Abstract
Hydrogen is a promising commodity, a renewable secondary energy source, and feedstock alike, to meet greenhouse gas emissions targets and promote economic decarbonization. A common goal pursued by many countries, the hydrogen economy receives a blending of public and private capital. After European Green Deal, state members created national policies focused on green hydrogen. This paper presents a study of energy transition considering green hydrogen production to identify Portugal's current state and prospects. The analysis uses energy generation data, hydrogen production aspects, CO2 emissions indicators and based costs. A comprehensive simulation estimates the total production of green hydrogen related to the ratio of renewable generation in two different scenarios. Then a comparison between EGP goals and Portugal's transport and energy generation prospects is made. Portugal has an essential renewable energy matrix that supports green hydrogen production and allows for meeting European green hydrogen 2030-2050 goals. Results suggest that promoting the conversion of buses and trucks into H2-based fuel is better for CO2 reduction. On the other hand, given energy security, thermoelectric plants fueled by H2 are the best option. The aggressive scenario implies at least 5% more costs than the moderate scenario, considering economic aspects.

Abstract
The reliability of power converters in photovoltaic systems is critical to the overall system reliability. This paper proposes a novel active thermal-controlled algorithm that aims to reduce the rate of junction temperature increase, therefore, increasing the reliability of the device. The algorithm works alongside a normal perturb and observe maximum power point tracking algorithm, taking control when certain temperature criteria are met. In conjunction with a neural network, the algorithm is applied to long-term real mission profile data. This would grant a better understanding of the real-world trade-offs between energy generated and lifetime improvement when using the proposed algorithm, as well as shortening study cycle times. The neural network, when applied to 365 days of data, was 28 times faster than using standard electrothermal modeling, and the lifetime consumption was predicted with greater than 96.5% accuracy. Energy generated was predicted with greater than 99.5% accuracy. The proposed algorithm resulted in a 3.3% reduction in lifetime consumption with a 1.0% reduction in the total energy generated. There is a demonstrated trade-off between lifetime consumption reduction and energy-generated reduction. The results are also split by environmental conditions. Under very variable conditions, the algorithm resulted in a 4.4% reduction in lifetime consumption with a 1.4% reduction in the total energy generated.

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Grid-Forming Power Inverters: Control and Applications is the first book dedicated to addressing the operation principles, grid codes, modeling, and control of grid-forming power inverters. The book initially discusses the need for this technology due to the substantial annual integration of inverter-based renewable energy resources. The key differences between the traditional grid-following and the emerging grid-forming inverter technologies are explained. Then, the book explores in detail various topics related to grid-forming power inverters, including requirements and grid standards, modeling, control, damping power system oscillations, dynamic stability under large fault events, virtual oscillator-controlled grid-forming inverters, grid-forming inverters interfacing battery energy storage, and islanded operation of grid-forming inverters. Features: • Explains the key differences between grid-following and grid-forming inverters • Explores the requirements and grid standards for grid-forming inverters • Provides detailed modeling of virtual synchronous generators • Explains various control strategies for grid-forming inverters • Investigates damping of power system oscillations using grid-forming converters • Elaborates on the dynamic stability of grid-forming inverters under large fault events • Focuses on practical applications

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Nontechnical losses in electricity distribution networks are often associated with a countries' socioeconomic situation. Although the amount of global losses is usually known, the separation between technical and commercial (nontechnical) losses will remain one of the main challenges for DSO until smart grids become fully implemented and operational. The most common origins of commercial losses are energy theft and deliberate or accidental failures of energy measuring equipment. In any case, the consequences can be regarded as consumption anomalies. The work described in this paper aims to answer a request from a DSO, for the development of tools to detect consumption anomalies at end-customer facilities (HV, MV and LV), invoking two types of assessment. The first consists of the identification of typical patterns in the set of consumption profiles of a given group or zone and the detection of atypical consumers (outliers) within it. The second assessment involves the exploration of the load diagram evolution of each specific consumer to detect changes in the consumption pattern that could represent situations of probable irregularities. After a representative period, typically 12 months, these assessments are repeated, and the results are compared to the initial ones. The eventual changes in the typical classes or consumption scales are used to build a classifier indicating the risk of anomaly.