Power Quality

Electrical power is becoming one of the most dominant factors in our society. Power generation, transmission, distribution and usage are undergoing signifi cant changes that will aff ect the electrical quality and performance needs of our 21st century industry. One major aspect of electrical power is its quality and stability – or so called Power Quality. The view on Power Quality did change over the past few years. It seems that Power Quality is becoming a more important term in the academic world dealing with electrical power, and it is becoming more visible in all areas of commerce and industry, because of the ever increasing industry automation using sensitive electrical equipment on one hand and due to the dramatic change of our global electrical infrastructure on the other. For the past century, grid stability was maintained with a limited amount of major generators that have a large amount of rotational inertia. And the rate of change of phase angle is slow. Unfortunately, this does not work anymore with renewable energy sources adding their share to the grid like wind turbines or PV modules. Although the basic idea to use renewable energies is great and will be our path into the next century, it comes with a curse for the power grid as power fl ow stability will suff er. It is not only the source side that is about to change. We have also seen signifi cant changes on the load side as well. Industry is using machines and electrical products such as AC drives or PLCs that are sensitive to the slightest change of power quality, and we at home use more and more electrical products with switching power supplies or starting to plug in our electric cars to charge batt eries. In addition, many of us have begun installing our own distributed generation systems on our rooft ops using the latest solar panels. So we did look for a way to address this severe impact on our distribution network. To match supply and demand, we are about to create a new, intelligent and self-healing electric power infrastructure. The Smart Grid. The basic idea is to maintain the necessary balance between generators and loads on a grid. In other words, to make sure we have a good grid balance at all times. But the key question that you should ask yourself is: Does it also improve Power Quality? Probably not! Further on, the way how Power Quality is measured is going to be changed. Traditionally, each country had its own Power Quality standards and defi ned its own power quality instrument requirements. But more and more international harmonization efforts can be seen. Such as IEC 61000-4-30, which is an excellent standard that ensures that all compliant power quality instruments, regardless of manufacturer, will produce of measurement instruments so that they can also be used in volume applications and even directly embedded into sensitive loads. But work still has to be done. We still use Power Quality standards that have been writt en decades ago and don’t match today’s technology any more, such as fl icker standards that use parameters that have been defi ned by the behavior of 60-watt incandescent light bulbs, which are becoming extinct. Almost all experts are in agreement - although we will see an improvement in metering and control of the power fl ow, Power Quality will suff er. This book will give an overview of how power quality might impact our lives today and tomorrow, introduce new ways to monitor power quality and inform us about interesting possibilities to mitigate power quality problems. Regardless of any enhancements of the power grid, “Power Quality is just compatibility” like my good old friend and teacher Alex McEachern used to say. Power Quality will always remain an economic compromise between supply and load. The power available on the grid must be suffi ciently clean for the loads to operate correctly, and the loads must be suffi ciently strong to tolerate normal disturbances on the grid

