• Energy Research
• 2016-2025close
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In the quest for more efficient solar thermal systems, accurately determining the thermal emittance of low-emissive materials is crucial in determining the power losses. This paper describes the calorimetric method designed to precisely measure the thermal emittance of Selective Solar Absorbers (SSAs) to be used in High Vacuum Flat Plate Collectors (HVFPCs). The method’s capability is demonstrated through the successful correction of thermal emittance values for copper samples of varying sizes, including dimensions down to 49 cm2. Results highlight the method’s potential to significantly reduce measurement errors associated with small-size and/or low-emittance samples, providing a path forward to improve the design and efficiency of SSAs. This research marks a significant step in advancing solar thermal technology by enabling emittance measurements with a precision better than 0.003, which is essential for the development of high-performance solar thermal absorbers. The method has also been applied to correct the thermal emittance value of SSA measured in previous measurement campaigns, and it allows a better estimation of the SSA efficiency conversion curve.

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 paper investigates the impact of the standard approximations embodied in the well-known Momentum Theory on its performance prediction capabilities. To this aim, the results of the momentum theory, which is still widely used in all Blade Element/Momentum codes for the analysis and/or design of wind turbines, are compared with those obtained with an actuator disk model based on Computational Fluid Dynamics techniques. In this method, the axisymmetric and steady Euler equations are solved with a classical finite volume approach, while the turbine effects are modelled through a set of axial and tangential body forces distributed over a disk shaped region representing the rotor swept surface. Since this method does not rely on the momentum theory simplifying assumptions, it can be suitably employed to verify the momentum theory validity. The analysis is carried out using the well documented experimental data of the National Renewable Energy Laboratory Phase VI wind turbine.

Cogeneration of heat and electricity is an important pillar of energy and climate policy. To plan the production and distribution system of combined heat and power (CHP) systems for residential heating, suitable methods for decision support are needed. For a comprehensive feasibility analysis, the integration of the location and capacity planning of the power plants, the choice of customers, and the network planning of the heating network into one optimization model are necessary. Thus, we develop an optimization model for electricity generation and heat supply. This mixed integer linear program (MILP) is based on graph theory for network flow problems. We apply the network location model for the optimization of district heating systems in the City of Osorno in Chile, which exhibits the “checkerboard layout” typically found in many South American cities. The network location model can support the strategic planning of investments in renewable energy projects because it permits the analysis of changing energy prices, calculation of break-even prices for heat and electricity, and estimation of greenhouse gas emission savings.

The joint impact of human activities and climate change on natural resources lead to biodiversity loss. Therefore, it is important to select protected areas through systematic conservation planning. The present study assessed how representative natural habitats are protected under the nature conservation network, and to identify new—but so far insufficiently—protected areas containing these habitats for sustainable management. We used the Marxan model to select the most valuable insufficiently protected natural habitats in the Czech Republic as a representative example for a conservation strategy for Central–Eastern European environments. We set three conservation targets (25%, 50%, and 75%), defining how much percent area of valuable representative natural habitats should be added to the area of the habitats already included in the Nature Protection Network. To implement these conservation targets it is necessary to preserve 22,932 ha, 72,429, ha and 124,363 ha respectively of the conservation targets occurring in the insufficiently protected areas, and 17,255 ha, 51,620 ha, and 84,993 ha respectively of the conservation features in the areas without protection status. Marxan was revealed to be an appropriate tool to select the most valuable and insufficiently protected natural habitats for sustainable management.

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.