Climate change is one of the most dangerous and simultaneously most complex threats humanity has ever faced. The key response to this threat has been an unprecedented strategic shift in the energy sector, known as the energy transition. Electricity powers the modern world and is at the very centre of the energy transition. The shift to sustainable electricity production, transmission, distribution, and consumption is therefore vital. However, such a change brings significant technical challenges that should be addressed. The objective of this research is to uncover and investigate some of the key challenges in this regard and propose solutions for their mitigation.

This thesis largely focuses on two technical aspects and related challenges: power system vulnerability and stability. The emphasis lies on modern power systems, where conventional synchronous generation is increasingly replaced by inverter-based resources (IBRs). The first research objective is to improve the understanding of both system vulnerability and stability, particularly in the context of voltage stability and system strength and their intricate relationship. Relying on this improved understanding, the second objective is to develop advanced and novel evaluation methods and algorithms.

The developed methods form a basis for advanced voltage stability and system strength evaluation of modern power systems. Such an evaluation can play an important role in the overall stability and dynamic security assessment performed by power system operators, with the goal of cutting through the complexity of numerous possible contingencies and operating scenarios. The evaluation automatically identifies the most vulnerable weak grid sections and dangerous operating scenarios that may lead to cascading faults and possible instability. Consequently, once such grid sections and scenarios are observed, more detailed simulations and analyses can be performed by power system stability experts in a much more time-efficient and targeted manner. Subsequently, proactive mitigation measures can be taken to avoid the risk of instability and blackouts.
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This paper deals with the essentials of synchrophasor’s applications for future power systems to increase system reliability and resilience, which have been investigated within a four-year research project. The project has several applications, covering real-time disturbance detection and blackout prevention distributed across multiple work-packages. Firstly, an advanced big-data management platform built in a real-time digital simulation (RTDS) environment is described to support measurement data collection, processing, and sharing among stakeholders. This platform further presents and demonstrates a network-splitting methodology to avoid cascading failures. Online generator coherency identification is another synchrophasor application implemented on the platform, the use of which is demonstrated in the context of controlled network splitting. Using synchrophasors, data-analytics techniques can also identify and classify disturbances in real time with minor human intervention. Therefore, a novel centralized artificial intelligence (AI) based expert system is outlined to detect and classify critical events. Finally, the paper elaborates on developing advanced system resilience metrics for real-time vulnerability assessment of power systems with a high penetration of renewable energy, focusing on increasingly relevant dynamic interactions and system instability risks.@en

As power systems evolve from synchronous to inverter-based generation, short-term voltage stability evaluation plays an increasingly important role. Voltage perturbations become faster and highly variable, exposing systems to much larger risks of cascading faults. Therefore, assessing the severity and origin of potential voltage deviations becomes a critical step in risk-based vulnerability analysis of modern power systems. In this paper, a novel approach that evaluates rapid post-fault voltage deviations for both online and offline short-term instability quantification and classification is investigated. The findings indicate that the approach is intuitive and effective in automatically determining the severity and type of instability. Such an output enables grid operators to anticipate and prioritize potential high-risk events and act with suitable preventive and/or corrective actions. Finally, the paper provides future research directions that deal with the open grid resilience challenges. Particularly, the challenges related to post-disturbance dynamic system strength evaluation are addressed.

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Due to the continuous increase (decrease) in the number of inverter-based (synchronous) generators in modern electrical power systems, the theoretical foundations behind widely used system strength and voltage stability assessment methods require thorough revision. The existing evaluation methods such as the Short-Circuit Ratio (SCR) are often based on simplifications which may produce inaccuracies, particularly when studying weak systems. As a result, a misleading estimation of voltage stability can occur, exposing systems to unnecessary renewables curtailment or other inappropriate remedial actions that may cause partial disruptions or potential instability. This paper provides a rigorous analytical revision of voltage stability assessment to confidently evaluate the maximum power transfer under various operating conditions. Subsequently, the proposed approach is applied as an enhanced method of system strength evaluation. The method is extensively tested on a single-machine-infinite-bus test system. Numerical results show a notably more accurate assessment relative to the common alternative methods.@en

This paper deals with the essentials of synchrophasor applications for future power systems aimed at increasing system reliability and resilience. In this work, several applications are presented, covering real-time disturbance detection and blackout prevention. Firstly, an advanced big-data management platform built in real-time digital simulation (RTDS) environment to support measurement data collection, processing and sharing among stakeholders is described. With this platform, a network splitting methodology to avoid cascading failures is presented and demonstrated, which upon the occurrence of a disturbance successfully isolates the affected part to avoid catastrophic cascade system outage. Online generator coherency identification is another synchrophasor application implemented on the platform, whose use is demonstrated in the context of controlled network splitting. By using synchrophasors, data-analytics techniques can also be used for identifying and classifying different disturbances in real-time with the least human intervention. Therefore, a novel centralized artificial intelligence (AI) based expert system to detect and classify critical events is outlined. Finally, the paper elaborates on the development of advanced system resilience metrics for real-time vulnerability assessment, with a focus on increasingly relevant dynamic interactions between distribution and transmission systems.@en

