Skoltech Center for Energy Systems



Energy Systems Center for Research, Education, and Innovation (ES CREI) is one of nine Skoltech centers with was initiated in 2013 and since that time ES CREI has significantly grown in number of people, projects successfully finished, courses taught and is continuing its development. The main principle of research followed in Skoltech Center for Energy Systems is an interdisciplinary approach. We are employing or collaborating with researchers representing wide variety of disciplines (engineers, mathematicians, physicist, economists, etc.) in order to utilize advances in new technologies (ICT, communication networks and sensing) and algorithms (distributed control, networks science, complex systems)  and to create a cyber-physical energy system able to deal with the challenges of the 21st Century. We believe that in this respect Skoltech Center for Energy Systems is a unique in the world and able to deliver a significant step, rather than incremental change.

Mission Statement

  • To establish an internationally-recognized, multidisciplinary, research, education and innovation center of excellence in energy systems.
  • To engage with Russian industry to apply new developments in ICT and modern optimization and control tools to improve efficiency and resilience of the Russian power system.

Main Research Areas

  • Smart and Resilient Grids
  • Coupled Energy Infrastructures
  • Energy Markets and Regulation
  • Power Electronics and Devices

Further details can be found under  Research.

Advanced mathematical methods for energy systems
Our main focus of research is advanced mathematical methods for energy systems, involving Janusz Bialek, Misha ChertkovYury Maximov  and Anatoly Dymarski, and taking advantage of the abundance of excellent Russian mathematicians, statisticians and physicists at Skoltech and abroad. In this research w collaborate closely with our international partners: MIT (Kostya Turitsyn) and Caltech (Steven Low). We have organized an international conference in Moscow in June 2015 that attracted top scientists from MIT, Caltech, Michigan University, Cambridge University, University College London, Manchester University, Hong Kong University, ETH Zurich, Southampton University, Trapeznikov Institute of Control Sciences of RAS, Steklov Mathematical Institute of RAS, and Energy Systems Institute SB of RAS. We intend to organize an international conference in 2017 on data-driven analytics for energy systems.

Currently our research in this theme concentrates on the following areas:

  • Analysis of Power Flow equations (Power Flow equations define real algebraic variety) – (Turitsyn, Dymarski, Maximov, Chertkov)
  • Convex optimization with applications to power systems (Optimal Power Flow problems, calculation of safety margins, probabilistic approach) – (Turitsyn, Dymarski, Maximov, Chertkov)
  • Lyapunov stability analysis (Lyapunov functions constructed via convex optimization) – (Turitsyn)
  • Estimation and identification:
    • Utilizing synchronizing phasor measurements to identify power system dynamic model (Bialek, Turitsyn, Dymarski)
    • Data-driven machine learning approaches to provide statistical state estimation (Chertkov)
  • Stochastic Optimal Power Flow  of chance-constrained and robust types accounting for frequency control (Chertkov)
  • Optimal decentralized control: frequency control and congestion management for future power systems (Bialek, Low)
  • Scalable algorithms and advanced visualization for operations-aware planning of large (country scale) future transmission power systems (Chertkov, Bialek)

Smart Grids (Bialek, Chertkov, Dymarsky, Maximov, Gryazina, Ouerdane, Pozo)

The objective of this thrust, which is the main area of application of advanced mathematical methods to energy systems (our USP), is the development of new advanced energy system models, optimization algorithms and software to enable optimal operation and planning of energy systems. This will enable better decision-making thus enhancing economic efficiency, reliability and flexibility of energy systems. The main specific research directions include:

  • Optimization problems in energy sector. This includes short-term optimization (e.g. optimal power flow and unit commitment) and long-term optimization (infrastructure planning). One specific example is the theory of convex relaxations for optimization problems in the energy sector
  • Development of novel data-driven (machine learning, statistical) approaches to energy system analysis. This takes advantage of modern sensor technologies (e.g. phasor measurement units)
  • Probabilistic approaches to energy systems including decision making under multi-scale uncertainties
  • Transient stability assessment for secure operation of Special Protection Systems
  • Modeling and controlling energy resources at the distribution level (demand response)
  • Novel frequency control for future power systems

Research in that area is by its nature fundamental and interdisciplinary combining maths (Elena Gryazina, Yury Maximov), physics (Michael Chertkov, Anatoly Dymarsky, Henni Ouerdane) and engineering (Janusz Bialek). We also collaborate closely in that area with MIT (Kostya Turitsyn) and Caltech (Steven Low).

