An Information-Centric Communication Infrastructure for Real-Time State Estimation of Active Distribution Networks

The evolution toward emerging active distribution networks (ADNs) can be realized via a real-time state estimation (RTSE) application facilitated by the use of phasor measurement units (PMUs). A critical challenge in deploying PMU-based RTSE applications at large scale is the lack of a scalable and flexible communication infrastructure for the timely (i.e., sub-second) delivery of the high volume of synchronized and continuous synchrophasor measurements. We address this challenge by introducing a communication platform called C-DAX based on the information-centric networking (ICN) concept. With a topic-based publish-subscribe engine that decouples data producers and consumers in time and space, C-DAX enables efficient synchrophasor measurement delivery, as well as flexible and scalable (re)configuration of PMU data communication for seamless full observability of power conditions in complex and dynamic scenarios. Based on the derived set of requirements for supporting PMU-based RTSE in ADNs, we design the ICN-based C-DAX communication platform, together with a joint optimized physical network resource provisioning strategy, in order to enable the agile PMU data communications in near real-time. In this paper, C-DAX is validated via a field trial implementation deployed over a sample feeder in a real-distribution network; it is also evaluated through simulation-based experiments using a large set of real medium voltage grid topologies currently operating live in The Netherlands. This is the first work that applies emerging communication paradigms, such as ICN, to smart grids while maintaining the required hard real-time data delivery as demonstrated through field trials at national scale. As such, it aims to become a blueprint for the application of ICN-based general purpose communication platforms to ADNs.

Real-Time State Estimation of the EPFL-Campus Medium-Voltage Grid by Using PMUs

Sergio Barreto Andrade, German Dario Flores Ponce, Jean-Yves Le Boudec, Mario Paolone, Marco Pignati, Miroslav Popovic, Paolo Romano, Styliani Sarri, Teklemariam Tsegay Tesfay, Dan-Cristian Tomozei, Lorenzo Zanni

We describe the real-time monitoring infrastructure of the smart-grid pilot on the EPFL campus. We experimentally validate the concept of a real-time state-estimation for a 20 kV active distribution network. We designed and put into operation the whole infrastructure composed by the following main elements: (1) dedicated PMUs connected on the medium-voltage side of the network secondary substations by means of specific current/voltage transducers; (2) a dedicated communication network engineered to support stringent time limits and (3) an innovative state estimation process for real-time monitoring that incorporates phasor-data concentration and state estimation processes. Special care was taken to make the whole chain resilient to cyber-attacks, equipment failures and power outages. The achieved latency is within 65ms. The refresh rate of the estimated state is 20ms. The real-time visualization of the state estimator output is made publicly available, as well as the historical data (PMU measurements and estimated states). To the best of our knowledge, the work presented here is the first operational system that provides low-latency real-time state estimation by using PMU measurements of a real active distribution network.

2015

Static and recursive PMU-based state estimation processes for transmission and distribution power grids