Door middel van een zo representatief mogelijk rekenmodel voor het middenspanningsnet van de Amsterdamse gebieden Buiksloterham-Zuid/Overhoeks (BZOH), heeft het onderzoeksteam een detailanalyse kunnen uitvoeren naar de verwachte leveringscongestie in dit gebied zoals aangekondigd door Liander op 24 juni 2021. De detailanalyse laat een grootschalige toename in elektriciteitsverbruik in 3 jaar tijd zien, voornamelijk vanwege de stedelijke ontwikkeling in Overhoeks. Uit de beperkte beschikbare data en de resultaten uit het rekenmodel blijkt dat deze toename in vermogensvraag in het middenspanningsnet boven de normale beleidsgrenzen komt totdat de realisatie van de geplande netuitbreiding halverwege 2023 gereed is. De capaciteit is vooral ontoereikend in storings- en/of onderhoudssituaties, ook wel verschakelde toestand genoemd, in bepaalde delen van het netwerk. De studie laat zien dat het effectief verschakelen van het netwerk door Liander een groot deel van het capaciteitsprobleem vermindert. Er bestaan meerdere mogelijkheden om de configuratie van het net aan te passen om zowel in normaal bedrijf als in storings- en/of onderhoudssituaties belastingen beter in het netwerk te kunnen integreren. Een optimale netwerktopologie is daarom noodzakelijk om capaciteit vrij te spelen. In combinatie met een alternatieve reservestelling voor storing en onderhoud (t.o.v. de huidige reservecapaciteit in het netwerk) blijkt dat kritieke netsituaties voorkomen kunnen worden. Om tot een kosteneffectieve en uitvoerbare inschatting te komen voor de dimensionering en locatie van de alternatieve reservestelling, is het detailniveau van netanalyse cruciaal en is voor het toepassen van een alternatieve reservestelling in BZOH een kalibratie van deze studie door Liander noodzakelijk. Daarbij kan de detailanalyse inzichten bieden om in tijden van congestie het overschrijden van de normale beleidsgrenzen omtrent kabelbelasting tijdelijk toe te staan onder de veilige omstandigheden. Op basis van de resultaten uit deze studie zijn deze opties voor reservestelling vanuit energetisch perspectief kansrijk voor BZOH, zonder een verdere uitwerking te bieden voor implementatie.@en

To facilitate the increasing penetration of inverter-based resources, understanding and evaluating system strength becomes one of the central questions for the resilient operation of power systems. However, this is a very challenging and nuanced task, currently without a clear consensus in the industry and academia. This paper provides a comprehensive review of the proposed notion for system strength, followed by a consequent introduction of a novel classification. Furthermore, an exhaustive examination of present system strength evaluation methods is performed. Finally, a critical outlook on remaining and emerging challenges of system strength evaluation is presented, with several key recommendations for future research directions.@en

As power systems evolve from synchronous to inverter-based generation, voltage stability plays an increasingly important role. Voltage perturbations become faster and highly variable, and as such attract the research interest in the field of short-term instability monitoring and evaluation. The digitalization of the power systems provides a higher degree of observability by making use of synchrophasor measurements. The next step of utilizing such measurements by tailoring and applying innovative analytical and data-driven solutions is, however, still at the early development stage. In this paper, a novel approach that utilizes rapid post-fault voltage deviations for short-term instability quantification is investigated. The findings indicate that the approach is intuitive and effective. Finally, the paper discusses future research directions, enabled by the presented methodology, that deal with grid resilience challenges. Particularly, those related to post-disturbance system strength evaluation, as well as the real-time short-term instability evaluation and prediction, are addressed.@en

The number of Distributed Energy Resources (DER) and dynamic loads is increasing rapidly in modern power systems. Their aggregated effects on power grid dynamics are, however, still insufficiently explored. It is expected that distribution-transmission interactions will be more pronounced in the future, resulting in a stronger need to analyse such effects. One of the emerging issues in modern systems’ distribution-transmission interactions is short-term voltage stability (STVS), which at present receives relatively low attention among the researchers. This paper utilizes advanced load and DER models in a large-system study, intending to determine the relationship between various distribution system specifics and the bulk power system STVS. Based on a developed heuristic method that generates a big data set by performing an extensive number of simulations, it is shown how the dynamic load and DER interact with each other in terms of STVS, and what load and DER amounts and types are beneficial or detrimental to modern systems. The study improves the understanding of modern distribution-transmission interactions related to STVS and emphasizes the importance of more accurate future modelling and analyses.

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The possibility to monitor and evaluate power system stability in real-time is in growing demand. Whilst most stability-related studies focus on long-term voltage stability and frequency stability, very little attention is given to the issue of short-term (voltage) instability. In this paper, the most common evaluation methods present in the literature are summarized, with a focus on their applicability to modern power systems with a large amount of renewable energy integration. The paper presents a first-of-a-kind structured review of this topic. We find that all existing methods have noteworthy limitations that necessitate further improvements. Additionally, the need of having an inclusive short-term instability prediction method is demonstrated, due to strong interactions between various short-term instability mechanisms. These findings provide a good foundation for further research and advancement in the field of real-time stability monitoring.

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Renewable energy sources (RES) penetrate power grids at all voltage levels. A large number of RES units are connected to medium-voltage (MV) and low-voltage (LV) levels resulting in a significant share of overall generation. Therefore, the dynamic behavior of such distribution grids should be thoroughly examined. The goal of this paper is to show how various changes in the composition of the dynamic power flows interact with Low-Voltage Ride Through (LVRT) requirements, and how they affect the very important aspect of the RES-penetrated grids – voltage stability. The analysis is performed on a selected network, which is modeled with real grid data. The concluding concepts, however, are applicable for any distribution grid topology with a large number of distributed energy resources (DER). The results show essential grid details that should be modeled more precisely. This paper also addresses the level of complexity needed to obtain accurate results. Models are generally always imperfect and therefore, having more detailed data for a specific study is of the uttermost importance.@en