On power system automation: a Digital Twin-centric framework for the next generation of energy management systems

The ubiquitous digital transformation also influences power system operation. Emerging real-time applications in information (IT) and operational technology (OT) provide new opportunities to address the increasingly demanding power system operation imposed by the progressing energy transition. This IT/OT convergence is epitomised by the novel Digital Twin (DT) concept. By integrating sensor data into analytical models and aligning the model states with the observed system, a power system DT can be created. As a result, a validated high-fidelity model is derived, which can be applied within the next generation of energy management systems (EMS) to support power system operation. By providing a consistent and maintainable data model, the modular DT-centric EMS proposed in this work addresses several key requirements of modern EMS architectures. It increases the situation awareness in the control room, enables the implementation of model maintenance routines, and facilitates automation approaches, while raising the confidence into operational decisions deduced from the validated model. This gain in trust contributes to the digital transformation and enables a higher degree of power system automation. By considering operational planning and power system operation processes, a direct link to practice is ensured. The feasibility of the concept is examined by numerical case studies.The electrical power system is in the process of an extensive transformation. Driven by the energy transition towards renewable energy resources, many conventional power plants in Germany have already been decommissioned or will be decommissioned within the next decade. Among other things, these changes lead to an increased utilisation of power transmission equipment, and an increasing number of complex dynamic phenomena. The resulting system operation closer to physical boundaries leads to an increased susceptibility to disturbances, and to a reduced time span to react to critical contingencies and perturbations. In consequence, the task to operate the power system will become increasingly demanding. As some reactions to disturbances may be required within timeframes that exceed human capabilities, these developments are intrinsic drivers to enable a higher degree of automation in power system operation. This thesis proposes a framework to create a modular Digital Twin-centric energy management system. It enables the provision of validated and trustworthy models built from knowledge about the power system derived from physical laws, and process data. As the interaction of information and operational technologies is combined in the concept of the Digital Twin, it can serve as a framework for future energy management systems including novel applications for power system monitoring and control, which consider power system dynamics. To provide a validated high-fidelity dynamic power system model, time-synchronised phasor measurements of high-resolution are applied for validation and parameter estimation. This increases the trust into the underlying power system model as well as the confidence into operational decisions derived from advanced analytic applications such as online dynamic security assessment. By providing an appropriate, consistent, and maintainable data model, the framework addresses several key requirements of modern energy management system architectures, while enabling the implementation of advanced automation routines and control approaches. Future energy management systems can provide an increased observability based on the proposed architecture, whereby the situational awareness of human operators in the control room can be improved. In further development stages, cognitive systems can be applied that are able to learn from the data provided, e.g., machine learning based analytical functions. Thus, the framework enables a higher degree of power system automation, as well as the deployment of assistance and decision support functions for power system operation pointing towards a higher degree of automation in power system operation. The framework represents a contribution to the digital transformation of power system operation and facilitates a successful energy transition. The feasibility of the concept is examined by case studies in form of numerical simulations to provide a proof of concept.Das elektrische Energiesystem befindet sich in einem umfangreichen Transformations-prozess. Durch die voranschreitende Energiewende und den zunehmenden Einsatz erneuerbarer Energieträger sind in Deutschland viele konventionelle Kraftwerke bereits stillgelegt worden oder werden in den nächsten Jahren stillgelegt. Diese Veränderungen führen unter anderem zu einer erhöhten Betriebsmittelauslastung sowie zu einer verringerten Systemträgheit und somit zu einer zunehmenden Anzahl komplexer dynamischer Phänomene im elektrischen Energiesystem. Der Betrieb des Systems näher an den physikalischen Grenzen führt des Weiteren zu einer erhöhten Störanfälligkeit und zu einer verkürzten Zeitspanne, um auf kritische Ereignisse und Störungen zu reagieren. Infolgedessen wird die Aufgabe, das Stromnetz zu betreiben anspruchsvoller. Insbesondere dort wo Reaktionszeiten erforderlich sind, welche die menschlichen Fähigkeiten übersteigen sind die zuvor genannten Veränderungen intrinsische Treiber hin zu einem höheren Automatisierungsgrad in der Netzbetriebs- und Systemführung. Aufkommende Echtzeitanwendungen in den Informations- und Betriebstechnologien und eine zunehmende Menge an hochauflösenden Sensordaten ermöglichen neue Ansätze für den Entwurf und den Betrieb von cyber-physikalischen Systemen. Ein vielversprechender Ansatz, der in jüngster Zeit in diesem Zusammenhang diskutiert wurde, ist das Konzept des so genannten Digitalen Zwillings. Da das Zusammenspiel von Informations- und Betriebstechnologien im Konzept des Digitalen Zwillings vereint wird, kann es als Grundlage für eine zukünftige Leitsystemarchitektur und neuartige Anwendungen der Leittechnik herangezogen werden. In der vorliegenden Arbeit wird ein Framework entwickelt, welches einen Digitalen Zwilling in einer neuartigen modularen Leitsystemarchitektur für die Aufgabe der Überwachung und Steuerung zukünftiger Energiesysteme zweckdienlich einsetzbar macht. In Ergänzung zu den bereits vorhandenen Funktionen moderner Netzführungssysteme unterstützt das Konzept die Abbildung der Netzdynamik auf Basis eines dynamischen Netzmodells. Um eine realitätsgetreue Abbildung der Netzdynamik zu ermöglichen, werden zeitsynchrone Raumzeigermessungen für die Modellvalidierung und Modellparameterschätzung herangezogen. Dies erhöht die Aussagekraft von Sicherheitsanalysen, sowie das Vertrauen in die Modelle mit denen operative Entscheidungen generiert werden. Durch die Bereitstellung eines validierten, konsistenten und wartbaren Datenmodells auf der Grundlage von physikalischen Gesetzmäßigkeiten und während des Betriebs gewonnener Prozessdaten, adressiert der vorgestellte Architekturentwurf mehrere Schlüsselan-forderungen an moderne Netzleitsysteme. So ermöglicht das Framework einen höheren Automatisierungsgrad des Stromnetzbetriebs sowie den Einsatz von Entscheidungs-unterstützungsfunktionen bis hin zu vertrauenswürdigen Assistenzsystemen auf Basis kognitiver Systeme. Diese Funktionen können die Betriebssicherheit erhöhen und stellen einen wichtigen Beitrag zur Umsetzung der digitalen Transformation des Stromnetzbetriebs, sowie zur erfolgreichen Umsetzung der Energiewende dar. Das vorgestellte Konzept wird auf der Grundlage numerischer Simulationen untersucht, wobei die grundsätzliche Machbarkeit anhand von Fallstudien nachgewiesen wird