Jean-Yves Le Boudec, Mario Paolone, Styliani Sarri, Lorenzo Zanni

In the operation of power systems, the knowledge of the system state is required by several fundamental functions, such as security assessment, voltage control and stability analysis. By making reference to the static state of the system represented by the voltage phasors at all the network buses, it is possible to infer the system operating conditions. Until the late 1970s, conventional load flow calculations provided the system state by directly using the raw measurements of voltage magnitudes and power injections. The loss of one measurement made the calculation impossible and the presence of measurement errors affected dramatically the computed state.To overcome these limitations, load flowtheory has been combined with statistical estimation constituting the so-called state estimation (SE). The latter consists in the solution of an optimization problem that processes the measurements together with the network model to determine the optimal estimate of the system state. The outputs of load flow and SE are composed of the same quantities, typically the voltage magnitude and phase at all the network buses, but SE uses all the types of measurements (e.g., voltage and current magnitudes, nodal power injections and flows, synchrophasors) and evaluates their consistency using the network model. The measurement redundancy is key to tolerate measurement losses, identify measurement and network parameter errors, and filter out the measurement noise. The foregoing properties of SE allow the system operator to obtain an accurate and reliable estimate of the system state that consequently improves the performance of the functions relying on it. Traditionally, SE has been performed at a relatively low refresh rate of a few minutes, dictated by the time requirements of the related functions together with the low measurement acquisition rate of remote terminal units (RTUs). Nowadays, the emerging availability of phasor measurement units (PMUs) allows to acquire accurate and time-aligned phasors, called synchrophasors, with typical streaming rates in the order of some tens of measurements per second. This technology is experiencing a fast evolution, which is triggered by an increasing number of power system applications that can benefit from the use of synchrophasors. SE processes can exploit the availability of synchrophasor measurements to achieve better accuracy performance and higher refresh rate (sub-second). PMUs already compose the backbone of wide area monitoring systems in the context of transmission networks to which several real-time functionalities are connected, such as inter-area oscillations, relaying, fault location and real-time SE. However, PMUs might represent fundamental monitoring tools even in the context of distribution networks for applications such as: SE [5, 6], loss of main [7], fault event monitoring, synchronous islanded operation [9] and power quality monitoring. The recent literature has discussed the use of PMUs for SE in distribution networks both from the methodological point of view and also via dedicated real-scale experimental setups. Since the pioneering works of Schweppe on power system SE in 1970, most of the research on the subject has investigated static SE methods based on weighted least squares (WLS). Static SE computes the system state performing a “best fit” of the measurements belonging only to the current time-step. Another category of state estimators are the recursive methods, such as the Kalman filter (KF). In addition to the use of the measurements and their statistical properties, they also predict the system state by modelling its time evolution. In general, recursive estimators are characterized by higher complexity and the prediction introduces an additional source of uncertainty that, if not properly quantified, might worsen the accuracy of the estimated state. Besides, their ability to filter out measurement noise could not be exploited due to the low SE refresh rate: even in quasi-steady state conditions, the measurement noise was smaller than the state variations between two consecutive time-steps. However, the effectiveness of power system SE based on KF has been recently reconsidered thanks to the possibility to largely increase the SE refresh rate by using synchrophasor measurements. The chapter starts by providing the measurement and process model of WLS and KF SE algorithms and continues with the analytical formulation of the two families of state estimators, including their linear and non-linear versions as a function of the type of available measurements. Finally, two case studies targeting IEEE transmission and distribution reference networks are given.

The Institution of Engineering and Technology - IET2015

Real-Time Control Framework for Active Distribution Networks Theoretical Definition and Experimental Validation

Lorenzo Enrique Reyes Chamorro

The great challenge of massively integrating the volatile distributed power-generation into the power system is strongly related to the evolution of their operation and control. The literature of the last decade has suggested two models for such an evolution: (i) the supergrid model, based on enhanced continental/intercontinental network interconnections (mainly DC) for bulk transmission, (ii) the microgrid mode, where small medium/low voltage networks interfacing heterogeneous resources, such as local generation, energy storage and active customers, are intelligently managed so that they are operated as independent cells capable of providing different services from each other and operate in islanded mode. Irrespective of the model that will eventually emerge, the control of heterogeneous distributed resources represents a fundamental challenge for both supergrid and microgrid models. This requires the definition of scalable and composable control methods that guarantee the optimal and feasible operation of distribution grids in order to satisfy local objectives (e.g., distribution grid power balance), as well as the provision of ancillary services to the external bulk transmission (e.g., primary and secondary frequency supports). Several control methodologies have been proposed to achieve these goals, and the majority of them have been inspired by the classic time-layered approach traditionally adopted in power systems that are associated with different time-scales and extension of the controlling area, i.e. primary, secondary and tertiary controls, ranging from sub-seconds to hours, respectively. In the context of microgrids, these three levels of control can be associated with a decision process that can be centralized (i.e., a dedicated central controller decides on the operation of the system resources) and/or decentralized (each element decides based on its own rules). In the current literature, the former is used for long-term, whereas the latter for short-term decisions. In particular, primary controls are typically deployed through fully decentralized schemes mainly relying on the use of droop control. With this in mind, in this thesis we propose, and experimentally validate, a novel control framework called COMMELEC â A Composable Framework for Real-Time Control of Active Distribution Networks, Using Explicit Power Set-Points. It controls a power grid in real-time based on a multi-agent structure, using a simple and low-bandwidth communication protocol. Such a framework enables a controller to easily steer an entire network as an equivalent energy resource, thus making an entire system able to provide grid support by exploiting the flexibility of its components in real-time. The main features of the framework are (i) that it is able to indirectly control the reserve of the storage systems, thus maximizing the autonomy of the islanding operation, (ii) that it keeps the system in feasible operation conditions and better explores, compared to traditional techniques, the various degrees of freedom that characterize the system, and (iii) that it maintains the system power-equilibrium without using the frequency as a global variable, even being able to do so in inertia-less systems. Our framework has been extensively validated, first by simulations but, more importantly, in a real-scale microgrid laboratory specially designed and setup for this goal. This is the first real-scale experiment that proves the applicability of a droop-less explicit power-flow control mechanism in microgrids.