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Abstract The effect of the thermal environment on performance and productivity has been a focus of interest among indoor environmental researchers for nearly a century, but most of that work has been conducted in relative isolation from the cognate disciplines of human performance evaluation. The present review examines thermal environmental effects on cognitive performance research conducted across multiple disciplines. After differentiating performance from productivity, we compare the two dominant conceptual models linking thermal stress to performance; (1) the inverted-U concept and (2) the extended-U relationship. The inverted-U specifies a single optimum temperature (or its corresponding subjective thermal sensation) at which performance is maximised. In contrast, the extended-U model posits a broad central plateau across which there is no discernible thermal effect on cognitive performance. This performance plateau is bounded by regions of progressive performance decrements in more extreme thermal conditions. The contradictions between these opposing conceptual models might derive from various confounding factors at play in their underlying research bases. These include, inter alia, environment-related, task-related, and performer-related factors, as well as their associated two-way and three-way interaction effects. Methodological discrepancies that might also contribute to the divergence of these conceptual models are evaluated, along with the proposed causal mechanisms underlying the two models. The weight of research evidence reviewed in this paper suggests that the extended-U hypothesis fits the relationship between moderate thermal environments and cognitive performance. In contrast to the inverted-U relationship, implemention of the extended-U in indoor climate control implies substantial reductions in building energy demand, since it permits the heating and cooling setpoint deadband to expand across the full width of the thermal comfort zone, or even slightly further during emergencies such as peak demand events on the electricity grid. Use of personal comfort systems can further extend the thermostat setpoint range beyond the comfort zone.

Abstract In Australia, the government spending on public buildings’ energy and water consumption is considerable; however the building energy and water retrofit market potential has been diminished by a number of barriers, especially financial. In contrast, in other advanced economies there are several reported financing strategies that have been shown to accelerate retrofit projects implementation. In this study, a coupled Bayesian Network – System Dynamics model was developed with the core aim to assess the likely influence of those novel financing options and procurement procedures on public building retrofit outcomes scenarios in the Australian context. A particular case-study focusing on Australian public hospitals was showcased as an example in this paper. Stakeholder engagement was utilised to estimate likely preferences and to conceptualise causal relationships of model parameters. The scenario modelling showed that a revolving loan fund supporting an energy performance contracting procurement procedure was preferred. Subsequently, the specific features of this preferred framework were optimised to yield the greatest number of viable retrofit projects over the long term. The results indicated that such a financing scheme would lead to substantial abatement of energy and water consumption, as well as carbon emissions. The strategic scenario analysis approach developed herein provides evidence-based support to policy-makers advocating novel financing and procurement models for addressing a government’s sustainability agenda in a financially responsible and net-positive manner.

Nowadays, the photovoltaic technology level development makes it the best option for its building integration as energy supplier. Nevertheless, its aesthetic appearance plays a relevant role because architect requirements go beyond the simple installation of solar devices on terraces. In order to fulfill their requirements, the typical white backsheet uses to be replaced by a black one. This simple change leads to a huge PV module performance reduction. In this work, it has been demonstrated that a suitable material selection allows to fabricate photo voltaic modules with a high architectonic integration, but without power reduction with respect to the most commercial solar devices. The former consists in the replacement of the typical glass front cover and the white backsheet by an antireflective glass and a black backsheet respectively. All the study has been developed on real size photovoltaic modules fabricated in an automatic line. The obtained results determine that those modules where black backsheets are used, suffer a power reduction equal to 8.66 W per fabricated module. Nevertheless, when in addition of the black backsheet an antireflective coating glass is implemented, the resulted PV modules present a more aesthetic presence without a detrimental of their power performance when they are compared to the standard PV modules. Additionally, the fabricated solar devices using the proposed configuration successfully overcome the most common aging tests. Política de acceso abierto tomada de: https://openpolicyfinder.jisc.ac.uk/id/publication/11131

Abstract Accurate rooftop solar energy potential characterization is critically important for promoting the wide penetration of renewable energy in high-density cities. However, it has been a long-standing challenge due to the complex building shading effects and diversified rooftop availabilities. To overcome the challenge, this study proposed a novel 3D-geographic information system (GIS) and deep learning integrated approach, in which a 3D-GIS-based solar irradiance analyzer was developed to predict dynamic rooftop solar irradiance by taking shading effects of surrounding buildings into account. A deep learning framework was developed to identify the rooftop availabilities. Experimental validations have shown their high accuracies. As a case study, a real urban region of Hong Kong was used. The results showed that the annual solar energy potential of the entire building group was reduced by 35.7% due to the shading effect and the reduced rooftop availability. The reductions of individual buildings varied from 13.4% to 74.5%. In spite of the substantial reductions of the annual solar energy, the shading effect could only slightly reduce the peak solar power. In fact, the annual solar energy reduction could be five times higher than the peak solar power reduction. Further analysis showed that simple addition of the respective solar energy potential reductions, caused by the shading effect and the rooftop availability, tends to highly overestimate the total reduction by up to 26%. For this reason, their impacts cannot be considered separately but as joint effects. The integrated approach provides a viable means to accurately characterize rooftop solar energy potential in urban regions, which can help facilitate solar energy applications in high-density cities.