Smart grids: smart meters and non intrusive load monitoring

El objetivo de este proyecto consiste en sintetizar los conceptos generales de las redes inteligentes (Smart Grids), los cambios que se prevén en la red eléctrica y las principales tecnologías que apoyaran el desarrollo de las mismas. Una Smart Grid es una sistema que permite la comunicación bidireccional entre el consumidor final y las compañías eléctricas, de forma que la información proporcionada por los consumidores pueda ser utilizada por las compañías eléctricas para permitir una operación mas eficiente de las red eléctrica, así como ofrecer nuevos servicios a los clientes. El desarrollo de las Smart Grids es esencial si la comunidad global quiere alcanzar objetivos comunes de seguridad energética, desarrollo económico y mitigación del cambio climático. Para ello, se están desarrollando e implementando nuevas tecnologías como los medidores inteligentes (Smart Meters) y nuevas técnicas de medida de consumo eléctrico como la monitorización no intrusiva (Non Intrusive Load Monitoring). Los Smart Meters son medidores de electricidad, agua o gas que recopilan de forma automática los datos de medida y los envían a las compañías eléctricas permitiendo a estas tener una mejor visión de la distribución eléctrica y proporcionan a sus clientes un mayor conocimiento de su propio consumo. La monitorización no intrusiva es una técnica que detecta los eventos de aparatos eléctricos analizando la demanda total de la carga. Esto es posible debido a que los aparatos presentan características especiales en los momentos de conexión y desconexión consistentes en cambios tanto positivos como negativos en las potencias activa y reactiva. Como dichas características son únicas en cada dispositivo, es posible reconocer el perfil de cada uno de ellos pudiendo saber que dispositivos se están encendiendo o apagando, así como el consumo eléctrico de cada uno de ellos. Esto es lo que ofrece la tecnología Plugwise, que mediante el uso de sus dispositivos permite monitorizar y controlar el consumo eléctrico de una vivienda, oficina o empresa y poder ver los resultados en nuestro propio Smartphone o PC. El uso de tecnología Plugwise en combinación con un Smart Meter permite que tanto clientes como compañías eléctricas sean conscientes de cuanto, como y donde se consume la electricidad

Study of the electric vehicle implementation on the smart grid

Since some years ago the electric vehicle popularity, and so the pluggable hybrid, notably increased although it's not a brand new development. To understand it, together with the oil prices rise, another factors are to be considered like the CO2 emissions reduction or the fossil fuels dependence. This work is devoted to the study of the electric vehicle integration on the Smart Grid exploring the synergies and the challenges of it. Geographically the study illustrates the Spanish case using as a main data inputs the International Energy Agency forecasts for western Europe together with some highly valuable European Union studies, especially those issued by the JRC. On a first step an electric vehicle market penetration investigation shows that, on year 2030, a 21% of the cars running trough the Spanish roads will be electrically powered. The impact of such a presence of electric vehicles could be assumed, disregarding power grid meshing requirements, by the Spanish electric generation pool and transport infrastructures even if no improvement on them takes place on the next 15 years. The bottleneck will then be found on the low voltage distribution systems and their associated medium voltage lines, that will not be able to hold the electric vehicle deployment forecast unless their capacities are increased or the users car availability is impaired. A solution must be found to this fix this issue that should also explore all the possible synergies with the rest of the electrical system. As a result two countermeasures arise preserving as much as possible the cars availability to their owners. One is to size up all the low voltage and related medium voltage systems to accommodate bigger power flows solving the main problem but doing nothing to integrate the steadily increasing renewal energy that should be consumed when is produced or stored on expensive, environmentally harmful, hydropower pumping stations. The other countermeasure, the main outcome of the next pages, derives from the functionalities of the Smart Grid and is in fact a reviewed version of the, yet popular, Vehicle To Grid (V2G) strategy. Its about to add an inertia battery emulating the inertia tanks in central sanitary water production facilities. Such a kind of proposal is possible because the grid-wide information share and distributed control that lies on the Smart Grid concept. The countermeasure will allow not only a 21% presence of the electric vehicle but even a 100% with almost no cost for the owners, will greatly help the renewables integration as offers a big energy storage capacity on valley hours without compromising the electric vehicles batteries life and also could prevent outages acting as a grid energy supplier in some case

