4E Advancement of Heat Recovery During Hot Seasons for a Building Integrated Photovoltaic Thermal (BIPV/T) System

In conventional building integrated photovoltaic thermal (BIPV/T) systems, heat is only recovered during cold seasons. However, no recovery takes place in hot seasons. Therefore, this study comes up with an answer to the question “how much improvement in the amount of annual recovered heat (ANRH), average exergy efficiency (AAEE), and CO2 saving (ACDS), as well as payback period (PBP), is achieved when heat recovery is done in hot seasons?”. These are representatives of energy, exergy, environmental and economic (4E) aspects, respectively. The results show a 135.6%, 1.8% and 123.0% enhancement in the ANRH, AAEE and ACDS, respectively, while PBP decreases from 6.10 to 3.94 years

Solar pre-cooling with different tariff structures and household time of use patterns

This paper presents a clustering-based solar pre-cooling (SPC) analysis to evaluate the SPC potential of Australian housing stock. 450 households with solar PV systems and Air Conditioning (AC) are clustered into different groups based on their net electricity demand profiles excluding any AC operation. Then, the AC excluded net demand profile of each household is combined with nine different building types, creating nine virtual building envelopes for each household. Solar pre-cooling is simulated for all the virtual buildings and the results are compared with a baseline scenario in terms of maximum demand reduction, minimum demand mitigation, and cost savings, considering three different tariff structures. The results show that regardless of the energy efficiency and construction materials of a building, the SPC potential varies significantly based on the AC excluded net demand profile of the household. SPC offers high minimum demand mitigation while maximum demand reduction is not considerable. The cost savings highly depends on the tariff structure, and the Feed-in Tariff (FiT)

Cost-Saving through Pre-Cooling: A Case Study of Sydney

Air conditioning is responsible for a considerable proportion of households’ electricity bills. During summer afternoons when households usually run their air conditioners, the retail time-of-use electricity tariffs are highest, and there is a peak demand in the electricity network. Pre-cooling is a method to shift air conditioning demand from peak hours to hours with lower demand and cheaper electricity tariffs. In this research, the pre-cooling potential of nine different types of residential housing in Sydney constructed with different star ratings and construction weights is evaluated. Star rating is the method to represent the annual heating and cooling requirements of buildings in Australia. Results highlight that pre-cooling produces cost saving for most of the days in 6-star and 8-star buildings. For 2-star buildings, pre-cooling sometimes leads to higher electricity costs. Moreover, pre-cooling improves thermal comfort, especially in 2-star light and medium weight buildings

Optimal Spline Generators for Derivative Sampling

The goal of derivative sampling is to reconstruct a signal from the samples of the function and of its first-order derivative. In this paper, we consider this problem over a shift-invariant reconstruction subspace generated by two compact-support functions. We assume that the reconstruction subspace reproduces polynomials up to a certain degree. We then derive a lower bound on the sum of supports of its generators. Finally, we illustrate the tightness of our bound with some examples

Application based multi-objective performance optimization of a proton exchange membrane fuel cell

An application-based multi-objective optimization approach is presented to acquire the best operation condition for a proton-exchange membrane fuel cell. The optimization is done for propulsion, power station, and portable applications, in which the recommended range for decision variables and importance level of the objective functions are taken into consideration for optimization to obtain more accurate and practical results. In the multi-objective optimization, from each important aspect of the performance, i.e., technical, economic, dimensional, and environmental aspects, one objective is selected. The effect of the maximum allowable (threshold) current density on both optimum decision variables and objective functions are also investigated to find the best value for that. The results reveal that increasing the maximum allowable current density leads to improvements in optimized values of all the objective functions. Moreover, the conducted sensitivity analyses determine that the best value for threshold current density for the propulsion and power station applications is 1.3 A cm−2 and for the portable application is 1.5 A cm−2. Furthermore, comparison of the results to the base case condition shows that values of the temperature, pressure, and voltage in power station are not affected by optimization, whereas substantial decrease in both propulsion and portable applications brings more level of safety. Similarly, objective functions, i.e., efficiency, levelized cost, size, and greenhouse emission are averagely improved by 9.93, 16.95, 37.13, and 7.77%, respectively. The proposed procedure helps to design and manufacture the high-performance proton-exchange membrane fuel cells based on the employed application and users’ preference