Power quality studies in distribution systems involving spectral decomposition

Im Rahmen der Arbeit wurde eine Methode der Spannungsqualitätsanalyse vorgestellt, die zur Untersuchung von Oberschwingungen und Zwischenharmonischen in Verteilungsnetzen besonders geeignet ist. Der zunehmende Einsatz von elektronisch gesteuerten Geräten führt zur Beeinträchtigung der Energiequalität in elektrischen Netzen. Die resultierende Spannungs- und Stromverzerrung kann für empfindliche Einrichtungen gefährlich sein, besonders dann, wenn der Oberschwingungspegel nahe an den Störfestigkeitspegeln der angeschlossenen Betriebsmittel liegt oder diese überschreitet. Die in der Arbeit vorgestellte Methode findet die bezüglich Oberschwingungen und Zwischenharmonischen gefährdetsten Stellen in einem Verteilungssystem heraus. Somit wird eine Vorab-Analyse zur Ergreifung der notwendigen Maßnahmen ermöglicht. Zunächst wurde das Thema Spannungsqualität und ihr Zusammenhang mit der elektromagnetischen Verträglichkeit aus Sicht der Normen und Vorschriften erläutert. Darauf aufbauend wurde eine grundlegende Klassifikation der Spannungsqualitätsereignisse vorgestellt und analysiert. Es wurde festgestellt, dass die Spannungsqualität aus verschiedenen Gründen zunehmend überwacht werden muss - einerseits aufgrund verstärkter Resonanzgefahr durch wachsenden Anteil nichtlinearer Verbraucher bei gleichzeitig sinkenden Anteil ohmscher Lasten und andererseits, da der durch den veränderten Energiemarkt verstärkte Kostendruck die Evaluierung auch unter wirtschaftlichen Gesichtspunkten notwendig macht. Das Konzept eines entsprechend entwickelten Messsystems zur Beurteilung der Spannungsqualität in Verteilungsnetzen wurde vorgestellt. Der Einsatz der verwendeten Beurteilungsalgorithmen stand hierbei im Zentrum des Messsystems, deren flexibler Aufbau sowohl langzeitige Spannungsqualitätsmessungen aber auch Emissionsmessungen an einzelnen Geräten normgerecht ermöglicht. Im Weiteren wurden Modellierungsansätze für elektrische Betriebsmittel sowie sowohl lineare- als auch nicht-lineare Lasten für die Modellierung im FrequenzBereich vorgestellt. Dabei wurde verdeutlicht, dass das Zusammenwirken zwischen der Störquelle - nichtlinearer Last - und der Störsenke - dem Versorgungsnetz - sehr wesentlich für die Genauigkeit der Simulationen ist. Darauf aufbauend wurde eine messungsbasierte Methode vorgeschlagen, um die zu berücksichtigenden Nichtlinearitäten mit Hilfe einer Crossed-Frequency-Admittance-Matrix im Harmonischen-Bereich zu modellieren. Ein Beispiel illustriert detailliert dieses Verfahren, so dass alle Abhängigkeiten und Wechselwirkungen deutlich werden.  Um die in der Arbeit entwickelte Methode sinnvoll durchführen zu können, müssen im Voraus die sensitivsten Knoten in einem Verteilungsnetz gefunden werden. Deshalb wurde als Kern der entwickelten Methode ein Verfahren vorgeschlagen, das auf der internen Struktur des zu analysierenden Netzes basiert. Nachdem die mathematischen Grundlagen dieses spektralen Ansatzes vorgestellt wurden, wurde eine Beispielanalyse am realen Netz durchgeführt um die Eigenschaften dieser qualitativen Methode zu veranschaulichen. Die Untersuchungen zeigten, dass die Methode zur Beurteilung von Spannungsqualität in Verteilungsnetzen wirkungsvoll anwendbar ist und zu besserer Genauigkeit bei Simulationen führt. Durch die Filterungseigenschaft der Spektralanalyse wurde eine bessere Selektivität der Analyse erreicht als bei herkömmlichen Methoden der Spannungsqualitätsanalyse. Das ist besonders bei Verteilungsnetzen von Vorteil, bei denen ungünstige Verhältnisse bezüglich Spannungs– und Stromqualität, hervorgerufen durch niedrige Kurzschlussleistungen und eine Vielzahl von Störquellen in den Verteilungsnetzen, entstehen. &nbsp

An improved harmonic load flow formulation

This is a post-peer-review, pre-copyedit version of an article published in Electric power components and systems. The final authenticated version is available online at: http://dx.doi.org/10.1080/15325008.2019.1689450The paper contributes an improved harmonic load flow formulation with fewer convergence problems but the same accurate results as traditional formulations. The proposed formulation approaches the harmonic load flow problem as a single nonlinear equation system where the harmonic bus voltage influence on nonlinear load behavior is considered and harmonic bus voltages at linear buses are not included as unknowns. This formulation allows any sort of nonlinear load to be considered and uses the Newton-Raphson method with true Jacobian matrix to reduce the inherent increase in the number of iterations caused by the presence of highly distorted bus voltages. The numerical results obtained when solving a three-bus network operating under highly distorted bus voltages using traditional harmonic load flow formulations and the improved formulation are comparatively discussed.Peer ReviewedPostprint (author's final draft

