State-of-the-art of data collection, analytics, and future needs of transmission utilities worldwide to account for the continuous growth of sensing data

Nowadays, transmission system operators require higher degree of observability in real-time to gain situational awareness and improve the decision-making process to guarantee a safe and reliable operation. Digitalization of energy systems allows utilities to monitor the system dynamic performance in real-time at fast time scales. The use of such technologies has unlocked new opportunities to introduce new data driven algorithms for improving the stability assessment and control of the system. Motivated by these challenges, a group of experts have worked together to highlight and establish a baseline set of these common concerns, which can be used as motivation to propose innovative analytics and data-driven solutions. In this document, the results of a survey on 10 transmission system operators around the world are presented and it aims to understand the current practices of the participating companies, in terms of data acquisition, handling, storage, modelling and analytics. The overall objective of this document is to capture the actual needs from the interviewed utilities, thereby laying the groundwork for setting valid assumptions for the development of advanced algorithms in this field.

Ultra high-speed electronics for power system dynamic emulation

Laurent Fabre

Modern society is dependent on reliable electricity for security, health, communication, transportation, finance, computers and nearly all aspects of the contemporary life. Providing reliable electricity is a very complex challenge. It involves real-time metering, real-time assessment, control and coordination of hundreds of production centers. Power consumption is steadily increasing and the power system is always operating closer to its limits. Introduction to smart-grid provides more and more data to be collected for the operation center by means of smart-metering for a better knowledge of the system. Moreover, focus is put on decentralized and stochastic green energy sources, leading to a much more complex and less predictable power system. Guarantying security of supply with these new requirements involves further enhancement for faster power system simulators. Indeed, they can provide online security assessment for better real-time control. Time-domain simulations are probably the most demanding in term of computation power. Existing time-domain simulators are based on time-consuming algorithm and targets very precise results. An effective way to accelerate the computational speed of power system assessment simulators is to use analog or mixed-signal emulation. Instead computing numerical matrix calculations of the grid this technique is based on a quasi-instantaneous analog Kirchhoff solver. It provides an intrinsic parallel computer and simulation time is independent of the analyzed power system topology size. This work addresses the development of a new power system emulation approach based on mixed-signal dedicated electronics hardware. Mixed-signal or hybrid electronics uses the coexistence of both digital and analog implementation. The digital functions are intended to facilitate the model portability when analog functions are used for achieving parallelism and speed enhancement. This thesis covers theoretical principles to the realization of a first power system emulation-on-chip (PSEoC) by means of application specific integrated circuit (ASIC). Moreover, different hardware platform (HDP) have been designed, realized and tested for demonstrating the performances by measurement. Within the framework of this work, we restrict our developments to transient stability and cover applications such N-1 contingency analysis and Critical Clearing Time (CCT) analysis. The approach used is called the phasor emulation (PE) approach. It is based on a mathematical abstraction of the grid where the transmission lines are represented by multiple programmable resistive networks, connected in array with CMOS analog switches. Generators and loads model are then computed through current-techniques blocks, embedded processors or FPGAs. Four HDP are presented: - The first electronics implementation provides a quasi-full analog computer and illustrates the limitations in terms of accuracy of such implementation without calibration. - The second uses multiple embedded 32-bit processors with analog emulation of the grid. It illustrates a comparison in term of accuracy between standard electronic and ASIC implementations (0.35um 3.3V CMOS technology) for a 16 node reconfigurable power system topology. - The third uses multiple FPGA processing units with analog emulation of the grid. It covers applications such N-1 contingency analysis and Critical Clearing Time (CCT) analysis for a 96 nodes reconfigurable power system topology. - Finally, the forth is based on PSEoC and the design of a dedicated ASICs developed for time-domain power system emulation. Main enhancement of this development is the design and realization of hybrid R-A/D C-A/D converter in 0.35um 3.3V CMOS technology. The emulated phenomena are shown to be between 100 to 1000 time faster than the real-time phenomena proving the high-speed capabilities of mixed-signal emulation approach.

EPFL2013

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.

EPFL2016