We propose a methodology to price an insurance contract designed to hedge the volumetric risk associated with weather conditions. Our methodology is based on conditional quantile regressions and adapts Value at Risk (VaR) and Expected Shortfall statistics from the literature on financial econometrics. In our empirical application, we use actual daily meteorological and radiation data for 40 European cities in 13 countries, from April 1, 2011, to December 31, 2021, and calculate the value of the annual insurance premium under reasonable assumptions on the technology of the solar panels and expected energy demand. We consider variables such as temperature, wind speed, and precipitation in our calculations. Our results for the different cities in our sample show that due to the nonlinear impact of weather (mainly temperature and precipitation) on the expected generation losses, it is appropriate to use quantile regressions to calculate the VaR of radiation, conditional on weather factors. Our insurance premium calculations also present a high degree of variation across European, which indicates that risk-diversification opportunities of catastrophic risk due to weather conditions faced by insurance companies exist. This variation is explained by different weather conditions, model adjustment, and the average price of electricity.

Enhancing the reliability of energy networks and minimizing downtime is crucial, making self-healing smart grids indispensable for ensuring a continuous power supply and fortifying resilience. As smart grids increasingly incorporate decentralized prosumers, innovative coordination strategies are essential to fully exploit their potential and improve system self-healing capabilities. To address this need, this paper presents a novel bi-level strategy for managing the self-healing process within a smart grid influenced by Hydrogen Refueling Stations (HRSs), Electric Vehicle Charging Stations (EVCSs), and energy hubs. This approach taps into the combined potential of these prosumers to boost system self-healing speed and reliability. In the initial stage, the Smart Grid Operator (SGO) conducts self-healing planning during emergencies, communicating required nodal capacities to prevent forced load shedding and outlining incentives for smart prosumers. Subsequently, prosumers schedule their activities and contribute flexible capacities to the SGO. Bridging the first and second stages, an adaptive Alternating Direction Method of Multipliers (ADMM) algorithm ensures convergence between the SGO and prosumer schedules within a decentralized framework. This strategy underwent implementation on a 118-node distribution system using GAMS. Results demonstrate that the proposed concept reduces Forced Load Shedding (FLS) by 32.04% and self-healing costs by 17.48% through effective utilization of smart prosumers' flexible capacities. Furthermore, outcomes indicate that the SGO reduces FLS by 6.69% by deploying Mobile Electrical Energy Storages (MEESs) and Mobile Fuel Cell Trucks (MFCTs) to critical nodes. This research has benefited from the funding of the program Strategic projects oriented to the ecological transition and digital transition with NextGenerationEU/PRTR funds of the Spanish Ministry of Science and Innovation/State Research Agency (project ‘‘Local markets for energy communities: designing efficient markets and assessing the integration from the electricity system perspective (OptiREC)’’, with reference number TED2021-131365B-C43. The research has also supported by the Natural Science Foundation of Universities of Anhui Province (KJ2020A0009)

A volume transmission phase holographic element was designed and constructed to perform as a building integrated photovoltaic concentrator. The holographic lens diffracts light in the spectral bandwidth to which the cell presents the highest sensitivity with a concentration factor of 3.6X. In this way, the cell is protected from overheating because the infrared for which the solar cell is not sensitive is not concentrated. In addition, based on the asymmetric angular selectivity of the volume hologram and based on the linear concentration, only single-axis tracking is needed. The use of the holographic element increases the efficiency of the PV cell by 3% and the fill factor by 8%.

Parabolic reflectors, also known as parabolic troughs, are widely used in solar thermal power plants. This kind of power plants is usually located on desert climates, where the combined action of wind and dust can be of paramount importance. In some cases it becomes necessary to protect these devices from the joined wind and sand action, which is normally accomplished through solid windbreaks. In this paper the results of a wind tunnel test campaign, of a scale parabolic trough row having different windward windbreaks, are reported. The windbreaks herein considered consist of a solid wall with an upper porous fence. Different geometrical configurations, varying the solid wall height and the separation between the parabolic trough row and the windbreak have been considered. From the measured time series, both the mean and peak values of the aerodynamic loads were determined. As it would be expected, mean aerodynamic drag, as well as peak values, decrease as the distance between the windbreak and the parabolic increases, and after a threshold value, such drag loads increase with the distance.