Multi-timescale framework for the voltage control of active distribution grids

De Din, Edoardo; Monti, Antonello (Thesis advisor); Ulbig, Andreas (Thesis advisor)

1. Auflage. - Aachen : E.ON Energy Research Center, RWTH Aachen University (2023)
Book, Dissertation / PhD Thesis

In: E.On Energy Research Center : ACS, Automation of complex power systems 117
Page(s)/Article-Nr.: 1 Online-Ressource : Illustrationen, Diagramme

Dissertation, RWTH Aachen University, 2023


Motivation, Goal and Task of the Dissertation: Electric distribution grids are facing significant grid management challenges due to the increasing installation of Distributed Generator (DG)s and Energy Storage System (ESS)s. As compared to the past, Low Voltage (LV) and Medium Voltage (MV) grids are becoming active distribution grids, requiring advanced solutions to manage the resources installed in the grid while respecting the standards. One of the possible effects produced by this transformation are voltage fluctuations, which can occasionally lead to exceeding the undervoltage or overvoltage limits. For this reason, control algorithms that are able to manage the installed resources in a smart and less invasive way represent an innovative approach to operate active distribution grids. A particular aspect of the voltage control algorithms is that they can have different objectives depending on the timescale and on the structure of the control. This dissertation aims at presenting a possible framework to combine control algorithms with different timescales, showing the beneficial contribution of such control framework. Moreover, distributed algorithms have been recently proven to be a better option for the implementation of the voltage control algorithms that work in a closed-loop with the measurements (defined as online or feedback controls). Therefore, distributed formulation of the online control layers of the framework has been carried out. The work aims satisfying the following requirements: 1. Interconnection of voltage control with different timescales: The proposed framework is used to interface voltage control algorithms with different timescales. 2. Distributed and flexible: The controls with a feedback approach are formulated in a distributed and flexible configuration. 3. Modular and scalable: The modularity is guaranteed by a full distributed implementation of the controls. Scalability for the proposed distributed algorithms has been also analyzed. Major Scientific Contributions: The three requirements defined above have been fulfilled considering three steps, which also define the major scientific contribution of the dissertation. The first step addresses the first requirement, defining the proposed multi-timescale framework in its centralized formulation. In the framework, three different control levels have been defined: the scheduling, an offline control to perform a day-ahead scheduling of the ESSs; the Model Predictive Control (MPC) to track the references produced by the scheduling within a prediction horizon while compensating for any mismatch; the online voltage control that takes action if a rapid voltage variation occurs between two MPC iterations. The scheduler uses the day-ahead forecast information to calculate an operation plan for the ESSs to target the State of Charge (SoC) objective while maintaining the voltage within the limits. The MPC is used as an intermediate layer to track the operation plan for the ESSs and compensate for the errors of the forecast using real measurements from the field in a closed loop. The final stage of the framework prevents sudden voltage violations by modifying the control set-points calculated by the MPC.The second step considers the implementation of a full distributed algorithm to solve the MPC. The procedure is based on the reformulation of the original problem in a constraint-coupled setup and on the adoption of a recently presented algorithm to distribute such optimization setup. Condition limits for the convergence of the proposed distributed MPC have been proposed and proven by simulation tests. Additional simulations tests have been carried out to analyze the scalability of the proposed control.This second step address the both the second and third requirements for the MPC.In the third step, second and third requirements are addressed for the online voltage control. This step considers the implementation of the distributed formulation of the lower layer of the framework, which features the smaller timescale. The formulation, which extend a recently presented algorithm, is obtained by applying the duality theory and by exploiting the sparse structure of the control matrix. The test of the algorithm has been performed by implementing it with containers, which allow a more versatile implementation of the control while reducing the customizationrequired for hardware implementation. Tests with simulated grid are performed to demonstrate the characteristics of the control strategy and its scalability.


  • E.ON Energy Research Center [080052]
  • Institute for Automation of Complex Power Systems [616310]