Impact of static and dynamic load models on security margin estimation methods

The post-contingency loadability limit (PCLL) and the secure operating limit (SOL) are the two main approaches used when computing the security margins of an electric power system. While the SOL is significantly more computationally demanding than the PCLL, it can account for the dynamic response after a disturbance and generally provides a better measure of the security margin. In this study, the difference between these two methods is compared and analyzed for a range of different contingency and load model scenarios. A methodology to allow a fair comparison between the two security margins is developed and tested on a modified version of the Nordic32 test system. The study shows that the SOL can differ significantly from the PCLL, especially when the system has a high penetration of loads with constant power characteristics or a large share of induction motor loads with fast load restoration. The difference between the methods is also tested for different contingencies, where longer fault clearing times are shown to significantly increase the difference between the two margins

Wide Area Monitoring and Control

Today\u27s interconnected power system is deregulated for wholesale power transfers. In 1996 Federal Energy Regulatory Commission provided open access of the transmission network to utilities. Since then utilities are transferring power over long distances to bring reliable and economical electric supply to their customers. As the number of wholesale power transactions taking place over an interconnected system are increasing, system operators in control areas are forced to monitor the grid on a large scale to operate it reliably. Before scheduling such a large scale power transactions, it is necessary to make sure that such transaction will not violate system operating steady state security limits such as transmission line-flow limits and bus voltage limits. The ideal solution to this problem is to consider entire interconnected system as one system to monitor it. However, this solution is technically expensive if not impossible and hindered by confidentiality issues. This research aims to develop tools that help the system operators to operate the deregulated power grid reliably. State estimation is the tool used by today\u27s energy control centers to develop a base case of the system in real-time, which is further used to study the impact of disturbances and power transactions on static and dynamic security limits of the system. In order to monitor the deregulated power system, a wide area state estimator is required. In this dissertation a two-level approach to achieve such a solution is presented. This way, individual areas are allowed to run their own state estimator, without exchanging any real-time data with neighbor areas. The central coordinator then coordinates state estimator results available from individual areas to bring them to a global reference. This dissertation also presents the application of measurements from GPS synchronized phasor measurement units to improve accuracy of two-level state estimator. In addition to monitoring, system operators also need to determine that if they can allow the scheduled transaction to take place. This requires them to determine transfer capability of the system in real-time. This dissertation presents new iterative transfer capability algorithm which can be used in real-time. As an interconnected system is deregulated and the power transactions are taking place through many control areas, a system wide solution of transfer capability is required. This dissertation presents a two-level framework similar to one used for state estimation to achieve multi-area transfer capability solution. In general, the research work carried out would help in improving power system reliability and operation

Impact of Renewables on Grid Strength, Transient Stability, and Grid Operation Characterization

Increasing amounts of inverter based resources (IBR) are being added to the grid. With environmental and climate change concerns, even more is projected to be added. Many companies and regions are setting goals for high levels of renewables. As IBR are added to the grid, it changes how the power system responds to disturbances. With less traditional synchronous machines on the system, this decreases the inertia and can add stability concerns. Studies are required to know how power systems will respond to the change in generation resources. This dissertation contributes to studying transient stability and grid strength on the North American transmission system to help determine the future state of the system. Monitoring of the power system is also important to provide awareness of the system state. Especially as the generation mix changes and uncertainties are added to the grid, it is vital to have an accurate understanding of whether the system is in normal operation or experiencing stress. It is important to have early awareness of system stress to be able to prevent instability. This dissertation will also explore potential methods to monitor for early awareness of system stress. This dissertation documents the efforts to study and monitor current and future changes on the power system. Chapter 1 presents a study of the impact of high penetration of IBR on grid strength, in both the Eastern Interconnection (EI) and Western Interconnection (WI). Chapter 2 documents a study of the impact of high photovoltaic (PV) penetration on transient stability in the Electric Reliability Council of Texas (ERCOT) System. And Chapter 3 describes an effort to study active power and voltage angle data on the Southern Company system in order to investigate voltage angle difference as an indicator of early event awareness due to stress on the system caused by power flow through an interface

