S. Herraiz

Opportunities and challenges for smart power restoration and reconfiguration smart decisions with smart grids

Smart grids bring new opportunities but also new challenges for designing and implementing restoration and reconfiguration algorithms. The efficiency of power restoration and network reconfiguration can be improved with the deployment of ICT technologies in smart grids. Protecting, monitoring, controlling, and metering the distribution power network will benefit from high interconnectivity and interoperability among multiple devices and an efficient exploitation of available information. Moreover, artificial intelligence and data mining techniques can also have a positive contribution in that sense. Nevertheless, new restoration techniques should also take into account power quality and network stability. They should also take full advantage of the possibility to change the topology, the increase of available data, and the communications and processing capability. More efforts should be devoted to designing powerful AI techniques. Our traditional vision of power distribution networks has also to be changed. Distribution network, power restoration, network reconfiguration, smartgrid, smart grid, intelligent grid, distributed generation, CBR, heuristic, metaheuristic, IED, power meter, islanding, power quality

Self-healing for smart grids: Problem formulation and considerations

Self-healing is capacity of the network to restore automatically the network when an outage occurs. Smart grids makes power restoration on the one hand more complex due to distributed generation, distributed storage and mobile loads (electrical vehicles), but on the other hand the observability is improved with the introduction of smart meters and IEDs (intelligent electronic devices). The relevant differences between traditional distribution networks and smart grids for power restoration are reviewed. This paper formulates the problem of self-healing in smart grids. Furthermore, the network features and constraints are explained. Moreover, the restoration goals are given. In short the contribution of this paper are: a definition of self-healing, the formalization of this concept (graph, constraints, goals), a description of the relevant smart grid features and discussion of the complexity of the problem.

Sequence pattern discovery of events caused by ground fault trips in power distribution systems

In this paper, sequences of events registered in power distribution systems are analysed using pattern sequence discovery algorithms. The events considered in the study are basically voltage sags generated by homopolar faults and registered by power quality monitors installed in the secondary of transformers in distribution substations. The events registered in a measuring point have associated the time of occurrence, and the list of increasing-time ordered events corresponds to a sequence. The aim is to discover existing temporal patterns, or episodes, that occur sufficiently often along that sequence. Sequence pattern discovery algorithms are used to discover those frequent episodes. Then, frequent episodes are used to obtain association rules that describe relationships between time spans of successive events. The method has been tested with data from gathered in different substations.

Fault-pattern discovery in sequences of voltage sag events

A pattern discovery approach applied to sequences of voltage sags is proposed for fault modeling and failure prediction. It is assumed the existence of some failures that are the result of accumulated stress produced by overcurrents during previous faults or the existence of pattern sequences produced by the reclosing of the protection system in presence of a fault. So there may exist relationships between events. Events registered in a real power distribution system are analyzed to search those fault patterns. The events considered in this study are voltage sags generated by homopolar faults and registered by power quality monitors installed in the secondary of transformers in distribution substations. The ordered list (according to their time of ocurrence) of events corresponds to a sequence, and magnitude and duration are the attributes considered to describe the events. The aim of this work is to find patterns in a sequence of voltage sags that allow to recognize relationships between different types of sags occurred along time.

Classification of sags according to their origin based on the waveform similarity

A statistical method for classification of sags their origin downstream or upstream from the recording point is proposed in this work. The goal is to obtain a statistical model using the sag waveforms useful to characterise one type of sags and to discriminate them from the other type. This model is built on the basis of multi-way principal component analysis an later used to project the available registers in a new space with lower dimension. Thus, a case base of diagnosed sags is built in the projection space. Finally classification is done by comparing new sags against the existing in the case base. Similarity is defined in the projection space using a combination of distances to recover the nearest neighbours to the new sag. Finally the method assigns the origin of the new sag according to the origin of their neighbours.

Application for fault location in electrical power distribution systems

Fault location has been studied deeply for transmission lines due to its importance in power systems. Nowadays the problem of fault location on distribution systems is receiving special attention mainly because of the power quality regulations. In this context, this paper presents an application software developed in Matlabtrade that automatically calculates the location of a fault in a distribution power system, starting from voltages and currents measured at the line terminal and the model of the distribution power system data. The application is based on a N-ary tree structure, which is suitable to be used in this application due to the highly branched and the non- homogeneity nature of the distribution systems, and has been developed for single-phase, two-phase, two-phase-to-ground, and three-phase faults. The implemented application is tested by using fault data in a real electrical distribution power system.

Estimation of zero-sequence impedance of undergrounds cables for single-phase fault location in distribution systems with electric arc

This paper focus on the problem of locating single-phase faults in mixed distribution electric systems, with overhead lines and underground cables, using voltage and current measurements at the sending-end and sequence model of the network. Since calculating series impedance for underground cables is not as simple as in the case of overhead lines, the paper proposes a methodology to obtain an estimation of zero-sequence impedance of underground cables starting from previous single-faults occurred in the system, in which an electric arc occurred at the fault location. For this reason, the signal is previously pretreated to eliminate its peaks voltage and the analysis can be done working with a signal as close as a sinus wave as possible.

Analysis of the influence of weather factors on outages in Spanish distribution networks

The origin of outages occurring in a power distribution network are highly related with the weather conditions existing during its apparition. Wind, rain and lightnings usually are the trigger causes of power network outages, hence the analysis of the relationship between weather and network outage information plays an important role for forecasting the impact of future weather conditions in the power distribution network. In this paper, weather information and distribution-network outages collected during three years are studied and statistically analyzed. From the analysis some useful relationships between weather conditions and network outages were extracted.

Analysis of frequent episodes in sequences of incidents collected in power distribution systems

Power distribution incidents collected by the electric utility through their customer service centers and incident management systems are analyzed systematically in this work. An incident is defined by the actions carried out by the utility to return the system to its normal operation when a failure occurrs. A sequence of incidents is a set of dated incidents recorded in a region or a network during a period of time, but only some subsets of them are of interest, either because they present similar features or because they are related in a way that allows them to be considered together (timing, periodicity, etc.). These subsets of significant incidents in a sequence are called episodes and are instances of possible patterns that define the behaviour of the system. The analysis is oriented to extract useful information from sequences of historical data to recognize relevant episodes that show a pattern of behaviour which could be useful to forecast future incidents or assist planning and operation. With this goal, the authors evaluate the use of a pattern discovery algorithm in sequences of incidents gathered in a network as part of the case study. Since the incidents can occur by random factors not all the frequent episodes that can be found are relevant. Then, it is proposed a methodology based on set theory to choose the relevant episodes which are especially useful to recognize outstanding episodes in sequences that have high randomness, which is the case of sequences of incidents in electrical networks.

Study of voltage sag effects on three-phase transformers

This paper studies the effects of symmetrical and unsymmetrical voltage sags on a three-phase three-legged transformer and a three-phase transformer bank by considering that fault clearing is produced instantaneously in all the phases. The transformer model includes saturation and the parameters have been obtained from experimental measurements. The influence of the sag type, depth, duration and initial point-on-wave on the inrush current peak value is studied. The current peak has periodical dependence on sag duration and the initial point-on-wave, and a linear dependence on depth. Unsymmetrical sags can result in current peaks as high as those of symmetrical sags.