Integrated Energy Infrastructures (Chertkov, Bischi, Bialek, Ouerdane)

Integrated energy modelling is perhaps the hottest topic internationally in energy research. Our research aim is to look at energy conversion systems from the point of view of both advanced technological solutions and processes and their integration into wider picture in order to provide techno-economic assessments. We analyze energy systems and networks in all their forms and shapes: from heat engines to large power plants, including energy storage processes, through micro-systems based on nanomaterials and biological systems. Specific research directions include:

  • Interdependency of modern energy systems (power, gas, heat, cooling)
  • Model-based vs model-free approaches for indoor climate control
  • Modeling and control of heat and mass flows in district heating systems
  • Modeling, optimization and planning of natural gas systems
  • Combined Cooling, Heating and Power (CCHP, trigeneration)
  • Energy storage: Vanadium Red-Ox flow batteries, Compressed Air Energy Storage (CAES) and Liquid Air Energy Storage (LAES) systems
  • Modeling of electrical conductivity of aqueous solutions
  • Hybrid geothermal-biomass power plants and Organic Rankine Cycle (ORC) plants
  • Two-phase fluid machines (expanders, compressors)

 Energy Markets and Regulation (Pozo, Bialek, Gryazina)

Activities in that area have started in earnest only after appointing Dr. David Pozo in 2017, one of the most promising international research stars in the area.  We aim at establishing Skoltech as a leading center in Russia, and one of the internationally-recognized centers, for providing advanced mathematical tools, policy and regulation analysis, and pricing mechanism solutions. We will also provide recommendations and roadmaps for institutional reforms and business models adapted to the reality of a specific energy system (especially Russia).

The research in this area is interdisciplinary and highly mathematical combining operation research (David Pozo), optimization (Elena Gryazina) and power system engineering (David Pozo, Janusz Bialek). The main specific research directions include:

  • Impact of smart grids on system economics and security
  • Operation and planning strategies based on game theory analysis.
  • Market mechanisms for integrated energy systems
  • Policies and regulation analysis
  • Power Supergrid (Energy Ring) in North-East Asia

Power Electronics and Devices (Ibanez, Bialek, Titov)

CES activities in this area include two labs: Smart Grids lab (run by Professor F. Ibanez) and Thermal lab (run by Dr. Titov).

Smart Grids lab

Our Smart Grids/Microgrids laboratory is, to our knowledge,  a unique laboratory in Russia offering facilities to test novel control technologies in hardware. We aim to take advantage of the lab to establish Skoltech as a leader in Russia in developing and testing in real hardware new strategies for controlling microgrids. We plan to use the Smart Grids lab to do research on integration of renewables (wind, solar, batteries) onto smart grid, and power electronics, particularly on multilevel and resonant converters at voltages up to 8kV.

Our main goal is the development of power converters for microgrid applications. These include traditional, multi level and resonant converters. For this purpose, the lab has enough equipment for developing unique converters, this includes a fast  milling machine for developing PCBs, 10W DC power supplies and instrument for measuring. In addition, the lab equipment will be expanded to the high voltage area, by adding new  equipment such as high voltage probes and high voltage power supplies, network analyzer and spectrum analyzer. In addition, energy storage devices are being purchased to test the power electronic circuits this includes supercapacitors and batteries.

Furthermore, a real-time simulator (OPAL RT) has been purchased and it is currently being used by the PhD and MSc students for testing different block of a power converter and it also will be used for testing strategies of sharing power in complex networks such as hierarchical droop control and  master slave control for inverters in renewable energy applications.

