Methodologies and tools for BiPV implementation in the early stages of architectural design.

Photovoltaic technology is among the best tools our civilization has to reduce the emissions of greenhouse gas that are currently altering the atmosphere composition of our planet. The idea of using photovoltaic surfaces on the envelope of buildings is called with the acronym of BIPV (building integrated photovoltaics), it offers the advantage of producing energy in the same location of the demand for electricity. Furthermore, BIPV allows to save monetary and environmental costs by substituting building materials with photovoltaic collectors. As every technology,BIPV follows an adoption pattern that is bringing it from a very limited niche product to a pervasive one. Nevertheless, the adoption rate of BIPV appears to be slow, and the industry has offered little opportunities of business for its stakeholders over the last 20 years. There are multiple reasons for this sluggish growth, and a considerable body of scientific literature has offered potential solutions to the problem. The building industry is notoriously slow in picking up innovation, furthermore the BIPV material needs to compete with much more mature, versatile and often cheaper cladding technologies and materials. Numerous research endeavors are focusing on the development of new BIPV claddings to have diversified colors, dimensions, shapes and other properties. The argument is that the technology is not mature and thus cannot be adopted by the bulk of architects and designers. Unfortunately, the premium characteristics of these new materials often come with a higher price and a reduced efficiency, thus reducing their market potential. Other research endeavors, among which this thesis, are focusing on the design of buildings: trying to include the use of photovoltaics into the architectural practice through education and software development. Numerous software has been developed over the last 20 years with the aim of calculating the productivity or the economic outlook of a BIPV system. The main difference between the existing software and the method presented here lies in the following fact: previously, the capacity and positions of a BIPV system are required as input for the calculation of performance, in this method the capacity and positions of the BIPV system are given as the output of an optimization process. A designer whois skeptical or disengaged about the use of BIPV could be induced to avoid its use entirely by the discouraging simulation results given by the lack of a techno-economic optimal configuration. Conversely, a designer who opt for a premium architectural PV material would, thank to the methodology shown, be able to assess the impact its unitary cost has on the optimal BIPV capacity of the building. Ultimately, the method presented provides new knowledge to the designer regarding the use of BIPV on his building, hopefully this can facilitate the spread of BIPV technology. The method described was translated into a software tool to find the best positions and number of PV surfaces over the envelope of the building and the best associated battery capacity. The tool is based on the combined use of ray-tracing (for irradiation calculation) and optimization algorithms, its use led to the following conclusions: • BIPV is profitable under a wide range of assumptions if installedin the correct capacities • 20% of the residential electric demand can easily be covered by PV without the need for electric storage and in a profitable way • Despite an interesting rate of return of the investment, the payback time was generally found to be long (over 10 years) • More research is needed to assess the risk on the investment on BIPV: if found to be low, future financial mechanisms could increase its spread despite the long payback time • The optimal capacity in energy terms (i.e. the energy consumed on-site minus the energy used to produce a BIPV system) tends to be far higher than any techno-economic optimum • The specific equivalent CO2 emissions for an NPV optimal system have been found to be between 70 and 123 [kg CO2 eq/MWh] under the range of assumptions applied • The installation of optimal BIPV capacity could change the overall residential CO2 emission of -12%, +13%, -29% in England, France and Greece respectively • despite the non optimal placement of a BIPV system compared to a ground mounted, south oriented one, and despite the noncontemporaneity of production and consumption, the BIPV still easily outperforms the energy mix of most countries when optimized for maximum NPV. • The part of the building envelope that have the most annual irradiation (i.e. the roof) should not necessarily host the entirety of the system as other facades might have an advantage in terms of matching production and consumption times. • when different scenarios are made in terms of techno-economic input parameters (e.g. degradation of the system, future costs of maintenance, future variation of electricity price etc..) larger capacities are optimal for optimistic outlooks and vice-versa • the optimal capacity for the expected scenario (i.e. the 50 % ile) can be considered robust as it performs close to the optimum in optimistic and pessimistic scenarios alike. • a reduction in price for the electric storage appears to have a positive effect on the optimal capacity of PV installed for the case study considered. • when a group of households is optimized separately V.S. aggregated together, the aggregation have a huge positive effect on all KPIs of the resulting system: in the NPV optimal system of a case study examined the installed capacity ( +118%), the NPV ( +262.2%) and the self-sufficiency( +51%) improved thanks to aggregation.