Abstract
This study explores models for synthetic data generation of time series. In order to improve the achieved results, i.e., the data generated, new ways of improvement are explored and different models of synthetic data generation are compared. The model addressed in this work is the Generative Adversarial Networks (GANs), known for generating data similar to the original basis data through the training of a generator. The GANs are applied using the datasets of Quinta de Santa Barbara and the Pinhao region, with the main variables being the Average temperature, Wind direction, Average wind speed, Maximum instantaneous wind speed and Solar radiation. The model allowed to generate missing data in a given period and, in turn, enables to analyze the results and compare them with those of a multiple linear regression method, being able to evaluate the effectiveness of the generated data. In this way, through the study and analysis of the GANs we can see if the model presents effectiveness and accuracy in the synthetic generation of meteorological data. With the proper conclusions of the results, this information can be used in order to improve the search for different models and the ability to generate synthetic time series data, which is representative of the real, original, data.

Abstract
To achieve lower switching losses and higher frequency capabilities in converter design, researchers worldwide have been investigating Silicon carbide (SiC) modules and MOSFETs. In power electronics, wide bandgap devices such as Silicon carbide are essential for creating more efficient, higher-density, and higher-power-rated converters. Devices like SiC and Gallium nitride (GaN) offer numerous advantages in power electronics, particularly by influencing parasitic capacitance and inductance in printed circuit boards (PCBs). A review paper on Silicon carbide converter designs using coupled inductors provides a comprehensive analysis of the advancements in SiC-based power converter technologies. Over the past decade, SiC converter designs have demonstrated both efficiency and reliability, underscoring significant improvements in performance and design methodologies over time. This review paper examines developments in Silicon carbide converter design from 2014 to 2024, with a focus on the research conducted in the past ten years. It highlights the advantages of SiC technology, techniques for constructing converters, and the impact on other components. Additionally, a bibliometric analysis of prior studies has been conducted, with a particular focus on strategies to minimize switching losses, as discussed in the reviewed articles. © 2025 by the authors.

Abstract
Water stress is a significant issue in many countries, including Portugal, which has seen a 20% reduction in water availability over the last 20 years, with a further 10-25% reduction expected by the end of the century. To address potable water consumption, this study aims to identify the optimal rainwater harvesting (RWH) system for a commercial building under various non-potable water use scenarios. This research involved qualitative and quantitative methods, utilizing the Rippl method for storage reservoir sizing and ETA 0701 version 11 guidelines. Various scenarios of non-potable water use were considered, including their budgets and economic feasibility. The best scenario was determined through cash flow analysis, considering the initial investment (RWH construction), income (water bill savings), and expenses (energy costs from hydraulic pumps), and evaluating the net present value (NPV), payback period (PB), and internal rate of return (IRR). The energy savings obtained were calculated by sizing a hybrid system with an RWH system and a photovoltaic (PV) system to supply the energy needs of each of the proposed scenarios and the water pump, making the system independent of the electricity grid. The results show that the best scenario resulted in energy savings of 92.11% for a 7-month period of regularization. These results also demonstrate the possibility for reducing potable water consumption in non-essential situations supported by renewable energy systems, thus helping to mitigate water stress while simultaneously reducing dependence on the grid.

Abstract
The increasing integration of distributed energy generation into the electrical grid has led to changes in the structure and organization of energy markets over the past years. Market trading has become increasingly demanding due to the different types of production profiles. A forecast of the total production of all assets is made to bid for energy. Whenever there are differences between the forecast and the actual produced energy, a deviation occurs, which is assigned to the agent responsible for its settlement. This article proposes the application of a linear regression algorithm supported by a clustering method to forecast energy production. Based on the historical production profile of the installations in each cluster, it is possible to predict the production pattern for a period with no available data, thus standardizing this data for other assets belonging to the same cluster. © 2025 IEEE.

Abstract
In recent years, Positive Energy Districts (PEDs) have been interpreted in many—and often conflicting—ways. This breadth has limited traction: projects defined disparate “energy-positive” metrics that were not directly tied to Paris-aligned climate neutrality. We recast PEDs as a vehicle for verifiable climate neutrality and present a declaration-ready assessment that integrates (i) a cumulative, science-based GHG budget per m² gross floor area (GFA), (ii) full life-cycle accounting, and (iii) time-resolved operational factors that include everyday motorized individual mobility (EMIM) and quantify flexibility. Two KPIs anchor the framework: the cumulative GHG LCA balance (2025–2075) against a maximum compliant budget of 320 kgCO2e·m?²GFA and the annual primary-energy (PE) balance used to declare PED status with or without mobility. We follow EN 15978 system logic with PED-oriented refinements—certain biogenic storage, PV?grid substitution crediting, and omission of project-level PV embodied impacts—and apply time-resolved emission factors that decline to zero by 2050. Under this assumption, most GHG accounting past 2050 ceases to be decision-relevant; the framework’s obligation is to stay within the 2025–2050 budget. Its applicability is demonstrated on six Austrian districts spanning new build and renovation, diverse energy systems, densities, and mobility contexts. Baseline scenarios show heterogeneous outcomes—only some meet both the cumulative GHG budget and the positive primary-energy balance—but design iterations indicate that all six districts can reach the targets with realistic, ambitious packages (e.g., ecological material substitutions, PV oversizing with flexibility, GSHP/TABS, BESS/V2B, and mobility electrification/demand reduction). Hourly emission factors with rolling-average flexibility signals can materially lower import-weighted emission intensity versus monthly or annual factors and reveal seasonal import–export asymmetries that annual bookkeeping masks. Built on transparent, auditable rules and open tooling, this framework both diagnoses performance gaps and maps credible pathways to compliance—steering PED design away from project-specific targets toward verifiable climate neutrality. It now serves as the basis for a national labeling/declaration scheme, enabling broad, consistent adoption across projects.