based on the topological properties of actual electricity, gas and heat networks that are used for calibration. Its primary objective is to estimate the need for and the cost of distribution infrastructure expansion for different demand, generation and flexibility scenarios. The model relies on the fact that the reinforcement cost in distribution networks tends to be driven by the network length, which is a function of consumer density. Using a limited number of statistically representative network types (e.g. for urban, rural or intermediate areas) allows for a very accurate estimate of reinforcement costs on national or regional level. Several examples of representative networks are shown in the figure below. The model is currently being expanded to cover other vectors such as heat networks.

    Key publications

    • Pudjianto D, Aunedi M, Djapic P, Strbac G, “Whole-Systems Assessment of the Value of Energy Storage in Low-Carbon Electricity Systems”, IEEE Transactions on Smart Grid, vol. 5, pp. 1098-1109, March 2014. DOI: 10.1109/TSG.2013.2282039.
    • Teng F, Aunedi M, Strbac G, Benefits of flexibility from smart electrified transportation and heating in the future UK electricity system, Applied Energy, Oct 2015, DOI: 10.1016/j.apenergy.2015.10.028
    • Papadaskalopoulos D, Strbac G, Mancarella P, Aunedi M, Stanojevic V, Decentralized Participation of Flexible Demand in Electricity Markets—Part II: Application With Electric Vehicles and Heat Pump Systems, IEEE Transactions on Power Systems 05/2013; PP(99):1. DOI:10.1109/TPWRS.2013.2245687
    • Pudjianto D, Djapic P,·Aunedi M,·Gan C K, Strbac G, Huang S,·Infield D, Smart control for minimizing distribution network reinforcement cost due to electrification, Energy Policy 01/2013; 52:76–84. DOI:10.1016/j.enpol.2012.05.021
    • Chaudry M, Jenkins N, Strbac G, Multi-time period combined gas and electricity network optimisation, Electric Power Systems Research, 78 (7) (2008) 1265-1279 ISSN 1873-2046 10.1016/j.epsr.2007.11.002