Compliance of Distribution System Reactive Flows with Transmission System Requirements

Transmission system operators (TSOs) often set requirements to distribution system operators (DSOs) regarding the exchange of reactive power on the interface between the two parts of the system they operate, typically High Voltage and Medium Voltage. The presence of increasing amounts of Distributed Energy Resources (DERs) at the distribution networks complicates the problem, but provides control opportunities in order to keep the exchange within the prescribed limits. Typical DER control methods, such as constant cosϕ or Q/V functions, cannot adequately address these limits, while power electronics interfaced DERs provide to DSOs reactive power control capabilities for complying more effectively with TSO requirements. This paper proposes an optimisation method to provide power set-points to DERs in order to control the hourly reactive power exchanges with the transmission network. The method is tested via simulations using real data from the distribution substation at the Sundom Smart Grid, in Finland, using the operating guidelines imposed by the Finnish TSO. Results show the advantages of the proposed method compared to traditional methods for reactive power compensation from DERs. The application of more advanced Model Predictive Control techniques is further explored.©2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).Part of this work was carried out in the SolarX research project with financial support provided by Business Finland, 2019–2021 (grant No. 6844/31/2018).fi=vertaisarvioitu|en=peerReviewed

Applications of Clustering on Distribution Use-of-System Τariff Design

Εθνικό Μετσόβιο Πολυτεχνείο--Μεταπτυχιακή Εργασία. Διεπιστημονικό-Διατμηματικό Πρόγραμμα Μεταπτυχιακών Σπουδών (Δ.Π.Μ.Σ.) "Επιστήμη Δεδομένων και Μηχανική Μάθηση

An analytical method for optimal allocation of distributed generation in radial distribution networks.

166 σ.Σκοπός της διπλωματικής εργασίας είναι η επίλυση του προβλήματος της βέλτιστης τοποθέτησης μονάδων διεσπαρμένης παραγωγής (ΜΔΠ) με αναλυτική προσέγγιση με σκοπό: (α) την ελαχιστοποίηση των απωλειών ενεργού ισχύος και (β) τη μεγιστοποίηση του οικονομικού κινήτρου του διαχειριστή του δικτύου σε ακτινικά δίκτυα διανομής. Με την τοποθέτηση ΜΔΠ, δεν μειώνονται μόνο οι απώλειες, αλλά επίσης βελτιώνονται οι τάσεις στους ζυγούς του συστήματος. Στην παρούσα εργασία, υλοποιήθηκε αλγόριθμος σε περιβάλλον MATLAB για τον υπολογισμό του βέλτιστου πλήθους, των θέσεων και της ονομαστικής ισχύος των ΜΔΠ. Για την καλύτερη και πιο εύχρηστη εφαρμογή του προγράμματος από το χρήστη δημιουργήθηκε και γραφικό περιβάλλον (GUI). Αρχικά γίνεται ανάλυση ροών φορτίου με τη μέθοδο Newton-Raphson και έπειτα υπολογίζονται οι απώλειες του υπό μελέτη δικτύου. Στη συνέχεια, μέσω των μεθόδων βέλτιστης τοποθέτησης ΜΔΠ υπολογίζονται: το βέλτιστο πλήθος, οι θέσεις (ζυγοί) και η ονομαστική ισχύς των ΜΔΠ. Τέλος, υπολογίζονται οι απώλειες ενεργού ισχύος του δικτύου και το χρηματικό κίνητρο μετά την τοποθέτηση των ΜΔΠ, με τη βοήθεια της ανάλυσης ροών φορτίου. Οι αλγόριθμοι που υλοποιήθηκαν εφαρμόστηκαν σε τέσσερα δίκτυα 4, 10, 33 και 69 ζυγών. Τα αποτελέσματα των μεθόδων της εργασίας παρουσιάζονται, συγκρίνονται και εξάγονται ειδικά και γενικά συμπεράσματα.The current Diploma Thesis deals with the optimal allocation of Distributed Generators (DGs) in radial distribution networks using an analytical approach in order: (a) to maximize the power loss reduction, (b) to maximize the financial incentive. The optimal DG allocation offers, not only active power losses reduction but also an improvement to the voltage profile of the network. In the present diploma thesis, an algorithm was developed in MATLAB environment for calculating the optimal number, location and size of DGs. A graphic user interface (GUI) was created to make the program user-friendly. Initially, a load flow analysis, with Newton-Raphson method, is calculated, and then line losses of the studied network are calculated. After that, using an analytical optimal DG allocation method, the optimal number, location and size of DGs are calculated. Finally, line losses are calculated along with the financial incentive using load flow analysis. The algorithms developed for the current Thesis were tested on four networks with 4, 10, 33 and 69 buses, respectively. The application results are presented compared and application specific conclusions are drawn.Παναγιώτης Γ. Πεδιαδίτη

Synergies between Distribution Use-of-System Tariffs and Local Flexibility Markets

Managing flexibility is an important element of future distribution networks with more than one mechanisms aiming at this goal. Recently proposed methods include variable distribution use-of-system tariffs and flexibility markets. This paper proposes a model for designing variable tariffs under the presence of flexibility products, such as capacity limits offered by aggregators, and studies their synergies. A detailed model of the network power flows is considered and tariffs can have temporal granularity, while retaining simplicity and cost recovery for the system operator. The flexibility products' cost functions are calculated in detail. Case studies illustrate that flexibility products are preferable as a means of motivating flexibility as long as their are priced close to their actual value. As their pricing increases beyond that, tariffs become increasingly preferable