Risk analysis of Geomagnetically Induced Current (GIC) in Power Systems

Solar storms are a phenomenon that has a wide array of adverse consequences on technological systems, power systems in particular. During severe solar storms a geomagnetically induced current (GIC) starts to flow through long conducting structures, such as power lines and pipelines. The probability of solar storms has a roughly linear relation with the sunspot activity level which varies in 11 years cycles and at the moment of writing this thesis we are approaching the maxima of solar cycle 24. This thesis is a risk analysis of GIC in power systems and describes the causes and sources of GIC, the consequences, both on component level and on system level, and the likelihood of occurrence. When GIC flows through a transformer it causes the core to saturate, which leads to (a) increased reactive power consumption, (b) high levels of harmonics in the power system and (c) localized heating of the transformer. Point a and b are confirmed through simulations. High harmonics levels can cause protective relays to sense false fault conditions and trip. On a system level this can lead to (a) loss of production (b) local blackouts or (c) widespread blackouts. Localized heating of transformers can lead to permanent damage and spare parts and replacement units are associated with having long lead times. Communication and control systems are also subject to GIC and other solar storm related interferences. The thesis also contains a discussion about GIC risk associated to gas pipelines. The likelihood of solar storms is discussed and a method for determining the exceedance probability of extreme values for solar storms such as a 100-year storm is presented. The exceedance probability of a 100- year storm during 2012-2014 is estimated to 4.7%. Possible risk treatment strategies and forecasting capabilities are also briefly discussed, in order to briefly illustrate possible risk management schemes. This report should facilitate risk evaluation and provide the information needed to calculate quantitative risk values with respect to solar storms and power systems. In order to fully understand the extent of the consequences of a 100-year storm further studies are needed in order to take the complexities of covariance and the interconnectedness of different components and systems into account

Machine Learning and Data Mining Applications in Power Systems

This Special Issue was intended as a forum to advance research and apply machine-learning and data-mining methods to facilitate the development of modern electric power systems, grids and devices, and smart grids and protection devices, as well as to develop tools for more accurate and efficient power system analysis. Conventional signal processing is no longer adequate to extract all the relevant information from distorted signals through filtering, estimation, and detection to facilitate decision-making and control actions. Machine learning algorithms, optimization techniques and efficient numerical algorithms, distributed signal processing, machine learning, data-mining statistical signal detection, and estimation may help to solve contemporary challenges in modern power systems. The increased use of digital information and control technology can improve the grid’s reliability, security, and efficiency; the dynamic optimization of grid operations; demand response; the incorporation of demand-side resources and integration of energy-efficient resources; distribution automation; and the integration of smart appliances and consumer devices. Signal processing offers the tools needed to convert measurement data to information, and to transform information into actionable intelligence. This Special Issue includes fifteen articles, authored by international research teams from several countries

