Synchrophasor Data Analytics for Control and Protection Applications in Smart Grids

RESUME Des reseaux intelligents sont des reseaux d’energie fortement distribues ou les technologies d’energie et des services sont integres avec des informations, des communications et controlent des technologies. Puisque les sources d’energie renouvelable deviennent plus efficaces et rentables, les reseaux intelligents peuvent livrer la puissance propre, durable, securitaire, et fiable aux consommateurs. Cependant, l’utilisation rapide de sources d’energie renouvelable provoque des defis techniques en termes de surveillance, le controle et la protection des reseaux electriques. En fait, l’energie renouvelable implique les phenomenes qui sont naturellement stochastiques comme la lumiere du soleil et le vent. Donc, les reseaux intelligents devraient etre capables de surveiller et repondre aux changements tant dans fournisseur d’energie que dans la demande. L’evolution des reseaux electriques provoque aussi le deploiement de nombreuses unites de mesure sans precedent et d’intelligents appareils de mesure. En vertu des systemes de communications, les signaux en temps reel et les donnees peuvent etre echanges entre les composants des reseaux intelligents. Le flux de donnees en temps reel fournit une occasion unique pour des applications axees sur les donnees et des outils pour demultiplier la modernisation de reseaux et la resilience. Les unites de mesure de phaseur sont les dispositifs specialises qui acquierent le phaseur synchronise (synchrophasor) des donnees des reseaux electriques. L’analytique de donnees Synchrophasor peut potentiellement etre plus performant que des methodes traditionnelles en termes de prise de decisions. Specifiquement, l’analytique de donnees est des approches qualitatives/quantitatives et les algorithmes qui rassemblent et traitent des donnees pour en fin de compte ameliorer la conscience situationnelle dans des reseaux electriques. Motive par ce fait, cette these presente des solutions viables pour l’analytique de donnees synchrophasor dans le but d’ameliorer la surveillance, le controle et la protection de reseaux de distribution. La these se concentre sur trois fonctionnalites qui sont portees de base sur l’analytique de donnees synchrophasor: Detection de perturbation centralisee, surveillance de production decentralisee (PD) et la protection “backup” coordonnee. L’objectif de surveillance de perturbation est de realiser la detection rapide et fiable de tension/des deviations de frequence qui affectent la stabilite de reseau. La surveillance de PD est liee a la detection de la presence/absence de ressources energetiques pour la gestion du flux de puissance. ----------ABSTRACT Smart grids are highly distributed energy networks where energy technologies and services are integrated with information, communications and control technologies. As renewable energy sources are becoming more efficient and cost–effective, the smart grids can deliver safe, clean, sustainable and reliable power to consumers. However, the rapid utilization of renewable energy sources brings about technical challenges in terms of monitoring, control, and protection of power systems. In fact, renewable energy involves phenomena which are naturally stochastic such as sunlight and wind. Therefore, the smart grids should be capable of monitoring and responding to changes in both power supply and demand. The evolution of the power systems also gives rise to deployment of unprecedented number of measurement units and smart meters. By virtue of communications systems, real-time signals and data can be exchanged between components of the smart grids. The flow of real-time data provides a unique opportunity for data-driven applications and tools to leverage grid modernization and resiliency. Phasor measurement units are specialized devices that acquire synchronized phasor (synchrophasor) data from the power systems. Synchrophasor data analytics can potentially outperform traditional methods in terms of decision making. Specifically, data analytics are qualitative/quantitative approaches and algorithms that collect and process data to ultimately improve situational awareness in the power systems. Motivated by this fact, this thesis presents viable solutions for synchrophasor data analytics with the aim of improving monitoring, control and protection of power distribution grids. The thesis focuses on three functionalities that are carried out based on synchrophasor data analytics: Centralized disturbance detection, monitoring of distributed generation (DG) systems, and coordinated backup protection. The objective of disturbance monitoring is to achieve fast and reliable detection of voltage/frequency deviations that affect the network stability. The DG monitoring is concerned with detecting presence/absence of energy resources for management of the flow of power. Disturbance and DG monitoring tools pave the way for adaptive backup protection of active distribution networks. The adaptive backup protection scheme ensures the post-fault stability by detecting line faults within a permissible tolerance time. The coordination between control and backup protection systems leads to fast recovery of voltage/frequency and minimizes power outage. The efficacy and reliability of the developed methods and algorithms are validated by extensive computer simulations based on different benchmarks.