KP-LAB Knowledge Practices Laboratory -- Specifications and Prototype of the Knowledge Repository (V.3.0) and the Knowledge Mediator (V.3.0)

deliverablesThis deliverable reports the technical and research development performed until M36 (January 2009) within tasks T5.2 and T5.4 of WP5 in the KP-Lab project, per the latest Description of Work (DoW) 3.2 [DoW3.2]. The described components are included in the KP-Lab Semantic Web Knowledge Middleware (SWKM) Prototype Release 3.0 software that takes place in M36. This release builds on the Prototype Release 2.0 that was presented in [D5.4]. The present deliverable includes both the specification, as well as the implementation details for the described components. The description of the features of the new functionalities is provided based on the motivating scenarios and the subsequent functional requirements. The focus and the high-level objective of the new services is the provision of improved scalability and modularity properties on the existing services, as well as improved management abilities upon conceptualizations. The implementation of the services is described by providing the related services signatures, their proper way of use, the accepted input parameters, as well as their preconditions and effects. Initially, we describe the Delete Service, which is a Knowledge Repository service allowing the removal of existing namespaces from the repository; such removal includes the deletion of the contents of said namespaces, as well as the deletion of any reference to the namespaces themselves that exists in the repository. This new service enhances SWKM management capabilities upon conceptualizations. Then, the Named Graphs functionality is described, which is a new feature that allows a very flexible modularization of the information found in RDF KBs. We describe in detail the semantics of this feature, as well as the offered capabilities for querying and updating RDF KBs that include modularization information (i.e., information on named graphs) and the implications from their use. Finally, in the context of the Knowledge Mediator, we present the Persistent Comparison Service, which is a variation of the existing (Main Memory) Comparison Service (see M24 release, [D5.3], [D5.4]); unlike the original version, the new service works exclusively on the persistent storage, guaranteeing improved scalability features

Automatic Assessment of Depression Based on Visual Cues: A Systematic Review

International audienceAutomatic depression assessment based on visual cues is a rapidly growing research domain. The present exhaustive review of existing approaches as reported in over sixty publications during the last ten years focuses on image processing and machine learning algorithms. Visual manifestations of depression, various procedures used for data collection, and existing datasets are summarized. The review outlines methods and algorithms for visual feature extraction, dimensionality reduction, decision methods for classification and regression approaches, as well as different fusion strategies. A quantitative meta-analysis of reported results, relying on performance metrics robust to chance, is included, identifying general trends and key unresolved issues to be considered in future studies of automatic depression assessment utilizing visual cues alone or in combination with vocal or verbal cues.Visualization; Affective computing; Monitoring; Europe; Mood; Reliability; Tools; Depression assessment; affective computing; facial expression; machine learning; facial image analysi

Automated Characterization of Mouth Activity for Stress and Anxiety Assessment

International audienceNon-verbal information portrayed by human facial expression, apart from emotional cues also encompasses information relevant to psychophysical status. Mouth activities in particular have been found to correlate with signs of several conditions; depressed people smile less, while those in fatigue yawn more. In this paper, we present a semi-automated, robust and efficient algorithm for extracting mouth activity from video recordings based on Eigen-features and template-matching. The algorithm was evaluated for mouth openings and mouth deformations, on a minimum specification dataset of 640x480 resolution and 15 fps. The extracted features were the signals of mouth expansion (openness estimation) and correlation (deformation estimation). The achieved classification accuracy reached 89.17%. A second series of experimental results, for the preliminary evaluation of the proposed algorithm in assessing stress/anxiety, took place using an additional dataset. The proposed algorithm showed consistent performance across both datasets, which indicates high robustness. Furthermore, normalized openings per minute, and average openness intensity were extracted as video-based features, resulting in a significant difference between video recordings of stressed/anxious versus relaxed subjects

Détection de la dépression par l’analyse de la géométrie faciale et de la parole

International audienceDepression is one of the most prevalent mental disorders, burdening many people world-wide. A system with the potential of serving as a decision support system is proposed, based on novel features extracted from facial expression geometry and speech, by interpreting non-verbal manifestations of depression. The proposed system has been tested both in gender independent and gender based modes, and with different fusion methods. The algorithms were evaluated for several combinations of parameters and classification schemes, on the dataset provided by the Audio/Visual Emotion Challenge of 2013 and 2014. The proposed framework achieved a precision of 94.8% for detecting persons achieving high scores on a self-report scale of depressive symptomatology. Optimal system performance was obtained using a nearest neighbour classifier on the decision fusion of geometrical features in the gender independent mode, and audio based features in the gender based mode; single visual and audio decisions were combined with the OR binary operation.Les troubles d'humeur affectent de nombreuses personnes, la dépression étant la plus répandue. Les méthodes avec la prospective d'aide aux cliniciens dans le diagnostic sont proposées ici, en fonction de la géométrie de l'expression du visage et de la parole. Les approches indépendantes du genre et dépendantes du genre ont été testées, pour différentes combinaisons de caractéristiques visuelles et audio. L'évaluation et la quantification des méthodes développées, pour plusieurs ensembles de paramètres, sont effectuées sur l'ensemble de données fournies par le challenge Emotion Audio / Visual. Un score de F1 de 71.3% a été atteint pour détecter les individus signalant des scores élevés sur le BDI-II. La meilleure configuration du système comprenait un classificateur d'analyse discriminant pour les caractéristiques géométriques dans l'approche indépendante du genre. Facial Geometry and Speech Analysis for Depression Detection (PDF Download Available). Available from: https://www.researchgate.net/publication/317102616_Facial_Geometry_and_Speech_Analysis_for_Depression_Detection [accessed Sep 15, 2017]