The idea of combining photovoltaic and solar thermal collectors (PVT collectors) to provide electrical and heat energy is an area that has, until recently, received only limited attention. Although PVTs are not as prevalent as solar thermal systems, the integration of photovoltaic and solar thermal collectors into the walls or roofing structure of a building could provide greater opportunity for the use of renewable solar energy technologies. In this study, the design of a novel building integrated photovoltaic/thermal (BIPVT) solar collector was theoretically analysed through the use of a modified Hottel-Whillier model and was validated with experimental data from testing on a prototype BIPVT collector.The results showed that key design parameters such as the fin efficiency, the thermal conductivity between the PV cells and their supporting structure, and the lamination method had a significant influence on both the electrical and thermal efficiency of the BIPVT. Furthermore, it was shown that 1
With the growing use of solar thermal energy systems and small scale photovoltaic power generation by domestic users, there is increasing need to develop intelligent controllers that allow these users to efficiently manage the energy generated by these systems. Ideally these intelligent controllers will be able to forecast the availability and magnitude of the solar resource to plan in advance for periods when the solar irradiance magnitude is small or unavailable. In addition, the method used to provide this forecast needs to be adaptable to a range of timescales and locations.With this in mind, this study examined the possibility of providing a 24-hour ahead forecast of hourly global solar irradiation in New Zealand using several approaches but with particular reference to nonlinear autoregressive recurrent neural networks with exogenous inputs (NARX).Hourly time series data for nine historic weather variables recorded over a three year period was Zealand. The results demonstrate the ability of the NARX approach to forecast irradiation values at a later time and across a number of different locations. As such it is foreseeable that such an approach could serve as the basis of a forecasting system in future intelligent controllers.
Abstract-The sizing of a stand-alone wind-photovoltaic-battery hybrid renewable energy system (HRES) is greatly influenced by socio-demographic factors however, few studies have examined how sociodemographic factors, as borne out by different electrical usage patterns, influence the size of HRESs. This paper investigates how these factors influence the optimal sizing of a stand-alone HRES using a hybrid optimization method to match the available renewable energy with the demand. In this regard, different energy usage patterns resulting from users socio-demographic profile have been investigated and used for the optimal sizing of a HRES. The results show that the electricity usage profile of a site has a significant impact on the sizing and design of the system. Further, the results illustrate that one can design a system that meets the demand profiles resulting from socio-demographic factors with a minimum unmet load; however, by optimizing systems to the users socio-demographic profile, significant cost savings can be made.
New Zealand transport accounts for over 40% of carbon emissions with private cars accounting for 25%. In the Ministry of Economic Development's recently released "New Zealand Energy Strategy to 2050" it proposed the wide scale deployment of electric vehicles as a means of reducing carbon emissions from transport. However, New Zealand's lack of public transport infrastructure and its subsequent reliance on private car use for longer journeys could mean that many existing battery electric vehicles (BEVs) will not have the performance to replace conventionally fuelled cars.
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