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Despite the rapid growth in the uptake of renewable energy technologies, the educational profile and the skills gained at University level do not always comply with the practical needs of the organisations working in the field. Furthermore, even though the residential sector has very high potential in curbing its CO2 emissions worldwide thus meeting the challenging goals set out by the international agreements, such reduction has been limited so far. Within this context, the ‘Skybelt’ project, co-funded by the EU under the framework of the Erasmus + programme aims at enhancing in several Universities of Asia and Europe the engineering skills of students of all level for application of sustainable renewable energy solutions in the built environment. With the target of increasing the employability of graduates and the impact of the project, a survey on the labour market needs for specialists with enhanced knowledge and skills in the topic of the project has been conducted in the related Asian countries. Hence, relevant industries, labour market organisations and other stakeholders have been interviewed and the main results of this analysis is reported in the present paper. As first outcome of this activity, the obtained results have been considered in the selection of the modules to be improved according to a student centred study approach.

The operation of a power plant based on solar energy can vary significantly with time because of the intrinsic intermittency of the energy resource. Hence, a smart management is required to deal with the complex dynamic variations of the different subsystems. In order to do that, different control logics can be implemented but their effectiveness strictly depends on the temporal evolution of the parameters considered. For a given plant configuration, their exact estimation can be obtained through experimental tests during the commissioning of the plant. However, any change in the design parameters of the plant reflects in a different time constant, whose preliminary knowledge may be of support in tuning the control logic of the plant during the design stage. Therefore, based on the configuration of a small-scale concentrated solar combined heat and power plant as designed and built under the EU funded project Innova MicroSolar by several universities and companies, in this study a prediction of the time constant of several plant configurations with varying solar multiple and size of the storage tank is performed. By making use of the dynamic simulator previously developed by some of the authors, an estimation of such characteristic is assessed in case of potential redesign of the plant, providing also useful suggestions into the design of the control logic.

6 p Electrónico, One of the main challenges related to the renewable energy labour market is that of human capital and as a consequence the educational profile of future employees is of paramount importance. Unfortunately, the skill level gained at University does not always fit with the practical needs of industry thus reducing the benefit-cost ratio of new employees and slowing down the programme aims at improving the renewable energy engineering curriculum at different university levels in several Universities of Latin America and Europe. In order to better appreciate the potential impact of the project, a survey on the labour market need for specialists with enhanced knowledge and skills in renewable and sustainable energy technologies has been conducted in the related EU and Latin America countries. More precisely, 60 organizations have been interviewed and almost 70% of them are interested in employing engineers with enhanced knowledge on renewable energy in the next three years. The analysis has shown significant discrepancies between EU and Latin American organizations. In fact, while future employees in EU countries will be mainly related to solar energy and management, the former together with wind and biomass will represent the main renewable energy working sector in Latin American countries. Moreover, MSc level will be the most demanded in EU while bachelor education seems to satisfy the future industry requirements in Latin America. Despite each country having its own needs, the research carried out under this EU project confirms the potential of renewable energy education on the global labour market in the near future.

In this paper four different detailed models of pipelines are proposed and compared to assess the thermal losses in small-scale concentrated solar combined heat and power plants. Indeed, previous numerical analyses carried out by some of the authors have revealed the high impact of pipelines on the performance of these plants because of their thermal inertia. Hence, in this work the proposed models are firstly compared to each other for varying temperature increase and mass flow rate. Such comparison shows that the one-dimensional (1D) longitudinal model is in good agreement with the results of the more detailed two-dimensional (2D) model at any temperature gradient for heat transfer fluid velocities higher than 0.1 m/s whilst the lumped model agrees only at velocities higher than 1 m/s. Then, the 1D longitudinal model is implemented in a quasi-steady-state Simulink model of an innovative microscale concentrated solar combined heat and power plant and its performances evaluated. Compared to the results obtained using the Simscape library model of the tube, the performances of the plant show appreciable discrepancies during the winter season. Indeed, whenever the longitudinal thermal gradient of the fluid inside the pipeline is high (as at part-load conditions in winter season), the lumped model becomes inaccurate with more than 20% of deviation of the thermal losses and 30% of the organic Rankine cycle (ORC) electric energy output with respect to the 1D longitudinal model. Therefore, the analysis proves that an hybrid model able to switch from a 1D longitudinal model to a zero-dimensional (0D) model with delay based on the fluid flow rate is recommended to obtain results accurate enough whilst limiting the computational efforts.

Solar energy is widely considered as one of the most attractive renewable energy source to curb CO2 emissions at residential level where micro-cogeneration has a very interesting potential. One promising application of solar energy is in combination with Organic Rankine Cycle (ORC) plants due to the ability to utilize low-medium temperature heat sources. However, because of the intermittent availability of solar energy, thermal energy storage (TES) systems are required to improve the performance of such systems and assure their prolonged operation. At medium temperatures, latent heat thermal energy storage (LHTES) systems allow to effectively store and release the collected thermal energy from the solar field. However, room for improvements exists to increase their efficiency when in operation. For this reason, in this work the authors have numerically investigated the performance of a 2 kWe micro-solar ORC plant coupled with an innovative LHTES system that is going to be built and tested under the EU funded project Innova MicroSolar. The novel LHTES, developed and designed by some partners of the Consortium, is subdivided into six modules and consists of 3.8 tons of high-temperature phase change material. In this study the effect of the storage volume partialization on the performance of the integrated plant is evaluated using a fuzzy logic approach. Main aim of the storage management is to achieve a reduction of the thermal losses and improve the plant overall efficiency. Annual dynamic simulations are performed in order to determine the optimal storage volume needed in different operating conditions. Results clearly show a remarkable annual increase in electric and thermal energy production of 8 % and 6 % respectively, in comparison with the configuration without fuzzy logic control: this achievement was obtained decreasing the working LHTES modules in winter and conversely increasing them in summer. This study is a part of the Innova MicroSolar Project, funded in the framework of the European Union’s Horizon 2020 Research and Innovation Programme (grant agreement No 723596).