A two-level Probabilistic Risk Assessment of cascading failures leading to blackout in transmission power systems

In our society, private and industrial activities increasingly rest on the implicit assumption that electricity is available at any time and at an affordable price. Even if operational data and feedback from the electrical sector is very positive, a residual risk of blackout or undesired load shedding in critical zones remains. The occurrence of such a situation is likely to entail major direct and indirect economical consequences, as observed in recent blackouts. Assessing this residual risk and identifying scenarios likely to lead to these feared situations is crucial to control and optimally reduce this risk of blackout or major system disturbance. The objective of this PhD thesis is to develop a methodology able to reveal scenarios leading to a blackout or a major system disturbance and to estimate their frequencies and their consequences with a satisfactory accuracy.A blackout is a collapse of the electrical grid on a large area, leading to a power cutoff, and is due to a cascading failure. Such a cascade is composed of two phases: a slow cascade, starting with the occurrence of an initiating event and displaying characteristic times between successive events from minutes to hours, and a fast cascade, displaying characteristic times between successive events from milliseconds to tens of seconds. In cascading failures, there is a strong coupling between events: the loss of an element increases the stress on other elements and, hence, the probability to have another failure. It appears that probabilistic methods proposed previously do not consider correctly these dependencies between failures, mainly because the two very different phases are analyzed with the same model. Thus, there is a need to develop a conceptually satisfying probabilistic approach, able to take into account all kinds of dependencies, by using different models for the slow and the fast cascades. This is the aim of this PhD thesis.This work first focuses on the level-I which is the analysis of the slow cascade progression up to the transition to the fast cascade. We propose to adapt dynamic reliability, an integrated approach of Probabilistic Risk Analysis (PRA) developed initially for the nuclear sector, to the case of transmission power systems. This methodology will account for the double interaction between power system dynamics and state transitions of the grid elements. This PhD thesis also introduces the development of the level-II to analyze the fast cascade, up to the transition towards an operational state with load shedding or a blackout. The proposed method is applied to two test systems. Results show that thermal effects can play an important role in cascading failures, during the first phase. They also show that the level-II analysis after the level-I is necessary to have an estimation of the loss of supplied power that a scenario can lead to: two types of level-I scenarios with a similar frequency can induce very different risks (in terms of loss of supplied power) and blackout frequencies. The level-III, i.e. the restoration process analysis, is however needed to have an estimation of the risk in terms of loss of supplied energy. This PhD thesis also presents several perspectives to improve the approach in order to scale up applications to real grids.Doctorat en Sciences de l'ingénieurinfo:eu-repo/semantics/nonPublishe

Probability of failure of overloaded lines in cascading failures

Power grids are vulnerable to cascading failures, as shown by previous blackouts or major system disturbances. Line outages due to overload are often the main contributors to the cascading failures leading to these undesired situations. Indeed, the more a line is overloaded, the larger is its sagging, and hence the probability that it will be tripped. It is necessary to quantify in a realistic way the probability of trip as a function of the load in order to compute a good estimation of the frequency of dangerous cascading outages. Several models were proposed for this purpose, but none of them is backed up by empirical evidence or detailed analysis. This paper studies factors that could affect the probability of trip as a function of load, and it computes this probability for two different test systems using a temperature simulation based methodology, called dynamic PRA level-I analysis. This paper then compares existing modelings of this probability to these results. This comparison shows that all modelings used in the literature are not always convenient. We finally propose a simple model that can be adopted in probabilistic risk assessment of cascading failures.SCOPUS: ar.jinfo:eu-repo/semantics/publishe

Offsite power reliability assessment for nuclear power plants: An application of dynamic reliability to power systems

The safety of nuclear power plants (NPPs) significantly relies on the reliability of offsite power. In particular, the loss of offsite power (LOOP) event is an important contributor to the total residual risk at NPPs. A particular category of LOOP events is due to the occurrence of failures in the transmission power system to which the NPP is connected (grid-related LOOP event). In such kind of events, the coupling between the dynamics of the power system and the failure of protection systems plays a crucial role. In that respect, a probabilistic risk/safety assessment (PRA/PSA) of grid-related LOOP events must thus rely on dynamic reliability methodologies. A PRA/PSA methodology based on Monte Carlo (MC) simulation is developed for such a purpose. The effectiveness of the method is demonstrated on a test system.SCOPUS: ch.binfo:eu-repo/semantics/publishe

Unsupervised learning procedure for NILM applications

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Probabilistic Security Analysis of Optimal Transmission Switching

Optimal transmission switching (OTS) optimizes simultaneously the generation dispatch and the topology of a power system. It has been shown that taking some transmission lines out of service can significantly reduce the operating cost of the system while respecting the traditional deterministic $N-1$ security criterion of operational reliability. However, topology modifications could adversely affect probabilistic security metrics. The operational reliability of a power system can be translated into a cost by multiplying the expected energy not served by the value of lost load. This paper therefore explores whether it is possible to maintain a positive economic balance with OTS when considering not only the cost of generation but also the expected socio-economic cost of disruptions in the supply. This is done in two steps: the computation of an $N-1$ secure OTS and then the calculation of a probabilistic estimate of the operational reliability of the OTS solution. Based on the results obtained with two test systems, it is shown that OTS tends to significantly degrade probabilistic measures of security. It is thus not obvious that OTS can lead to a positive economic balance, even when $N-1$ security is enforced. Consequently, a probabilistic security analysis should be performed before implementing an OTS solution.SCOPUS: ar.jinfo:eu-repo/semantics/publishe

Specific and generic unsupervised algorithms for NILM applications

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Dynamic probabilistic risk analysis of the fast cascade phase of large disturbances in power system

Power systems have experienced wide-area disturbances in the last decades, including large blackouts in the U.S. and Europe that impacted millions of customers. According to previous blackout analysis, the development of a cascading event leading to a blackout can be split in two phases. In an initial "slow cascade" phase, an initiating contingency (e.g. a line trip), though not supposed to challenge the electrical stability of the grid because of the N-1 security criterion, triggers a thermal transient developing on characteristic times much longer than the electrical time constants. This transient increases significantly the likelihood of additional contingencies. The loss of additional elements can then trigger an electrical instability. This is at the origin of the subsequent "fast cascade" phase, where a rapid succession of events can possibly lead the system to blackout. This paper is devoted to the study of the fast cascade phase of power system large disturbances. Dynamic Probabilistic risk assessment (PRA) has been developed, mostly in nuclear engineering, for identifying dangerous accident scenarios, while capturing the interaction between the dynamic evolution of a system in transient conditions and the occurrence of events along an accident sequence. Discrete dynamic event trees (DDET) is the core of the scheme used in this research. Misoperation of distance protection systems, involved in the propagation of disturbances, is integrated into the approach to provide more trustworthy results. The objective of this paper is the identification of dangerous scenarios leading to blackout in the fast cascade phase and the estimation of their frequency, using dynamic PRA. The methodology is applied to a test grid and results are analyzed.info:eu-repo/semantics/publishe