• Energy Research
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This study introduces novel phenothiazine-based organic dyes, 2-LBH-100, 2-LBH-44, and 2-Ryu-4, specifically designed for quasi-solid-state dye-sensitized solar cells (QsDSSCs). Employing a donor-π-acceptor architecture, these dyes incorporate varying electron-donating moieties, including bis(3-(hexyloxy)phenyl)amine and diphenylamino, coupled with a cyanoacrylic acid acceptor. Alkoxy substitutions in 2-LBH-100 and 2-LBH-44 enhanced solubility and dye loading on TiO2, leading to improved performance in QsDSSCs. 2-LBH-100 exhibited a power conversion efficiency (PCE) exceeding 5% with excellent stability, while 2-LBH-44 demonstrated a PCE of over 3%, increasing to 4% over time. 2-Ryu-4, with its diphenylamino donor, achieved an initial PCE of over 6%. This research highlights the crucial role of donor–acceptor interactions in optimizing organic dye design for high-performance QsDSSCs, paving the way for efficient and stable next-generation solar energy technologies.

The paper presents a preliminary technical-economic comparison between a 3 kV DC railway and the use of trains with on-board storage systems. Numerical simulations have been carried out on a real railway line, which presents an electrified section at 3 kV DC and a non-electrified section, currently covered by diesel-powered trains. Different types of ESS have been analyzed, implementing the models in Matlab/Simulink environment. A preparatory economic investigation has been carried out.

This paper presents a one-dimensional finite-volume model of an unglazed photovoltaic/thermal (PVT) solar collector. The unit consists of a conventional solar photovoltaic (PV) collector coupled with a suitable heat exchanger. In particular, the collector includes a roll bond heat exchanger and it is not equipped with back and frame insulation. The system is discretized along the flow direction (longitudinal) of the cogenerative collector. For each finite-volume element of the discretized computational domain, mass and energy balances are implemented. The collector geometry and materials parameters are taken from a commercially available device. An on-field experimental investigation is performed in order to validate the proposed model. The model is used to evaluate both electrical and thermodynamic parameters for each element of the domain and for fixed operating conditions. Finally, a sensitivity analysis is also performed in order to investigate the energetic performance of the cogenerative collector as a function of the main design/environmental parameters.

This work presents an innovative control architecture, which takes its ideas from the theory of adaptive control techniques and the theory of statistical learning at the same time. Taking inspiration from the architecture of a classical neural network with several hidden levels, the principle is to divide the architecture of the adaptive controller into three different levels. Each level implements an algorithm based on learning from data and therefore we can talk about learning concepts. Each level has a different task: the first to learn the required reference to the control loop; the second to learn the coefficients of the state representation of a model of the system to be controlled; and finally, the third to learn the coefficients of the state representation of the actual controller. The design of the control system is reported from both a rigorous and an operational point of view. As an application example, the proposed control technique is applied on a second-order non-linear system. We consider a servo-drive based on a brushless DC (BLDC) motor, whose dynamic model considers all the non-linear effects related to the electromechanical nature of the electric machine itself, and also an accurate model of the switching power converter. The reported example shows the capability of the control algorithm to ensure trajectory tracking while allowing for disturbance rejection with different disturbance signal amplitude. The implementation complexity analysis of the new controller is also proposed, showing its low overhead vs. basic control solutions.

This paper deals with wave energy conversion in shallow water, analyzing the performance of two different oscillating-body systems. The first one is a heaving float, which is a system known in the literature. The second one is obtained by coupling the heaving float with a surging paddle. In order to check the different behaviors of the multibody system and the single-body heaving float, physical models of the two systems have been tested in a wave flume, by placing them at various water depths along a sloping bottom. The systems have been tested with monochromatic waves. For each water depth, several tests have been performed varying the geometrical and mechanical parameters of the two systems, in order to find their best configurations. It has been found that the multibody system is more energetic when the float and the paddle are close to each other. Capture width ratio has been found to significantly vary with water depth for both systems: in particular, capture width ratio of the heaving float (also within the multibody system) increases as water depth increases, while capture width ratio of the paddle (within the multibody system) increases as water depth decreases. At the end, the capture width ratio of the multibody system is almost always higher than that of the heaving float, and it increases as water depth increases on average; however, the multibody advantage over single body is significant for water depth less than the characteristic dimension of the system, and decreases as water depth increases.

Overtopping-type wave power conversion devices represent one of the most promising technology to combine reliability and competitively priced electricity supplies from waves. While satisfactory hydraulic and structural performance have been achieved, the selection of the hydraulic turbines and their regulation is a complex process due to the very low head and a variable flow rate in the overtopping breakwater set-ups. Based on the experience acquired on the first Overtopping BReakwater for Energy Conversion (OBREC) prototype, operating since 2016, an activity has been carried out to select the most appropriate turbine dimension and control strategy for such applications. An example of this multivariable approach is provided and illustrated through a case study in the San Antonio Port, along the central coast of Chile. In this site the deployment of a breakwater equipped with OBREC modules is specifically investigated. Axial-flow turbines of different runner diameter are compared, proposing the optimal ramp height and turbine control strategy for maximizing system energy production. The energy production ranges from 20.5 MWh/y for the smallest runner diameter to a maximum of 34.8 MWh/y for the largest runner diameter.

Battery participation in the service of power system frequency regulation is universally recognized as a viable means for counteracting the dramatic impact of the increasing utilization of renewable energy sources. One of the most complex aspects, in both the planning and operation stage, is the adequate characterization of the dynamic variation of the state of charge of the battery in view of lifetime preservation as well as the adequate participation in the regulation task. Since the power system frequency, which is the input of the battery regulation service, is inherently of a stochastic nature, it is easy to argue that the most proper methodology for addressing this complex issue is that of the theory of stochastic processes. In the first part of the paper, a preliminary characterization of the power system frequency is presented by showing that with an optimal degree of approximation it can be regarded as an Ornstein–Uhlenbeck process. Some considerations for guaranteeing desirable performances of the control strategy are performed by assuming that the battery-regulating power depending on the frequency can be described by means of a Wiener process. In the second part of the paper, more realistically, the regulating power due to power system changes is described as an Ornstein–Uhlenbeck or an exponential shot noise process driven by a homogeneous Poisson process depending on the frequency response features requested of the battery. Because of that, the battery state of charge is modeled as the output of a dynamic filter having this exponential shot noise process as input and its characterization constitutes the central role for the correct characterization of the battery life. Numerical simulations are carried out for demonstrating the goodness and the applicability of the proposed probabilistic approach.