Power System Simulation, Control and Optimization

This Special Issue “Power System Simulation, Control and Optimization” offers valuable insights into the most recent research developments in these topics. The analysis, operation, and control of power systems are increasingly complex tasks that require advanced simulation models to analyze and control the effects of transformations concerning electricity grids today: Massive integration of renewable energies, progressive implementation of electric vehicles, development of intelligent networks, and progressive evolution of the applications of artificial intelligence

Modeling of Direct Current Grid Equipment for the Simulation and Analysis of Electromagnetic Transients

RÉSUMÉ Les transmissions à base de courant continu sont capables de répondre mieux que les transmissions traditionnelles à base de courant alternatif aux enjeux de nos jours tels que l’intégration des énergies renouvelables, les difficultés avec l’installation des nouvelles lignes aériennes pour les raisons socio-environnementaux, la gestion des flux de puissance sur le réseau électrique. Ceci est grâce aux systèmes de contrôle performants et rapides, à un niveau de fiabilité accrue des composants utilisés, à l’efficacité énergétique des technologies de pointe, telles que les convertisseurs modulaires multiniveaux (Modular Multilevel Converter ou MMC en anglais). Ces avantages ont contribué à une croissance rapide du nombre de transmissions à courant continu à travers le monde dans les dernières années, avec les plans d’établir des réseaux multi-terminaux d’un niveau supérieur aux réseaux électriques traditionnels dans le but de les renforcer. Les outils de simulation numériques sont nécessaires pour faciliter et accélérer la mise en œuvre de ce type de projets d’envergure. Ils permettent d’analyser et d’étudier les systèmes électriques de plus en plus complexes et par conséquent d’éviter les problèmes opérationnels, d’augmenter la fiabilité et l’efficacité des réseaux électriques. La complexité accrue des réseaux électriques modernes qui contiennent les composants à base de l’électronique de puissance tels que les liaisons à courant continu exige une recherche sur les outils de simulation et les modèles avancés. Ainsi, cette thèse se focalise sur le développement d’un cadre pour les simulations précises et rapides des liaisons à courant continu. À la suite d’une revue de la littérature il est démontré que la modélisation des MMCs a un impact particulièrement important sur la précision et l’accélération des simulations et par conséquent une grande partie de cette thèse est dédiée aux différentes méthodes pour réduire le temps de simulation et améliorer la précision des résultats dans les études avec les MMCs. Le cœur du sujet commence par la présentation de la modélisation des MMC hybrides et leurs systèmes de contrôle. Les modèles sont classés en quatre catégories selon le niveau de précision : le modèle détaillé permet de représenter les non-linéarités au niveau des composants semiconducteurs.----------ABSTRACT Compared to the traditional alternating current technology-based electrical grids, High-Voltage Direct Current (HVDC) transmission systems can more effectively respond to the challenges of the modern power grid related to the integration of renewable energy sources, difficulty to install new overhead lines due to socio-environmental reasons, and power flow management. This is mainly due to high performance of control systems, fast response times, reliable components and energy efficiency of the state-of-the-art HVDC technologies of today, such as the Modular Multilevel Converter (MMC). These advantages have contributed to the rapid growth in the number of HVDC projects in recent years with plans of having overlay HVDC grids that can reinforce the existing electrical grids. To facilitate and accelerate the implementation of large-scale HVDC projects, it is required to use numerical simulation tools. Such tools allow to perform advanced analysis of involved electrical systems for preventing operating problems, increasing robustness and efficiency in power grids. The increased level of complexity of modern power grids with power electronics-based components, such as HVDC, requires research on advanced simulation tools and models. Therefore, this thesis aims to develop a framework allowing for accurate modeling and fast simulations of HVDC projects. After analysis of existing literature, the areas with high potential impact on accuracy and acceleration of electromagnetic transient simulations are found, and it is the modeling of MMCs that is considered in this thesis. Thus, a significant part of this thesis is dedicated to research on efficient modeling techniques that allow to reduce simulation time and improve accuracy for MMC-based HVDC systems. The modeling aspects and control systems of hybrid MMCs are presented first. The MMC models used in electromagnetic transient simulations are grouped into four categories. The detailed model represents the nonlinear current-voltage characteristics of semiconductor switches. The detailed equivalent model represents the switches as two-value resistances: a small value for the closed state and a large value for the open state. The arm equivalent model assumes all capacitors in each arm have identical voltages, so a single equivalent capacitor is used to represent the whole arm, thus greatly reducing the computational burden of the model

Convergence of the Fast State Estimation for Power Systems

Power system state estimation is a fundamental computational process that requires both speed and reliability. To meet the needs, some variants of the constant Jacobian methods have been used in the industry over the last several decades. The variants work very well under normal operating conditions with nominal values of the states. However, the convergence of the methods are not analysed mathematically and it may contain pitfalls. In this study, the convergence of the constant Jacobian methods are analysed and it is shown that the methods fail under high variations of the states. To increase the reliability of the processes, a multi-Jacobian method is proposed. Through simulation, a special case is shown for IEEE 68, and IEEE 118-bus systems where the Jacobian calculated with the nominal value fails, and the proposed multi-Jacobian method succeeds

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

Housing equilibrium price framework for Malaysian middle Class group in affordable housing market

Failure in getting housing equilibrium price for affordable housing market has become a hot topic that is often discussed in the press due to the imbalance between housing demanded and supplied. The basic purpose of the research was to investigate the relationship between macroeconomic housing demand and supply detenninant factors and affordable housing needs in Malaysia, and to dete1111ine the equilibrium house price for middle-class income in the affordable housing market. The research involved the development of theoretical framework by synthesising the models and framework developed by past researchers on the housing equilibrium price framework. It also uses time series analysis together with regression analysis to collect and analyse data. As initial, 371 respondents from household's side and 32 respondents from developer's side in Melaka Tengah were selected as samples as case study in Melaka. During data analysed, around 200 questionnaires from households and 32 questionnaires from developers can be used. The data was analysed using SPSS software to investigate the relationship between macroeconomic housing demand and supply determinant factors towards the needs f and supply of afordable housing market. From the investigation, current house price, monetary status and population changes are the most critical factors that lead to the needs of affordable housing supplies. Meanwhile, developers put the interest rate, government interventions and population changes as the catalyst to develop the affordable housing projects. On the other hand, the empirical data of housing prices are collected from NAPIC from 2006 to 2015. The equilibrium price calculated from the sales perfonnance within four quarter reported by NAPIC is examined using linear regression method. Based on these themes, the research contended that the housing equilibrium price can be achieved using empirical data from demand and supply with supported from current house price, monetary status and population changes the interest rate, government interventions and population changes. Hence, government is the key player and be a pulling effect in controlling the housing price by using the housing demand and supply determinant factor to create a win-win situation between middle-class income and housing developers