PhD thesis defense to be held on November 14, 2022, at 10:30 (Virtually in MS Teams)

Picture Credit: Vasileios Evangelopoulos

Thesis title: Optimization of active electrical distribution network management with heterogeneous sources of flexibility

Abstract: The ever-increasing presence of distributed energy resources (DER) in the electric grid, in the form of distributed generation, energy storage and flexible loads, poses significant challenges to the distribution system operator (DSO). Nonetheless, DER can contribute to the flexible management of the operation of the distribution system. This PhD thesis focuses on optimizing the management of active distribution networks (DNs) by utilizing heterogeneous sources of flexibility, i.e., flexibility that is sourced by DER of different technologies with different technical characteristics.
Firstly, the impact of the ever-increasing penetration of DER in the distribution networks is analyzed, as well as their benefits as sources of flexibility for the effective management of active DNs are highlighted. Furthermore, a comprehensive literature review is presented for the methods and models that optimize the management of active DNs, both in the stage of operational planning and in the stage of real-time dispatch. Consequently, the research focuses on the development of innovative optimization methods that cover, financially and technically, the above-mentioned stages for the management of active DNs.
The problem of operational planning of active DNs is solved with a novel two-stage stochastic programming model that takes into consideration weighted forecasting scenarios of the electric load and the variable production of renewable energy sources (RES). The operational schedule determines a) the schedule of active power flows in the interconnection of the DN with the transmission system, and b) the required amounts of DER flexibility that is committed for the stage of real-time dispatch.
Then, the problem of real-time dispatch of the available DER flexibility is solved with a novel methodology that is based on the principles of model predictive control to reduce the deviations from the dispatch schedule and to minimize the operational costs of the DN. In addition, the response time of DER flexibility to the dispatch orders (set-points) that are sent by the DSO is taken into account.
Finally, the financial management of active DNs is modeled within a bi-level programming framework that is based on the Stackelberg model with one leader and multiple followers, and is solved as a problem of mathematical program with equilibrium constraints. The DSO (leader) organizes a local flexibility market, in which aggregators of flexible loads, RES and energy storage systems participate as providers of flexibility services (followers).

Supervisor: Associate Professor Pavlos Georgilakis

PhD Student: Vasileios Evangelopoulos