Involvement of smart end-users in a Smart Grid

To reach the 20-20-20 goals set by EU in 2009, all parts of the electricity system must be made more efficient. The previous fit-and-forget system must be left behind for a more active grid design. This also means that end-users must become an active part of the power grid. Consumers should be able to actively sell and buy their own energy and control their own usage of energy, or allow for a third party to handle this. A large part of the smart grid will be realized by using computer technology and telecommunication, which can send information to the different parts of the electricity grid. This makes it possible to make complex decisions, based on large quantities of collected data, concerning the most beneficial grid control decisions. This also enables energy efficiency throughout the entire electricity grid, all the way from production through transmission and distribution, including customer premises. This will help Finland reach the 202020 goals, but also achieve a function of the electricity grid that aligns with today’s expectations and demand for functionality. In this thesis the features that may arise from the development of a new smarter electricity grid has been investigated and how these functions align with the ordinary electricity consumers' interest and expectations on functionality. Demand response, distributed generation, energy storage systems, home automation systems and interactive user interfaces are some of the discussed features. The behavior of the end-users was researched through literature studies and by analyzing customer contacts at Fortum. The analysis showed two main reasons for contacting Fortum. Forced contacts, like customers moving, are matters that could be solved to some extent by interactive user-interfaces. The investigative contacts showed customer interest in electricity prices and agreements but also problems with understanding the electricity bill. In this thesis the Rogers' model for diffusion of innovations has also been described and used to analyze smart grid and smart house technology. The main result of the thesis is the definition of a collection of smart house functionalities that would serve as a good base for the development of added value services.fi=Opinnäytetyö kokotekstinä PDF-muodossa.|en=Thesis fulltext in PDF format.|sv=Lärdomsprov tillgängligt som fulltext i PDF-format

Modeling and simulation of power and energy demands to dimension an alternative energy supply for the aquaculture industry. Use of OpenModelica to develop an applicable simulation model for the energy and power demands

The purpose of the research is to investigate whether feed barges currently running on diesel generator can be powered by alternative energy sources where power from shore is limited. Through data collection, several models are developed in OpenModelica to represent the power and energy distribution on a feed barge. Using the Power Systems library provided in OpenModelica, it has offered benefits of modeling complex power systems put together by several simpler models. User-friendly, preset components from the Power Systems library provides simplicity for that matter. A diesel and battery-electric model is developed to dimension the battery to account for different power strategies throughout a production cycle for the farmed fish. The result from dimensioning of the battery provide some clues on how to dimension alternative energy providers to replace the diesel generators. Variations in the power consumption makes feed barges a good candidate for hybridization with a battery as an energy buffer to either shave the power peaks or used as a source to cover the base loads. By utilizing batteries, alternative energy sources and carriers are made available in order to reduce emissions from diesel generators

Decentralised Optimisation and Control in Electrical Power Systems

Emerging smart-grid-enabling technologies will allow an unprecedented degree of observability and control at all levels in a power system. Combined with flexible demand devices (e.g. electric vehicles or various household appliances), increased distributed generation, and the potential development of small scale distributed storage, they could allow procuring energy at minimum cost and environmental impact. That however presupposes real-time coordination of demand of individual households and industries down at the distribution level, with generation and renewables at the transmission level. In turn this implies the need to solve energy management problems of a much larger scale compared to the one we currently solve today. This of course raises significant computational and communications challenges. The need for an answer to these problems is reflected in today’s power systems literature where a significant number of papers cover subjects such as generation and/or demand management at both transmission and/or distribution, electric vehicle charging, voltage control devices setting, etc. The methods used are centralized or decentralized, handling continuous and/or discrete controls, approximate or exact, and incorporate a wide range of problem formulations. All these papers tackle aspects of the same problem, i.e. the close to real-time determination of operating set-points for all controllable devices available in a power system. Yet, a consensus regarding the associated formulation and time-scale of application has not been reached. Of course, given the large scale of the problem, decentralization is unavoidably part of the solution. In this work we explore the existing and developing trends in energy management and place them into perspective through a complete framework that allows optimizing energy usage at all levels in a power system