Abstract
With the energy transition at sight and the EU renewable energy source integration ambition, the EU-SysFlex project aims at defining a set of advancements in the electric system that drives us towards that direction. With the increasing decentralisation and granularity of the generation facilities, local generation will gain a determinant role in the provision of future local and global systems services. This study presents an overview of a framework for a local market for reactive power control that will be implemented and demonstrated under a real scenario in a Portuguese demo site. The demonstration includes a set of capacitor banks of the distribution system operator (DSO) and two wind farms of a wind power generation operator. This local reactive power market consists of a close to real-time continuous intraday local market managed by the DSO, with 15 min delivery time to increase temporal granularity, and with 7 h delivery horizons with complex bids to allow more flexible assets operation. Market agents can also correct future previously scheduled positions by participating themselves as sellers or buyers of capacitive or inductive reactive power, providing a more flexible framework.

Abstract
In an evolving European power system, with increasing shares of renewable energy sources – a high percentage of which connected to the distribution network – an accurate, reliable and up-to-date representation of the distribution network becomes a key tool for transmission and distribution system operators’ coordination. The Flexibility Hub, under development by INESC TEC and EDP, and in the scope of the European Union-funded project EU-SysFlex, offers a service that delivers an enhanced dynamic equivalent model of the distribution network to the transmission system operator. It is a useful tool for planning purposes to enable a better understanding of how the distribution network will behave under large voltage and frequency disturbances at the transmission level. This study describes the overall concept and the methodology, provides an overview of the data management model adopted to interface the involved agents and depicts some relevant scenarios under consideration for testing.

Abstract
This paper presents an active fault diagnosis (AFD) method with reduced excitation for detection and identification of sensor faults of vehicles in a platoon formation. By introducing a probing signal into the platooning, it will allow an active excitation of the system, reveling a residual component, with the same frequency, that can be explored to obtain a fault identification of specific system faults. A supervisor is introduced to monitor the platoon behavior and activate the auxiliary input whenever the system natural excitation is insufficient for a clear fault diagnosis. This solution will allow the fault diagnosis to behave as active or passive through the adaptive signal provided by the supervisor. A dual Youla-Jabr-Bongiorno-Kucera (YJBK) matrix transfer function, also known as fault signature matrix (FSM) is investigated to get a fault diagnosis. In order to obtain an online identification of specific faults in the system, a Taylor approximation of the FSM is pursued. Computational simulations with a high-fidelity full-vehicle model, provided by CarSim, are carried out to demonstrate the effectiveness of the proposed active approach. A direct comparison between an active and a passive behavior in the same scenario shows that the active fault diagnosis method outperforms the passive approach whenever the dynamic behavior does not provide sufficient excitation. Furthermore, the excitation supervisor is able to significantly reduce the amount of artificial excitation introduced into the system ensuring a more energy efficient active fault diagnosis.

Abstract
This paper addresses the problem of the left inversion of switched linear systems from a diagnostics perspective. The problem of left inversion is to reconstruct the input of a system with the knowledge of its output, whose differentiation is usually required. In the case of thiswork, the objective is to reconstruct the system's unknown inputs, based on the knowledge of its outputs, switching sequence and known inputs. With the inverse model of the switched linear system, a real-time Fault Detection and Isolation (FDI) algorithm with an integrated Fuzzy Logic System (FLS) that is capable of detecting and isolating abrupt faults occurring in the system is developed. In order to attenuate the effects of unknown disturbances and noise at the output of the inverse model, a smoothing strategy is also used. The results are illustrated with an example. The performance of the method is validated experimentally in a DC-DC boost converter, using a low-cost microcontroller, without any additional components.

Abstract
This paper presents theory, a new approach and validation results for fault detection and isolation (FDI) in DC-DC power converters, based on inversion method. The developed method consists on the inversion-based estimation of faults and change detection mechanisms adapted to the power converters context. With the inverse model of a switched linear system, we have designed a real-time FDI algorithm with an integrated fuzzy logic scheme which detects and isolates abrupt changes (faults) at unknown time instants. A smoothing strategy is used to attenuate the effect of unknown disturbances and noise that are present at the outputs of this inverse model. Once the fault event is detected, a dedicated fuzzy-logic-based scheme is proposed to isolate the four types of faults: switch, voltage and current sensor, and capacitor. The performance of the proposed method is verified experimentally to detect and isolate the mentioned faults in the DC-DC boost power converter.

Abstract
The main objective of modeling a switched reluctance machine is to derive a mathematical function to relate the outputs to the inputs. Due to the nonlinear relationship between the variables of torque, flux linkage, current and angular position of the rotor, Switched Reluctance Machine (SRM) modeling is a very challenging task and an open problem. Modeling is usually done in two situations, modeling a single machine, or modeling a set of machines. Each one must fulfill different requirements. This work presents a survey of different SRM modeling approaches, evaluating its advantages and limitations when modeling a single machine or a set of machines.