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

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.

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

Konstantina Christakou, Xiang Gao, Mario Paolone, Fabrizio Sossan

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.

IEEE2017

Optimal Allocation of Dispersed Energy Storage Systems in Active Distribution Networks for Energy Balance and Grid Support

Mostafa Nick, Mario Paolone

Dispersed storage systems (DSSs) can represent an important near-term solution for supporting the operation and control of active distribution networks (ADNs). Indeed, they have the capability to support ADNs by providing ancillary services in addition to energy balance capabilities. Within this context, this paper focuses on the optimal allocation of DSSs in ADNs by defining a multi-objective optimization problem aiming at finding the optimal trade-off between technical and economical goals. In particular, the proposed procedure accounts for: 1) network voltage deviations; 2) feeders/lines congestions; 3) network losses; 4) cost of supplying loads (from external grid or local producers) together with the cost of DSS investment/maintenance; 5) load curtailment; and 6) stochasticity of loads and renewables productions. The DSSs are suitably modeled to consider their ability to support the network by both active and reactive powers. A convex formulation of ac optimal power flow problem is used to define a mixed integer second-order cone programming problem to optimally site and size the DSSs in the network. A test case referring to IEEE 34 bus distribution test feeder is used to demonstrate and discuss the effectiveness of the proposed methodology.

Institute of Electrical and Electronics Engineers2014

Primary Voltage Control in Active Distribution Networks via Broadcast Signals: The Case of Distributed Storage

Maryam Bahramipanah, Konstantina Christakou, Jean-Yves Le Boudec, Mario Paolone, Dan-Cristian Tomozei

In this paper, we consider an active distribution network (ADN) that performs primary voltage control using real-time demand response via a broadcast low-rate communication signal. The ADN also owns distributed electrical energy storage. We show that it is possible to use the same broadcast signal deployed for controlling loads to manage the distributed storage. To this end, we propose an appropriate control law to be embedded into the distributed electrical storage controllers that reacts to the defined broadcast signal in order to control both active and reactive power injections. We analyze, in particular, the case where electrical storage systems consist of supercapacitor arrays and where the ADN uses the grid explicit congestion notification (GECN) for real-time demand response that the authors have developed in a previous contribution. We estimate the energy reserve required for successfully performing voltage control depending on the characteristics of the network. The performance of the scheme is numerically evaluated on the IEEE 34-node test feeder. We further evaluate the effect, depending on the line characteristics, of reactive versus active power controlled injections. We find that without altering the demand-response signal, a suitably designed controller implemented in the storage devices enables them to successfully contribute to primary voltage control.

Ieee-Inst Electrical Electronics Engineers Inc2014