Enhancing the Provision of Ancillary Services from Storage Systems using Smart Transformer and Smart Meters

The Smart Transformer, a solid-state transformer with control and communication functionalities, can be the ideal solution for integrating storage into the grid. By leveraging the knowledge of the grid state of distribution grids thanks to smart meters and/or dedicated remote terminal units, in the paper, it is proposed a control strategy for a MV/LV smart transformer (ST) with integrated storage to achieve: i) dispatched-by-design operation of the LV network by controlling the ST active power set-point on the MV power converter, and ii) voltage regulation of both MV and LV networks by controlling the reactive power injections of both LV and MV converter. The former is achieved by dispatching the active power flow of the LV network according to a profile established the day before the operation, called \emph{dispatch plan}, with the objective of reducing the amount of regulating power required to operate the grid. It is based on the use of forecast to compute a dispatch plan, and a tracking problem to compensate in real-time the mismatch between realization and dispatch plan by taking advantage of the storage capacity. The latter is achieved by using sensitivity coefficients, which are calculated from the state of the grid and integrating the information on the network topology. The problem formulation is given in the paper, and the proof-of-concept is shown by simulation using the IEEE 34 nodes test feeder and the CIGRE Low Voltage reference network.

Concurrent Voltage Control and Dispatch of Active Distribution Networks by means of Smart Transformer and Storage

Konstantina Christakou, Xiang Gao, Mario Paolone, Fabrizio Sossan

Dispatching active distribution networks is expected to play an important role in the smart grid technologies. Voltage control is also starting to be widely proposed to avoid voltage violations in the electrical grid. The integration of the storage in the so called smart transformer (ST), which is a solid state transformer with control and communication functionalities, can help combine both the services. The added value of such a configuration is that it allows the full decoupling of the reactive power flows between the medium voltage (MV) and low voltage (LV) networks. We show the augmented flexibility of such a configuration by proposing a control strategy where, i, the storage system is used to achieve dispatched-by-design operation of the LV network active power flow, and, ii, the two ST power converters to control the voltage in both the MV and LV grid on a best effort basis. The control strategy is validated by simulations using the IEEE 34-node MV test feeder and the Cigre LV reference network. Moreover, control performance is benchmarked against a conventional network setup, where the BESS is connected to the LV network through a DC/AC power converter and the ST transformer is replaced by a conventional transformer.

2018

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

Real-Time Optimal Controls for Active Distribution Networks

Konstantina Christakou

Decentralized generation, distributed energy storage systems and active participation of end-users in the lower level of the electrical infrastructure, intelligently managed to provide grid support, define the notion of Active Distribution Networks (ADNs). The presence of distributed generation in ADNs incurs severe impacts on planning and operational procedures and calls for intelligent control techniques. This thesis focuses on the compelling problem of optimal operation and control of ADNs, with particular reference to the design of real-time voltage control and lines congestion management algorithms. In the first part of the thesis, we adopt a centralized architecture for voltage control and lines congestion management in ADNs. The goal of the proposed controller is to schedule the active and reactive power injections of a set of controllable resources, in coordination with traditional resources, in order to achieve an optimal grid operation. The controller relies on a linearized approach that links control variables and controlled quantities using sensitivity coefficients. Once the proposed algorithm is validated, as a further step, we relax the assumption that the DNO has an accurate knowledge of the system model, i.e., a correct admittance matrix and we adapt the proposed control architecture to such a scenario. When the controllable resources are heterogeneous and numerous, control schemes that rely on two-way communication between the controllable entity and the DNO cannot scale in the number of network buses and controllable resources. In this direction, in the second part of this thesis, we propose the use of broadcast-based control schemes that rely on state estimation for the feedback channel. We propose a low-overhead broadcast-based control mechanism, called Grid Explicit Congestion Notification (GECN), intended for provision of grid ancillary services by a seamless control of large populations of distributed, heterogeneous energy resources. Two promising candidates in terms of controllable resources are energy storage systems and elastic loads. Therefore, we choose to validate GECN in the case of aggregations of thermostatically controlled loads, as well as of distributed electrochemical-based storage systems. In the last part of the thesis, we formulate the control problem of interest as a non-approximated AC optimal power flow problem (OPF). The AC-OPF problem is non-convex, thus difficult to solve efficiently. A recent approach that focuses on the branch-flow convexification of the problem is claimed to be exact for radial networks under specific assumptions. We show that this claim, does not hold, as it leads to an incorrect system model. Therefore, there is a need to develop algorithms for the solution of the non-approximated, inherently non-convex OPF problem. We propose an algorithm for the AC-OPF problem in radial networks that uses an augmented Lagrangian approach, relies on the method of multipliers and does not require convexity. We design a centralized algorithm that converges to a local minimum of the original problem. When controlling multiple dispersed energy resources, it is of interest to define also a distributed method. We investigate the alternating direction method of multipliers (ADMM) for the distributed solution of the OPF problem and we show cases for which it fails to converge. As a solution we present a distributed version of the proposed OPF algorithm that is based on a primal decomposition.

EPFL2015

Real-Time Optimal Controls for Active Distribution Networks

Konstantina Christakou

EPFL2015