Abstract
The decarbonization of the economy and the increasing integration of renewable energy sources into the generation mix are bringing new challenges, requiring novel technological solutions in the topic of smart grids, which include smart transformers and energy storage systems. Additionally, power quality is a vital concern for the future smart grids; therefore, the continuous development of power electronics solutions to overcome power quality problems is of the utmost importance. In this context, this article proposes a novel three-phase multiobjective unified power quality conditioner (MO-UPQC), considering interfaces for solar PV panels and for energy storage in batteries. The MO-UPQC is capable of compensating power quality problems in the voltages (at the load side) and in the currents (at the power grid side), while it enables injecting power into the grid (from the PV panels or batteries) or charging the batteries (from the PV panels or from the grid). Experimental results were obtained with a three-phase four-wire laboratory prototype, demonstrating the feasibility and the large range of applications of the proposed MO-UPQC.

Abstract
In isolated power systems with very high instantaneous shares of renewables, additional inertia should be used as a complementary resource to battery energy storage systems (BESSs) for improving frequency stability, which can be provided by synchronous condensers (SCs) integrated into the system. Therefore, this paper presents a methodology to infer the system dynamic security, with respect to key frequency indicators, following critical disturbances. Of particular interest is the evidence that multiple short-circuit locations should be considered as reference disturbances regarding the frequency stability in isolated power grids with high shares of renewables. Thus, an artificial neural network (ANN) structure was developed, aiming to predict the network frequency nadir and Rate of Change of Frequency (RoCoF), considering a certain operating scenario and disturbances. For the operating conditions where the system frequency indicators are violated, a methodology is proposed based on a gradient descent technique, which quantifies the minimum amount of additional synchronous inertia (SCs which need to be dispatch) that moves the system towards its dynamic security region, exploiting the trained ANN, and computing the sensitivity of its outputs with respect to the input defining the SC inertia.

Abstract
Isolated power systems with high shares of renewables can require additional inertia as a complementary resource to assure the system operation in a dynamic safe region. This paper presents a methodology for the day-ahead Unit Commitment/ Economic Dispatch (UC/ED) for low-inertia power systems including dynamic security constraints for key frequency indicators computed by an Artificial Neural-Network (ANN)-supported Dynamic Security Assessment (DSA) tool. The ANN-supported DSA tool infers the system dynamic performance with respect to key frequency indicators following critical disturbances and computes the additional synchronous inertia that brings the system back to its dynamic security region, by dispatching Synchronous Condensers (SC) if required. The results demonstrate the effectiveness of the methodology proposed by enabling the system operation within safe frequency margins for a set of high relevance fault type contingencies while minimizing the additional costs associated with the SC operation.

Abstract
This paper evidences the ability of a VSM-based grid-forming to mitigate stability problems of different classes, raising a special concern towards the importance of its location in systems with large converter-interfaced renewable energy systems. Within this context, a multi-class stability assessment, that pillars on the simulation of different nature disturbances and in the subsequent evaluation of a 4 index set, was performed. Such analysis was carried out on a modified version of the IEEE39 Test System, using DigSILENT Power Factory as the simulation engine.

Abstract
The operation of isolated power systems with 100% converter-based generation requires the integration of battery energy storage systems (BESS) using grid-forming-type power converters. Under these operating conditions, load dynamics influences the network frequency and voltage following large voltage disturbances. In this sense, the inclusion of induction motor (IM) load models is required to be properly considered in BESS power converter sizing. Thus, this paper presents an extensive sensitivity analysis, demonstrating how load modeling affects the BESS power converter capacity when adopting conventional control strategies while aiming to assure the successful recovery of all IM loads following a network fault. Furthermore, this work highlights that generators with converter interfaces can actively contribute to mitigate the negative impacts resulting from IM loads following a network fault. Thereby, two distinct control strategies are proposed to be integrated in the power electronic interfaces of the available converter-based generators: one to be adopted in grid-following converters and another one suitable for grid-forming converters. The proposed control strategies provide an important contribution to consolidating insular grid codes, aiming to achieve operational scenarios accommodating 100% penetration of converter-based generation with a significative percentage of the IM load composition without resorting to a significative increase in BESS power converter sizing.