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
Currently, the transmission system operators (TSOs) from Portugal and Spain do not procure a frequency containment reserve (FCR) through market mechanisms. In this context, a virtual power plant (VPP) that aggregates sources, such as wind and solar power and hydrogen electrolyzers (HEs), would benefit from future participation in this ancillary service market. The methodology proposed in this paper allows for quantifying the revenues of a VPP that aggregates wind and solar power and HEs, considering the opportunity costs of these units when reserving power for FCR participation. The results were produced using real data from past FCR market sessions. Using market data from 2022, a VPP that aggregates half of the HEs and is expected to be connected in the country by 2025 will have revenues over EUR 800k, of which EUR 90k will be HEs revenues.

Abstract
Frequency Containment Reserve (FCR) Cooperation is a European effort to integrate several countries in an integrated international electricity market platform for FCR procurement. In this market, Balancing Service Providers (BSPs) are on the supply side and Transmission System Operators (TSOs) on the demand side. This paper proposes a novel settlement scheme for sharing costs among TSOs; it proposes no changes to existing market clearing rules or to the existing settlement of the BSPs' revenues. It is shown that the current TSO settlement scheme is an inequitable mechanism that originates negative costs for some TSOs in specific conditions, which are extensively discussed. The proposed TSO settlement scheme overcomes these inequities. In the proposed scheme, TSOs begin paying the local BSPs for the cleared bids needed locally, and the remaining imports are calculated in a subsequent step. Doing so avoids using the so-called import/export costs, which are demonstrated to be the source of the inequities in the current scheme. It is shown that if the proposed pricing scheme had been adopted from July 2019 to December 2022, all TSOs would have been affected. Specifically, the most negatively impacted TSO would have its accumulated costs increased by 16% and the most positively impacted TSO would have its accumulated cost decreased by 32%. The inequities of the current mechanism amount to more than 50 Me or 7.4% of the total accumulated costs. Although the proposed mechanism is tested here under the FCR Cooperation, it can be applied to other markets where the rules allow different local settlement prices.

Abstract
The environmental impact on the energy sector has become a significant concern, necessitating the implementation of Home Energy Management Systems (HEMS) to enhance the energy efficiency of buildings, reduce costs and greenhouse gas emissions, and ensure user comfort. This paper presents a novel approach to provide optimal day-ahead energy management plans in smart homes with Photovoltaic/Thermal (PVT) systems, aiming to achieve a balance between energy cost and user comfort. This multi-objective problem employs the Non-dominated Sorting Genetic Algorithm III as the optimization algorithm and the Nonlinear Auto-regressive with External Input to forecast the day-ahead meteorological variables, which serve as inputs to predict the PVT electrical and heat production in the thermal resistance model. The HEMS benefits from the time-of-use tariff due to the flexibility provided by the energy storage from a battery bank and a boiler. Furthermore, it performs a load scheduling for 10 controllable loads based on three feature parameters to characterize occupant behavior. A study case analysis revealed a cost reduction of approximately 66% in the solution close to the knee of the Pareto curve (S3 solution). The environmental impact on the energy sector has become a The PVT heat production was sufficient to meet the thermal demand of the showers. The proposed hybrid battery management model effectively eliminated the export of electricity to the grid, reducing consumption during peak periods and the maximum peak demand.

Abstract
This paper investigates the stability of a converter-dominated islanded power system when the island’s battery energy storage converters are operated in different control modes (Grid Forming and Grid Following) and combined with different volumes of synchronous compensation. The study is conducted in a realistic simulation model of the future Madeira island, where no thermal generation is present, and the share of converter-based Renewable Energy Sources is large (75 to 80 % of instantaneous penetration). The impact of the different combinations of synchronous condensers and BESS converter control modes on the system stability is evaluated using a stability index-based approach that accounts for multiple operation scenarios. In this procedure, the system’s dynamic response to the reference disturbances (short-circuits in the Transmission and Distribution Network) is obtained via RMS dynamic simulation and is then analyzed to extract two stability indices (Nadir and Rocof). Such indices are computed for the synchronous generator speed and the grid electrical frequency (measured in different points using a PLL) and are later used as the basis for discussion and conclusion drawing. © Energynautics GmbH.

Abstract
As one of the functions integrating energy management systems, state estimation (SE) is instrumental in monitoring power networks, allowing the best possible use of energy resources. It plays a decisive role in debugging if sufficient data are available, ruined if not. Criticality analysis (CA) integrates SE as a module in which elements of the estimation process-taken one-by-one or grouped (tuples of minimal multiple cardinality)-are designated essential. The combinatorial nature of extensive CA (ExtCA), derestricted from identifying only low-cardinality critical tuples, characterizes its computational complexity and imposes defiant limits in implementing it. This paper presents the methodology for ExtCA and compares algorithms to find an efficient solution for expanding the boundaries of this analysis problem. The algorithms used for comparison are one sequential Branch&Bound (a well-known paradigm for combinatorial optimization recently used in ExtCA) and two new parallels implemented on the central processing unit (CPU) and the graphics processing unit (GPU). The conceived parallel architecture favors evaluating massive combinations of diverse cardinality measuring unit (MU) tuples in ExtCA. The acronym MU refers to the aggregate of devices deployed at substations, such as a remote terminal unit, intelligent electronic device, and phasor measurement unit. The numerical results obtained in the paper show significant speed-ups with the novel parallel GPU algorithm, tested on different and real-scale power grids. Since, the visualization of the ExtCA results is still not a well-explored field, this work also presents a novel way of graphically depicting spots of weak observability using MU-oriented ExtCA.