Analysis and management of security constraints in overstressed power systems

Management of operational security constraints is one of the important tasks performed by system operators, which must be addressed properly for secure and economic operation. Constraint management is becoming an increasingly complex and challenging to execute in modern electricity networks for three main reasons. First, insufficient transmission capacity during peak and emergency conditions, which typically result in numerous constraint violations. Second, reduced fault levels, inertia and damping due to power electronic interfaced demand and stochastic renewable generation, which are making network more vulnerable to even small disturbances. Third, re-regulated electricity markets require the networks to operate much closer to their operational security limits, which typically result in stressed and overstressed operating conditions. Operational security constraints can be divided into static security limits (bus voltage and branch thermal limits) and dynamic security limits (voltage and angle stability limits). Security constraint management, in general, is formulated as a constrained, nonlinear, and nonconvex optimization problem. The problem is usually solved by conventional gradient-based nonlinear programming methods to devise optimal non-emergency or emergency corrective actions utilizing minimal system reserves. When the network is in emergency state with reduced/insufficient control capability, the solution space of the corresponding nonlinear optimization problem may be too small, or even infeasible. In such cases, conventional non-linear programming methods may fail to compute a feasible (corrective) control solution that mitigate all constraint violations or might fail to rationalize a large number of immediate post-contingency constraint violations into a smaller number of critical constraints. Although there exists some work on devising corrective actions for voltage and thermal congestion management, this has mostly focused on the alert state of the operation, not on the overstressed and emergency conditions, where, if appropriate control actions are not taken, network may lose its integrity. As it will be difficult for a system operator to manage a large number of constraint violations (e.g. more than ten) at one time, it is very important to rationalize the violated constraints to a minimum subset of critical constraints and then use information on their type and location to implement the right corrective actions at the right locations, requiring minimal system reserves and switching operations. Hence, network operators and network planners should be equipped with intelligent computational tools to “filter out” the most critical constraints when the feasible solution space is empty and to provide a feasible control solution when the solution space is too narrow. With an aim to address these operational difficulties and challenges, this PhD thesis presents three novel interdependent frameworks: Infeasibility Diagnosis and Resolution Framework (IDRF), Constraint Rationalization Framework (CRF) and Remedial Action Selection and Implementation Framework (RASIF). IDRF presents a metaheuristic methodology to localise and resolve infeasibility in constraint management problem formulations (in specific) and nonlinear optimization problem formulations (in general). CRF extends PIDRF and reduces many immediate post-contingency constraint violations into a small number of critical constraints, according to various operational priorities during overstressed operating conditions. Each operational priority is modelled as a separate objective function and the formulation can be easily extended to include other operational aspects. Based on the developed CRF, RASIF presents a methodology for optimal selection and implementation of the most effective remedial actions utilizing various ancillary services, such as distributed generation control, reactive power compensation, demand side management, load shedding strategies. The target buses for the implementation of the selected remedial actions are identified using bus active and reactive power injection sensitivity factors, corresponding to the overloaded lines and buses with excessive voltage violations (i.e. critical constraints). The RASIF is validated through both static and dynamic simulations to check the satisfiability of dynamic security constraints during the transition and static security constraints after the transition. The obtained results demonstrate that the framework for implementation of remedial actions allows the most secure transition between the pre-contingency and post-contingency stable equilibrium points

Optimal Transmission Investment Strategies for Sustainable Power Systems

Maintaining security and reliability in the electricity supply is fundamental to the functioning of a modern society and drives the need for adequate transmission capacity for both market participants and customers. Planning the investment in transmission has always been a complicated undertaking due to the high development costs and long lead times. Furthermore, to anticipate the future needs of customers is a task as difficult as that of cost-effective planning and construction of new facilities. Trying to find treatments for some of these issues represents a major motivation for this thesis. This thesis investigates the problem of how much reinforcement a transmission system requires when a significant proportion of wind generation is integrated into an existing transmission system. A multi-period transmission planning model is developed for determining optimal transmission capacity by balancing amortised transmission investment costs and annual generation costs subject to network security constraints, The model employs the security-constrained DC optimal power flow formulation and applies a solver (DashXpress) to obtain the results of the remaining linear large-scale optimisation problem. This thesis begins by exploring the impact of wind generation on the determination of appropriate levels of system capacity on the transmission network starting from the premise that it is no longer cost effective to invest in sufficient network capacity to accommodate simultaneous peaks from all generators. As such, a significant finding of this study is that conventional and wind generation should share network capacity. Given the acknowledged increase in uncertainty to security of supply due to difficulties in wind generation forecast this thesis also explores the optimal sourcing of generation reserve, and investigates investment in transmission capacity to exploit the cost benefits offered by standing reserve. Finally, the thesis presents and evaluates an alternative associated with transmission operation and investment level of risk and uncertainty by introducing more flexibility to the way the transmission system is operated. Application of Quadrature Boosters and Demand Side as model of corrective control, brings savings in operating costs without jeopardizing the level of system security, enables better utilisation of existing facilities and reduces the demand for new transmission investment

Detection and Localization of Faults in a Regional Power Grid

The structure of power flows in transmission grids is evolving and is likely to change significantly in the coming years due to the rapid growth of renewable energy generation that introduces randomness and bidirectional power flows. Another transformative aspect is the increasing penetration of various smart-meter technologies. Inexpensive measurement devices can be placed at practically any component of the grid. Using model data reflecting smart-meter measurements, we propose a two-stage procedure for detecting a fault in a regional power grid. In the first stage, a fault is detected in real time. In the second stage, the faulted line is identified with a negligible delay. The approach uses only the voltage modulus measured at buses (nodes of the grid) as the input. Our method does not require prior knowledge of the fault type. The method is fully implemented in  R. Pseudo code and complete mathematical formulas are provided

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