Davide Aloisio

The adoption of hydrogen represents a key lever for reducing CO2 emissions in hard-to-abate industries and in the power generation sector. Nevertheless, the high costs and infrastructure requirements associated with green hydrogen production remain major challenges. This study investigates how an optimized hydrogen production strategy can reduce the Levelized Cost of Hydrogen (LCOH), thereby directly lowering the operational expenditure related to electricity procurement. The analysis focuses on the optimization of a hydrogen production plant where two strategies were adopted: one considering electricity supplied from the grid (low-carbon hydrogen) and one from renewable energy sources (Green Hydrogen case). To assess the influence of local energy conditions, the same scenario was analyzed in three European regions (Italy, Spain, and Netherlands) where both grid electricity prices and solar resource availability differs significantly. This comparative approach makes possible to quantify how regional energy peculiarities impact the cost-effectiveness of hydrogen production. A Matlab-based simulation model was developed to perform the analysis and to ensure accurate, realistic system behaviour. The resulting insights identify the most cost-effective approaches for integrating hydrogen production into the energy value chain. Overall, the study emphasizes the advantages of flexible hydrogen production scheduling, leveraging dynamic electricity pricing and renewable energy availability to minimize operational costs while maximizing system efficiency. The model uses cost data coming from an industrial-scale electrolysis plant under development in Sicily within the framework of Hy2Market EU funded project, providing a realistic basis for investment assumptions.

Demand Bidding (DB) is one of the programs that allow microgrid owners to provide Demand Response (DR). However, the DR bid formulation involves risks, such as technical infeasibility, cost ineffectiveness, and uncertainty on the actual DR service request. Furthermore, providing flexibility through load variations could be inconvenient. This paper proposes an Energy Management System (EMS) capable of microgrid flexibility evaluation to support DB. The EMS only leverages storage flexibility without changing the load profile. After computing the power flows that minimize the cash flow, it evaluates microgrid flexibility in terms of 1) possible deviations from the optimal profile of the power exchanged with the grid, and 2) the related incremental cost. This information allows microgrid owners to assess whether it is worth bidding for DR services and helps formulate the bid. Thus, the user is safeguarded from all the DB risks. The proposed technique is assessed considering the microgrid of an industrial hydrogen facility as a case study.

The emission reductions mandated by International Maritime Regulations present an opportunity to implement full electric and hybrid vessels using large-scale battery energy storage systems (BESSs). lithium-ionion batteries (LIB), due to their high power and specific energy, which allows for scalability and adaptability to large transportation systems, are currently the most widely used electrochemical storage system. Hence, BESSs are the focus of this review proposing a comprehensive discussion on the commercial LIB chemistries that are currently available for marine applications and their potential role in ship services. This work outlines key elements that are necessary for designing a BESS for ships, including an overview of the regulatory framework for large-scale onboard LIB installations. The basic technical information about system integration has been summarized from various research projects, white papers, and test cases mentioned in available studies. The aim is to provide state-of-the-art information about the installation of BESSs on ships, in accordance with the latest applicable rules for ships. The goal of this study is to facilitate and promote the widespread use of batteries in the marine industry.

This study focuses on the microwave characterisation of a microstrip resonator aimed for gas sensing applications. The developed one-port microstrip resonator, consisting of three concentric rings with a central disk, is coupled to a 50-Ohm microstrip feedline through a small gap. A humidity sensing layer is deposited on this gap by drop-coating an aqueous solution of Ag@alpha-Fe2O3 nanocomposite. The operation principle of the developed humidity sensor is based on the change of the dielectric properties of the Ag@alpha-Fe2O3 nanocomposite when the relative humidity is varied. However, it should be underlined that, depending on the choice of the sensing material, different target gases of interest can be detected with the proposed structure. The frequency-dependent response of the sensor is obtained using the reflection coefficient measured from 3.5 GHz to 5.6 GHz with relative humidity ranging from 0 %rh to 83 %rh. The variation of the humidity concentration strongly impacts on the two resonances detected in the measured reflection coefficient. In particular, an increase of the humidity level leads to lowering both resonant frequencies, which can be used as sensing parameters for humidity monitoring purpose. An exponential function has been used to accurately model the two resonant frequencies as a function of the humidity.

Scheduling of energy storage systems of distributed generation is a key element for optimal renewable energy sources (RES) exploitation in smart grids, demand side response strategies implementation and prosumers interaction with Distribution System Operators (DSOs). In this context, this paper presents the implementation of a management system for energy storage scheduling, which allows taking appropriate account of the storage system behavior in real cases. To properly consider the real system operation, the employed battery model is modified, in order to include also the hysteresis phenomena in state of charge estimation in both charging and discharging operation. The validation of the proposed methodology is supported by experimental tests which allow comparing two different battery models. The obtained results show that better results can be obtained with the model including the hysteresis effect.