Abstract

Abstract
Network human operators' decision-making during grid outages requires significant attention and the ability to perceive real-time feedback from multiple information sources to minimize the number of control actions required to restore service, while maintaining the system and people safety. Data-driven event and alarm management have the potential to reduce human operator cognitive burden. However, the high complexity of events, the data semantics, and the large variety of equipment and technologies are key barriers for the application of Artificial Intelligence (AI) to raw SCADA data. In this context, this paper proposes a methodology to convert a large volume of alarm events into data mining terminology, creating the conditions for the application of modern AI techniques to alarm data. Moreover, this work also proposes two novel data-driven applications based on SCADA data: (i) identification of anomalous behaviors regarding the performance of the protection relays of primary substations, during circuit breaker tripping alarms in High Voltage (HV) and Medium Voltage (MV) lines; (ii) unsupervised learning to cluster similar events in HV line panels, classify new event logs based on the obtained clusters and membership grade with a control parameter that helps to identify rare events. Important aspects associated with data handling and pre-processing are also covered. The results for real data from a Distribution System Operator (DSO) showed: (i) that the proposed method can detect unexpected relay pickup events, e.g., one substation with nearly 41% of the circuit breaker alarms had an 'atypical' event in their context (revealed an overlooked problem on the electrification of a protection relay); (ii) capability to automatically detect and group issues into specific clusters, e.g., SF6 low-pressure alarms and blocks with abnormal profiles caused by event time-delay problems.

Abstract
This paper proposes the use of a Gaussian window on the array factor as an interference mitigation method, aiming to avoid the computational complexity of the MVDR algorithm at the cost of a slight performance reduction. We show that by optimizing the parameters of the Gaussian window, it is possible to effectively mitigate the interfering signal if it is received within a certain angular range from the desired signal, while being still effective beyond that range. Finally, we show that the effectiveness of this approach is maintained across the full frequency reception range of the Ka-band, and confirm its validity using 8 × 8 and 16 × 16 array sizes. © 2022 IEEE.

Abstract
5G network technology is considered one of the driving forces behind various societal changes. Among multiple uses, it offers Telesurgery. In situations where the patient needs specialized surgery, but there are no conditions to be transported to where the surgical intervention can be performed, Telesurgery allows access to the procedure with all the security that 5G network technology offers. The Autonomous Region of the Azores (ARA) is considered an outermost region which is an integral part of the EU (despite the thousands of kilometres that separate it from the European continent). Therefore, the EU law applies to these regions with all rights and duties associated. The Support Service to the Displaced Patient (SADD) accompanies annually and under normal conditions an average of more than 1500 patients from the Azores. They travel to the mainland for health reasons. This scenario is applied across islands, where an average of 550 patients moved annually from islands without a hospital to islands with a hospital. As a result, health costs rise in this Region. This paper will use the survey research methodology since it is the most appropriate method when we want to obtain answers/data that express opinions, customs or characteristics of a certain target audience. Therefore, a mixed mode will be used, namely interviews and questionnaires, having as scientific target areas medicine and engineering, in the specialities of gastroenterology and telecommunications, to support the research questions. This paper aims to present research on the viability of Telesurgery in the Autonomous Region of the Azores, supported by the 5G network, as an alternative for travelling patients.

Abstract
The deployment of smart metering technologies in the low voltage (LV) grid created conditions for the application of data-driven monitoring and control functions. However, data privacy regulation and consumers' aversion to data sharing may compromise data exchange between utility and customers. This work presents a data-driven method, based on smart meter data, to estimate linear sensitivity factors for three-phase unbalanced LV grids, which combines a privacy-preserving protocol and varying coefficients linear regression. The proposed method enables centralized and peer-to-peer learning of the sensitivity factors. Potential applications for the sensitivity factors are demonstrated by solving voltage violations or computing operating envelopes in a LV grid without resorting to its network topology or electrical parameters.

Abstract
Bidirectional electric vehicle charging stations (EVSE) offer new business models for private users and companies such as Demand Response. Even if first standards for smart charging (ISO 15118, OCPP) are established, no commercial turnkey solution for the integration of a vehicle to grid (V2G) charging station into a smart prosumer household exists yet. This study shows a possible concept for the integration of a V2G charger for a vehicle to home (V2H) use case. A smart controller for a prosumer household is developed allowing the interconnection of different types of electrical equipment like a V2G charger, a photovoltaic system for electricity generation, a heat pump for heating. Therefore, different interfaces such as Modbus TCP, Modbus RTU, OCPP, HTTP are used. An algorithm is developed to charge the vehicle at low electricity prices or at times of overproduction of the PV system respective to discharge the car at high electricity prices or times of no PV production. The modular concept allows realizing the solution as a cloud-based service which can be applied to energy communities. © 2022 IEEE.