A Novel Temperature-Independent Model for Estimating the Cooling Energy in Residential Homes for Pre-Cooling and Solar Pre-Cooling

Australia’s electricity networks are experiencing low demand during the day due to excessive residential solar export and high demand during the evening on days of extreme temperature due to high air conditioning use. Pre-cooling and solar pre-cooling are demand-side management strategies with the potential to address both these issues. However, there remains a lack of comprehensive studies into the potential of pre-cooling and solar pre-cooling due to a lack of data. In Australia, however, extensive datasets of household energy measurements, including consumption and generation from rooftop solar, obtained through retailer-owned smart meters and household-owned third-party monitoring devices, are now becoming available. However, models presented in the literature which could be used to simulate the cooling energy in residential homes are temperature-based, requiring indoor temperature as an input. Temperature-based models are, therefore, precluded from being able to use these newly available and extensive energy-based datasets, and there is a need for the development of new energy-based simulation tools. To address this gap, a novel data-driven model to estimate the cooling energy in residential homes is proposed. The model is temperature-independent, requiring only energy-based datasets for input. The proposed model was derived by an analysis comparing the internal free-running and air conditioned temperature data and the air conditioning data for template residential homes generated by AccuRate, a building energy simulation tool. The model is comprised of four linear equations, where their respective slope intercepts represent a thermal efficiency metric of a thermal zone in the template residential home. The model can be used to estimate the difference between the internal free-running, and air conditioned temperature, which is equivalent to the cooling energy in the thermal zone. Error testing of the model compared the difference between the estimated and AccuRate air conditioned temperature and gave average CV-RMSE and MAE values of 22% and 0.3 °C, respectively. The significance of the model is that the slope intercepts for a template home can be applied to an actual residential home with equivalent thermal efficiency, and a pre-cooling or solar pre-cooling analysis is undertaken using the model in combination with the home’s energy-based dataset. The model is, therefore, able to utilise the newly available extensive energy-based datasets for comprehensive studies on pre-cooling and solar pre-cooling of residential homes

Lentiviral Expression of Rabies Virus Glycoprotein in the Rat Hippocampus Strengthens Synaptic Plasticity

“This is a pre-print of an article published in journal of Cellular and Molecular Neurobiology. The final authenticated version is available online at: https://doi.org/10.1007/s10571-020-01032-9"International audienceRabies virus (RABV) is a neurotropic virus exclusively infecting neurons in the central nervous system. RABV encodes five proteins. Among them, the viral glycoprotein (RVG) plays a key role in viral entry into neurons and rabies pathogenesis. It was shown that the nature of the C-terminus of the RABV G protein, which possesses a PDZ-binding motif (PBM), modulates the virulence of the RABV strain. The neuronal protein partners recruited by this PBM may alter host cell function. This study was conducted to investigate the effect of RVG on synaptic function in the hippocampal dentate gyrus (DG) of rat. Two μl (108 T.U./ml) of the lentiviral vector containing RVG gene was injected into the DG of rat hippocampus. After 2 weeks, the rat’s brain was cross-sectioned and RVG-expressing cells were detected by fluorescent microscopy. Hippocampal synaptic activity of the infected rats was then examined by recording the local field potentials from DG after stimulation of the perforant pathway. Short-term synaptic plasticity was also assessed by double pulse stimulation. Expression of RVG in DG increased long-term potentiation population spikes (LTP-PS), whereas no facilitation of LTP-PS was found in neurons expressing δRVG (deleted PBM). Furthermore, RVG and δRVG strengthened paired-pulse facilitation. Heterosynaptic long-term depression (LTD) in the DG was significantly blocked in RVG-expressing group compared to the control group. This blockade was dependent to PBM motif as rats expressing δRVG in the DG-expressed LTD comparable to the RVG group. Our data demonstrate that RVG expression facilitates both short- and long-term synaptic plasticity in the DG indicating that it may involve both pre- and postsynaptic mechanisms to alter synaptic function. Further studies are needed to elucidate the underlying mechanisms