Teaching in this area includes a course Power Electronics developed from scratch and run for the first time by Ibanzez in Fall 2017.  50% of the course was hands-on and  delivered in the lab where students developed their own power electronic converters. Similarly 50% of the course Smart Grid will be delivered using our installations. The lab is also use for short term research, currently the MSc are developing programmable DC loads (for cycling batteries) and testing algorithms for power converters.

Thermal lab

There are two main industry-funded projects in this area: insulation diagnostics for 10-500 kV transmission lines and monitoring of ice formation on overhead transmission lines. The novelty of the former lies in developing a mathematical model for estimating the probability of overlapping insulation, taking into account the type and age of the insulator, the degree and irregularity of contamination of the insulator surface, the leakage current, the discharge voltage, the intensity of partial and corona discharges, and meteorological data. A method for diagnosing any type of insulator based on an estimation of the current flowing through the insulating suspension, as well as interpretation of the ultraviolet monitoring data, has been developed. The application of the research results will allow to increase the coverage of instrumentally diagnosed insulators during planned inspections organizationally by one team of 4 cadets from 1,050 km to 2,350 km per year; to reduce the probability of overlapping insulation while maintaining volumes of replacement and cleaning insulation; to reduce the search time of the damaged polymer insulator by 50-70%. The project is worth 17 million rubles and is being implemented jointly with FGC, IDGC of Urals and IDGC of the South.

Monitoring of ice formation on overhead power lines aims to develop a new method of monitoring and short-term forecasting of ice formation on the wire. In calculating the intensity of ice formation, the temperature of the wire, the measured meteorological parameters and the prognostic meteorological data, the electric field strength of the wire, and the tension of the insulating suspension are taken into account. Application of research results will allow to minimize the cost of monitoring ice conditions in the network area, the cost of carrying out anti-ice measures, and also to justify investing in the use of types of wires with anti-ice properties. The research is a continuation of the MIG project, which attracted 4.7 million rubles, entered the register of PJSC “Rosseti”, successfully passed the IPE in IDGC of the South. In 2017, the project attracted an additional 4.8 million rubles.

Drivers for Energy Systems Research

Power systems around the world are undergoing a period of unprecedented change. A typical 20th Century power system was characterized by unidirectional flow of power from a limited number of large controllable power stations to a highly predictable demand. There was no no energy storage (apart from very expensive pumped-storage hydro  plants) so that at any time generation had to be equal to demand and the infrastructure utilization rates were low (about 55% for generation, 30% for transmission and even lower for distribution). Generally planning and controlling such a system was relatively straightforward as it was based around principles of deterministic hierarchical control, usually based on (N-1) reliability criterion.

20th Century power systemOn the other hand the emerging 21st Century power system is characterized by bi-directional flows between a very large number of uncontrollable and stochastic generators (usually, but not always, renewable ones such as wind or solar) and stochastic and often poorly-predictable demand. Demand ceases to be predictable as it consists of consumers equipped with smart meters and wind/solar generators hence possibly becoming net generators – so-called prosumers. Increased penetration of energy storage, both stationary and mobile due to a take-up of electric vehicles,  offers  buffering possibilities in dispatch (generation does not have to be equal to demand at any time). Controlling such a power system is the main research challenge in power systems and it is made possible by latest advances in ICT (Information and Control Technology), communication networks, Internet, GPS, sensors, etc. However it requires new tools and methodologies, developing of which is the main goal of Skoltech Center for Energy Systems.

Our research is not limited to power systems but rather it is aimed on energy systems due to close interactions between power, gas and heat networks (especially in Russia because of wide utilization of district heating).

21st Century power system1

Developing these new control tools and methodologies requires an interdisciplinary effort of scientists from many disciplines:

  • Mathematicians, statisticians and computer scientists to address the challenges of stochastic and distributed control
  • Physicists as power systems are large-scale dynamic objects
  • Economists as any solutions may require regulatory changes and will have to be accommodated in the markets framework
  • Social scientists in order to understand customers
  • Political scientists to ensure the support of stakeholders for the changes
  • And last but not least, power engineers who understand the physical power system (and will have to keep the feet of other scientists firmly on the ground)


Russian energy system