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Abstract Recent advances in materials have demonstrated the ability to maintain radiator surfaces at below-ambient temperatures in the presence of intense, direct sunlight. Daytime radiative cooling is promising for building applications. This paper estimates the energy savings from daytime radiative cooling, specifically based on photonic materials. A photonic radiative cooling system was proposed and modeled using the whole energy simulation program EnergyPlus. A typical medium-sized office building was used for the simulation analysis. Several reference systems were established to quantify the potential of energy savings from the photonic radiative cooling system. The reference systems include a variable-air-volume (VAV) system, a hydronic radiant system, and a nighttime radiative cooling system. The savings analysis was made for a number of locations with different climates. Simulation results showed that the photonic radiative cooling system saved between 45% and 68% cooling electricity relative to the VAV system and between 9% and 23% relative to the nighttime radiative cooling system featured with the best coating commercially available on market. A simple economic analysis was also made to estimate the maximum acceptable incremental cost for upgrading from nighttime cooling to photonic radiative cooling.

The problem of sizing an electricity storage for a 5000 inhabitants island supplied by both marine renewables (offshore wind and waves) and the mainland grid is addressed by a case study based on a full year resource and consumption data. Generators, transmission lines and battery storage are accounted for through basic simplified models while the focus is put on electricity import/export budget. Self-sufficiency does not seem a reasonable goal to pursue, but partial autonomy provided by renewable sources and a medium size storage would probably be profitable to the island community.

This work studies the power density (PD) optimization in wind farms, and its sensitivity to the available area size. A novel genetic algorithm (PDGA) is introduced, which optimizes PD and the turbine layout, by self-adapting to the PD and to the solutions diversity. PDGA uses the levelized cost of energy (LCOE) as cost function, which in turn employs the EPFL analytical wake model to derive the power output. For the baseline area size, PDGA reduces 2.25% the original LCOE, 2.6 times more than optimizing with constant PD. PDGA-driven solutions provide 11% and 6% LCOE reductions against the default layout for the smallest (6.4 km2) and largest (386 km2) scaled wind farm areas, respectively. Specially relevant for the industry, PDGA solutions depict convex fronts for area vs. LCOE or vs. PD, which allows determining the required area or turbine number given a target LCOE. Unlike default layouts, optimized ones reveal a linear relationship between LCOE and PD. The mean turbine spacing tends to 8-9D for very large areas. The economics-optimized PDs are below the estimated PD available in the atmosphere. This work is limited to a simplified, offshore wind climatology, a specific wind turbine model, and the LCOE specifications used herein.

Utilization of daylight in indoor spaces creates opportunities for energy savings and is linked to increasing productivity in the workplace. This sensitive aspect in environmentally aware architectural design depends on many interfacing factors. In this research, ceiling geometry is investigated as an element that can provide control to natural light, achieved through reflection and diffusion of the external and internal reflected components of daylight. This paper presents a generic optimization procedure for architects that aids in generation and finding of curvilinear and mesh ceiling forms. The objective was to maximize daylight uniformity ratios. A genetic algorithm was developed and coded in LUA, a versatile scripting language. Radiance simulation software was employed as the backend daylighting performance calculation engine, and Ecotect as the front end form input and visualization tool. Conclusions about the optimum ceiling geometry and form for a designed example case were drawn. The presented method provided architects with a variety of choices for designs which are weighed through daylighting performance. Results showed that this approach offers a robust and yet precise form finding method.

This paper addresses the simulation of a partially transparency, ventilated PV facade integrated into the envelope of an energy efficient building. Such an arrangement exploits the heat transfer between cavity air, the PV facade and the primary wall of the building for the purpose of PV cooling in summer (with natural convection) and heat recovery in winter (mechanical ventilation). A simplified physical model of the system is proposed for the summer operating configuration, which is more challenging from a numerical perspective. The model describes the active envelop in terms of a simplified geometry, and includes parameters such as density of PV cells, relative coverage of degree of transparency/opaque surfaces, and the ratio of height/width of the double-skin. For a given set of meteorological conditions, the surface and air temperatures, mass flow rate and PV power output are obtained by solving a system of thermal and aerodynamic balance equations. Validation of the model was undertaken using experimental data from a full scale prototype system installed in Toulouse, France as part of the RESSOURCES project (ANR-PREBAT2007). Coupling of the system to a simulated building was achieved with the aid of TRNSYS, and this combined system was evaluated in terms of heating and cooling needs for a range of French climates. It was found that the cooling needs are marginally higher for all locations considered, whereas the impact of the facade on the heating needs is weak as these needs are already low for these all locations.

The present study investigates the feasibility of coupling the intermittent electric power generation from a wind farm with alkaline electrolyzers to produce green hydrogen. A physically accurate model of commercial elec-trolytic modules has been first developed, accounting for conversion efficiency drop due to modules' cool down, effects of shutdowns due to the intermittence of wind power, and voltage degradation over the working time frame. The model has been calibrated on real modules, for which industrial data were available. Three com-mercial module sizes have been considered, i.e., 1, 2 and 4 MW. As a second step, the model has been coupled with historical power datasets coming from a real wind farm, characterized by a nominal installed power of 13.8 MW. Finally, the model was implemented within a sizing algorithm to find the best combination between the actual wind farm power output and the electrolyzer capacity to reach the lowest Levelized Cost Of Hydrogen (LCOH) possible. To this end, realistic data for the capital cost of the whole system (wind farm and electrolyzers) have been considered, based on industrial data and market reports, as well as maintenance costs including both periodic replacements of degraded components and periodic maintenance. Simulations showed that, if the right sizing of the two systems is made, competitive hydrogen production costs can be achieved even with current technologies. Bigger modules are less flexible but, by now, considerably cheaper than smaller ones. A future economy of scale in alkaline electrolyzers is then needed to foster the diffusion of the technology.