|Title||Webinar : NREL Smart Grid Educational Series webinar on Real-time optimization of distribution grids for increased flexibility and resilience|
|Start Time||2017-10-06 21:30 (IST)|
|End Time||2017-10-06 23:00 (IST)|
Abstract: The deployment of distributed energy resources (DERs) – including renewable-based sources of energy, controllable loads, energy storage systems, and electric vehicles – is increasing the complexity of distribution grids to a point where existing techniques to control and optimize the system operation will be inadequate. In particular, existing control and optimization techniques will rapidly become impractical because of (at least some of) the following challenges: (c1) Computational complexity, which prevents decision-making capabilities that are consistent with the form and function of future distribution systems, which will be governed by faster dynamics; (c2) They are based on rule-based approaches, which lack of stability guarantees; (c3) Sensitivity to model inaccuracy; (c4) Need for pervasive monitoring, and (c5) centralized implementation. For the latter, since the majority of the control and optimization actions are taken by centralized computing platforms (e.g., ADMS, EMS, DERMS), restricting the decision making process to single location increases the vulnerability of power grids to cyber-attacks and contingencies.
To address these challenges, this talk presents a system-theoretic optimization strategy that enables DERs to achieve coordination in real time, to systematically ensure that electrical quantities are within given security limits throughout the whole grid while maximizing well-defined performance objectives of customers, aggregators, and utilities. Additionally, the algorithm is designed to enable the active power at the point of coupling to track given set points (e.g., dispatch, ramp, or AGC signals), so that the feeder, in aggregate, can provide services to the rest of the grid. The closed-loop optimization algorithm is provably stable, can cope with inaccuracies in the representation of the system physics, and avoid pervasive metering to gather the state of non-controllable resources. A distributed implementation eliminates single points of failure (e.g., centralized computing platforms that solve optimization problems for the whole system), thus improving resiliency to attacks and contingencies.
The presentation will also introduce the concept of Autonomous Energy Grids (AEGs) – a new initiative of NREL – and will show how the presented algorithm can be applied to AEGs to significantly increase resilience, security, and efficiency of power grids.
Speaker Bio: Emiliano Dall'Anese received the Laurea Triennale (B.Sc. Degree) and the Laurea Specialistica (M.Sc. Degree) in Telecommunications Engineering from the University of Padova, Italy, in 2005 and 2007, respectively, and the Ph.D. in Information Engineering from the Department of Information Engineering, University of Padova, Italy, in 2011. From January 2009 to September 2010, he was a visiting scholar at the Department of Electrical and Computer Engineering, University of Minnesota, USA. From January 2011 to November 2014 he was a Postdoctoral Associate at the Department of Electrical and Computer Engineering and Digital Technology Center of the University of Minnesota, within the group of Prof. Georgios Giannakis. Since December 2014 he has been a Senior Engineer at the National Renewable Energy Laboratory. His research interests lie in the areas of optimization and signal processing, with applications for power systems and communications. Current efforts focus on distributed optimization and control of power distribution systems with distributed (renewable) energy resources, and statistical inference for grid data analytics.URL : Please click here for Details
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