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Personne# Sherif Alaa Salaheldin Fahmy

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The increasing penetration of stochastic renewable distributed generation, energy storage systems and novel loads (e.g. electric-vehicles (EVs)) in active-distribution-networks (ADNs) or microgrids has triggered the need to develop real-time (e.g. minutes to sub-second) control frameworks to avoid grid-operational problems. These can be split into two main categories of active constraints: static and power-quality. Static constraints refer to branches' ampacity limitations, nodal voltage magnitudes' security-bounds as well as resources' limitations (e.g. MV-LV substation transformer apparent power limitations, power converters' capability curves and general constraints of the internal states of energy storage systems). Power-quality constraints refer to the quality-of-service for the end-users that must be guaranteed by the power distribution utility. Within this context, this thesis focuses on the development of real-time ADN controls, in the form of frameworks or control-enabling methodologies, that take into account the above-mentioned power-grid operational constraints while considering grid uncertainties and unbalances. In its first part, the thesis focuses on a general, i.e. resource-agnostic, methodology to linearize the power-flow equations and showcases its real-time control-enabling advantages through two sub-second-scale control-application-examples. Then, in the second part, a deeper focus is given to the operational challenges raised by the large presence of electric-vehicles charging-stations in distribution grids.

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The problem of securely reconnecting active distribution networks (ADNs) - e.g. microgrids - to their upstream grids at the point of common coupling (PCC) has been extensively discussed by the existing literature. The latter is commonly referred to as resynchronization and has to be done with care in order to avoid large transient current flows resulting from differences of nodal voltage phasors at both sides of the PCC. The active resynchronization process can be split into two tasks: the PCC-control and the synchrocheck. The PCC-control refers to the process used to steer the PCC nodal voltage at the ADN's side (i.e. downstream) towards the PCC nodal voltage at the upstream-grid's side (i.e. upstream). The synchrocheck refers to the algorithm used to check the synchronization (i.e. phasor alignment within tolerances) of the upstream and downstream PCC nodal voltages. Methods for PCC-control and synchrocheck presented in the literature commonly ignore the ADN's operational constraints and rely on the assumption of a balanced system. In this respect, the contribution of this paper is twofold. First, an approximated optimal-power-flow is proposed to control ADNs' resources in order to rapidly steer their PCC downstream nodal voltages close to their non-controllable upstream counterparts. Second, an Interpolated-Discrete-Fourier-Transform (IpDFT)-based synchrocheck that verifies the alignment of all three-phases of both upstream and downstream nodal voltages at the PCC, is proposed. The algorithms associated to both contributions are experimentally validated on the CIGRE-low-voltage-benchmark-microgrid at the Distributed Electrical Systems Laboratory (DESL) at the ecole Polytechnique Federale de Lausanne (EPFL) where the results of the developed synchrocheck are further benchmarked against the Schneider Electric's Micom P143 grid relay.

Sherif Alaa Salaheldin Fahmy, Rahul Kumar Gupta, Mario Paolone

This work presents an optimization framework to aggregate the power and energy flexibilities in an interconnected power distribution systems. The aggregation framework is used to compute the day-ahead dispatch plans of multiple and interconnected distribution grids operating at different voltage levels. Specifically, the proposed framework optimizes the dispatch plan of an upstream medium voltage (MV) grid accounting for the flexibility offered by downstream low voltage (LV) grids and the knowledge of the uncertainties of the stochastic resources. The framework considers grid, i.e., operational limits on the nodal voltages, lines, and transformer capacity using a linearized grid model, and controllable resources’ constraints. The dispatching problem is formulated as a stochastic-optimization scheme considering uncertainty on stochastic power generation and demands and the voltage imposed by the upstream grid. The problem is solved by a distributed optimization method relying on the Alternating Direction Method of Multipliers (ADMM) that splits the main problem into an aggregator problem (solved at the MV-grid level) and several local problems (solved at the MV-connected-controllable-resources and LV-grid levels). The use of distributed optimization enables a decentralized dispatch computation where the centralized aggregator is agnostic about the parameters/models of the participating resources and downstream grids. The framework is validated for interconnected CIGRE medium- and low-voltage networks hosting heterogeneous stochastic and controllable resources.

2022