Benchmark Test of a Variable Speed Unit for Teaching Purposes

Variable speed pump-turbine units have become nowadays an interesting way to increase stability of electrical power networks due to their high level of operating flexibility. Different advantages offered by variable speed pump-turbine units for both pumping and generating modes can be pointed out by means of either reliable simulation models or benchmark test devices. This paper presents a benchmark test of 3.3 kVA of a variable speed unit for teaching purposes. The control strategies for the transformer section and for the machine section are described. Comparisons between simulated and test results performed on this low power system are presented for different cases of operation (SVC effect, reactive power compensation, flywheel effect).

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André Hodder, Basile Kawkabani, Sylvain Robert, Jean-Jacques Simond
2008
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https://infoscience.epfl.ch/record/128941?ln=fr

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Hardware-in-the-loop Validation of the Grid Explicit Congestion Notification Mechanism for Primary Voltage Control in Active Distribution Networks

Konstantina Christakou, Jean-Yves Le Boudec, Mario Paolone, Marco Pignati, Roman Rudnik, Styliani Sarri

The Grid Explicit Congestion Notification control mechanism (GECN) is a broadcast-based real-time demand- response mechanism designed for primary voltage control in Active Distribution Networks (ADNs) [1,2]. An extensive set of off-line simulations has indicated that GECN is a promising candidate for deployment in the real field. However, prior to the actual deployment of the control mechanism, it is crucial to validate its performance when controlling a real grid. For this purpose we design and develop a dedicated experimental Hardware-in-the-Loop (HIL) test platform for the real-time val- idation of GECN. The HIL architecture consists of a Real-Time Simulator (RTS) where a real distribution feeder is modeled, together with controllable loads and the associated measurement infrastructure composed by virtual PMUs. These virtual metering devices stream data, via Ethernet, to a local Phasor Data Con- centrator suitably coupled with a Discrete Kalman Filter State Estimator. The estimated network state is received by a GECN network controller. We close the control loop by transmitting the computed broadcast control signals back to the network buses in the RTS using a micro-controller. By using this experimental setup we are able to (i) assess the performance of the whole control process in terms of voltage optimality and time latencies in a realistic setting and (ii) implement the GECN controllers into dedicated equipment that with the proper ruggedization can be readily deployed in the real field.

Università degli Studi di Genova, Italy2016

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A unified control strategy for active distribution networks via demand response and distributed energy storage systems

Konstantina Christakou

As part of the transition to a future power grid, distribution systems are undergoing profound changes evolving into Active Distribution Networks (ADNs). The presence of dispersed generation, local storage systems and responsive loads in these systems incurs severe impacts on planning and operational procedures. This paper focuses on the compelling problem of optimal operation and control of ADNs, with particular reference to voltage regulation and lines congestion management. We identify the main challenges and opportunities related to ADNs control and we discuss recent advances in this area. Finally, we describe a broadcast-based unified control algorithm designed to provide ancillary services to the grid by a seamless control of heterogeneous energy resources such as distributed storage systems and demand-responsive loads. (C) 2016 The Author. Published by Elsevier Ltd.

Elsevier Science Bv2016

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The paper contributes to improving the computational performance of controls of distributed energy resources (DERs) in distribution grids for efficient real-time control and short-term scheduling. The considered setting is a distribution grid with heterogeneous DERs controlled with model predictive control (MPC) to track a dispatch plan at its grid connection point (GCP) subject to DERs’ and grid’s constraints. The MPC control is first expressed as a quadratic programming (using linearized grid models) and, then, solved with several state-of-the-art alternating direction optimization methods: AMA, ADMM, AADMM (ADMM with adaptive penalty parameter) and their accelerated variants: FAMA, FAADMM, and FAADMM with restart rule. Performance is tested in terms of computational performance, constraints satisfaction, and optimality against the centralized MPC. The case studies are the CIGRE and IEEE benchmark grid for low- and medium voltage systems hosting different numbers of controllable DERs.

IEEE2021

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