With the solar power panels as integrated surface elements in new building constructions, solar power will be economic attractive in urban areas, close to the power consumption. In the new dense urban areas, the rooftop areas will be attractive for other purposes, like terraces and green roofs. The solar power panels may instead be placed at the facades of the buildings – this is especially relevant at high geographic latitudes, where the altitude of the sun is low. It may even make sense to mount panels at all facades, better distributing the generation over the day.

This study proposes an improved single-diode modelling approach for photovoltaic (PV) modules suitable for a broad range of the PV technologies available today, including modules based on tandem cell structures. After establishing the model (which has an overall of seven parameters), this study devises a methodology to estimate its parameters using Standard Test Conditions (STC) data, Nominal Operating Cell Temperature (NOCT) data, and temperature coefficient values as provided in most manufacturers’ datasheets. Simulation results and their comparison with a previous work show a very accurate prediction of critical points in the current-voltage characteristics curve. The precise prediction happens for both STC and NOCT conditions and the error in predicting maximum power point (MPP) lies within 1% limit, and the error in its corresponding voltage and current is almost always within 2% limit. Further, for both MPP and open-circuit voltage, the statistical variance around manufacturer measurements due to temperature changes is demonstrated to be low for five various module technologies.

Most issue for a large-scale photovoltaic (PV) array shows an average loss of ∼20–25% in power generation yield due to partial shadow. Under partially shaded conditions, a PV array gets more complex characteristics. However, it is very difficult to understand and predict them since PV module has non-linear characteristic and it is also utterly necessary for one to extract the maximum possible power. This study presents the partial shading analysis and simulation approach to unveil the significant basic rules for estimating performances of a large-scale PV array. By using the macro-model and simplified parameter estimation formulas of the PV module proposed in part I, this study has made the following contributions: (i) basic and general shading patterns of PV string and array are proposed to unveil the basic rules, such as the count of maximum power points (MPP), magnitude of the global MPP, overall shape of V–I and V–P curves, and so on. (ii) The optimising configuration-simulation model are developed for a distributed PV system designed to optimise PV array configuration under a given shaded patterns. By using a Dell compatible personal computer to run Psim programs, it takes ∼15 minims to get the V–I and V–P curves of a partially shaded PV array with 1050 commercial PV modules. Furthermore, this study attempts to provide a simulation tool to study the behaviours of a complete PV system since the Psim-based models conveniently interface with the models of power electronic circuit.

replace with: Currently, the impacts of wide-scale implementation of photovoltaic (PV) technology are evaluated in terms of such indicators as rated capacity, energy output or return on investment. However, as PV markets mature, consideration of additional impacts (such as electricity transmission and distribution infrastructure or socio-economic factors) is required to evaluate potential costs and benefits of wide-scale PV in relation to specific policy objectives. This study describes a hybrid GIS spatio-temporal modelling approach integrating probabilistic analysis via a Bayesian technique to evaluate multi-scale/multi-domain impacts of PV. First, a wide-area solar resource modelling approach utilising GIS-based dynamic interpolation is presented and the implications for improved impact analysis on electrical networks are discussed. Subsequently, a GIS-based analysis of PV deployment in an area of constrained electricity network capacity is presented, along with an impact analysis of specific policy implementation upon the spatial distribution of increasing PV penetration. Finally, a Bayesian probabilistic graphical model for assessment of socio-economic impacts of domestic PV at high penetrations is demonstrated. Taken together, the results show that integrated spatio-temporal probabilistic assessment supports multi-domain analysis of the impacts of PV, thereby providing decision makers with a tool to facilitate deliberative and systematic evidence-based policy making incorporating diverse stakeholder perspectives.