Allocation of transmission losses to determine tariff

The recent widespread restructuring and unbundling of the electricity industry has introduced some changes in the organization of the sector, thereby creating a more competitive environment in which each participant must bear its own cost and be responsible for its own contribution to losses in the system. The allocation of transmission losses has become an important issue as this determines how and what to charge each of the participants in the industry. This allocation is best assessed and based on their individual contributions to grid losses. Earlier methods used in loss allocation include: The Pro rata approach which arbitrarily allocates 50% each to the load and generator; the Marginal procedure allocation, which is either positive or negative; the Proportional sharing method which bases its allocation on the Kirchhoff’s current law and allocates no losses to the transmission line and the Equilateral bilateral exchange (EBE) method. Most of the other methods, such as the Game theory method, Circuit theory method, Graph theory method, and Optimization methods are either mathematically complex in operation or time-consuming. And till date, none of these methods could be used to allocate transmission losses with fairness and transparency. Currently, power loss measurements have been estimated based on ideal conditions in which there exist a balanced load and reactive power, while the inefficiency caused by distortion and the unbalanced load is not usually taken into consideration. This research introduces a novel and a fairer method of determining power losses by using the Thévenin impedance in calculating the line parameters used in the determination of power losses. Since losses associated with a transmission power line depend on the wire resistance and the line current (I2 R), the Thévenin equivalent of the system is calculated from the point of connecting each participant (generator or load), i.e. the point of common coupling, to determine the system losses without prior knowledge of the power system supply quantities. This thesis identifies the avoidable losses in the system, which participants pay for because of the inadequacy of current methods which use only reactive powers (inductive and capacitive) to determine the power losses in the allocation of losses and in the calculation of the power system tariff. This report elucidates how to estimate the losses that can be avoided by the participants. This loss is equal to the numerical power difference in the conventional power loss and the new power loss calculation method which utilizes the general power theory where two components that are orthogonal to each other, making non-active power (reactive power and distortion power) are used. This difference, which is an extra loss created by the participants, can be conserved to reduce power generation cost and tariffs. This method which was tested on a standard IEEE test system is transparent, fair and requires a comparatively short time to execute, making it suitable for decision making thus emphasizing the importance of the proposed solution

Evaluating the level of harmonic distortion in a typical distribution feeder

Steady-state analysis of electrical power systems is largely based on linear and sinusoidal AC circuits which allow the concept of impedance, phasors and well-defined power quantities (i.e., real, reactive and apparent powers). In reality, however, the electric load which was once composed of linear elements (e.g., induction motors, incandescent lighting, etc …) is becoming more and more nonlinear due to the wide-spread use of electronic components such as fluorescent lighting and variable-frequency drives that power the majority of electric motors. As a consequence, the current drawn by such devices is often distorted, thus containing a number of high frequency harmonics that are superimposed on the fundamental 60 Hz component. As these high-frequency harmonic currents flow through the power distribution apparatus, they in turn cause distortion in the voltage. The distorted voltage can in turn affect other loads that share a transformer or branch circuit with the original harmonic loads. It has been shown that classical definitions of electric power; namely, active, reactive and apparent powers, do not fulfill the conditions caused by harmonics. Consequently, various power definitions and calculation methods have been proposed in the literature. It is hypothesized that existing definitions of power other than the active part in non-sinusoidal circuits are based on a non-real (i.e., frequency) domain and rate theoretical in nature. Therefore, these are not only hard (often impossible) to interpret their physical meaning and make use of them, but also hard to implement in measuring devices. On the other hand, power definitions that are based on a real time domain are expected to have simpler physical interpretations and easier to measure. A simple definition of non-active power will be of great value to the power industry. It is also hypothesized that a typical electrical power distribution system can handle significantly more non-linear loads than previously thought as modern electrical loads are less sensitive to distortion in the voltage supply. The motivation that led to the proposed works stems from the fast moving events that are taking place in the electric utility industry. more specifically, many utilities are considering additional customer charges (such as charging the residential sector for peak demand, reactive power consumption, and renewable power generation) in order to ring more profits. The recently installed smart meters that primarily record energy consumption every 5 minutes and communicate wirelessly the local utility, do have the ability to measure other electrical quantities. The way these quantities are defined and measured is of critical importance to both the supplier and consumer

Advanced Signal Processing Techniques Applied to Power Systems Control and Analysis

The work published in this book is related to the application of advanced signal processing in smart grids, including power quality, data management, stability and economic management in presence of renewable energy sources, energy storage systems, and electric vehicles. The distinct architecture of smart grids has prompted investigations into the use of advanced algorithms combined with signal processing methods to provide optimal results. The presented applications are focused on data management with cloud computing, power quality assessment, photovoltaic power plant control, and electrical vehicle charge stations, all supported by modern AI-based optimization methods