A cost-benefit analysis for reconfigurable PV modules under shading
Introduction
In recent years, the Photovoltaic (PV) market has expanded and PV arrays are installed in locations which are considered far from ideal. Building-Integrated PhotoVoltaics (BIPV), Building-Applied Photovoltaics (BAPV) and solar vehicles are increasing, leading to a plethora of PV plants which are operating under non-uniform conditions (Kumar et al., 2018, LIGHTYEAR, 2018, Salfiti, 2018).
Such non-uniformity can happen at different levels and can be due to different causes. For instance, installation of PV modules on different facades of a building, as well as on different parts of a vehicle, leads to non-uniformity between the PV modules. Furthermore, objects belonging to or surrounding a given building (e.g. chimneys or trees) can cast shades onto only a part of a PV module, thus moving the non-uniformity to a sub-module level (Shukla et al., 2016, Biyik et al., 2017). This can be even worse for solar vehicles, where the casted shade continuously changes while the vehicle is moving depending on the environment (usually urban) and the direction of the vehicle motion. Partial shading can be either dynamic or static. Dynamic shading can be caused by static objects (trees, chimneys) or by moving objects (clouds). Static shading is caused mainly due to soiling, but also bird dropping as well as localized degradation of PV modules creates static shading (Wohlgemuth et al., 2013). Operation under non-uniform conditions causes poor performance of standard series connected conventional modules (Teo et al., 2018).
A possible approach to mitigate the effects of partial shading and non-uniform conditions within the module is by allowing reconfiguration within the module and enabling control in the submodule level. The benefits of reconfigurable module topologies for static shading patterns have been discussed in Baka et al., 2014, Baka et al., 2016. It is shown that reconfigurable modules can recover lost power during conditions of partial shading, but produce less energy than conventional topologies under uniform operating conditions. Clearly, reconfigurable modules can be beneficial when non-uniform conditions are sufficiently present. However, this earlier work does not allow yet to quantitatively identify under what conditions gains extend beyond costs. To illustrate the potential long-term benefits of reconfigurable topologies, the performance of PV modules needs to be evaluated in realistic and dynamic shading scenarios over a longer period of time, thus a detailed simulation is required which includes time-varying effects. Ideally, one full year should be simulated, in order to account for variability of both overall irradiance and shading pattern. Results of a full year simulation can be extended to the following years by considering typical degradation rate of solar panels and power converters. Also, the cost introduced by extra components of reconfigurable modules should be taken into account.
To address this gap, in this work, an energy vs cost analysis is performed for the reconfigurable modules with a snake-like configuration previously introduced in Baka et al., 2014, Baka et al., 2016. Realistic shading scenarios are considered and the recovered energy is compared to the expected cost. It is worth to note that, although the discussion will focus on reconfigurable PV modules with a snake-like configuration, the methodology can be applied for any other module topology. This paper is organized as follows. In Section 2, works which focus on the mitigation of non-uniform conditions in the PV array are presented. The cost aspects which are considered for the design of reconfigurable modules are discussed in Section 3, where both design-time and run-time instantiations of reconfigurable modules which are considered in this work are presented too. The simulation framework, the shading scenarios and the simulation results in terms of energy are shown in Sections 4 Simulation framework, 5 Simulation results. The investment cost of these topologies is discussed in Section 6, and an estimation of the financial gain is made in Section 7. Conclusion ends the paper.
Section snippets
Optimization of performance under partial shading: review of different approaches
Several studies focus on the optimization of the performance of PV installations under conditions of partial shading. Depending on the method applied to deal with non-uniformity, such studies can be classified in three main categories: (I) work focusing on improvement of system components, (II) work focusing on alteration of the interconnection of the PV array and (III) work focusing on introduction of extra elements in the PV array.
Improving system components, such as solar cell’s efficiency
Design criteria for reconfigurable modules
The goal of our approach is to increase the overall energy yield of a PV module by enabling control in the submodule level. It is evident that additional elements required for the fabrication of reconfigurable modules increase the manufacturing cost. Furthermore, the added elements in the active current path induce power losses which must be taken into account. The way cost and gain relate each other is fundamental for designing reconfigurable modules. Such relationship between cost and gain is
Simulation framework
In order to estimate the accumulated gain and losses which are mentioned in Section 3, the overall energy of the module needs to be computed. The evaluation of the performance of the module topologies is done through simulation. This allows the comparison of different configurations of the module under the exact same external conditions. In Manganiello et al. (2017) a simulation setup is developed which allows an accurate comparison of energy generation of different PV module topologies under
Effect of diffuse irradiation
When DHI is completely blocked by objects (x = 1), the irradiation differences within the module are larger and the degree of non-uniformity within the module is highest, out of all the three cases. As fully shaded cells do not receive any irradiation, they do not contribute to power generation. In conventional modules this means that when not all bypass sections are affected, the bypass diodes of the shaded sections are active as to not compromise the operation of the rest of the module.
Investment cost
In an instantiation of a snake topology with X cell-strings, the numbers of added discrete elements are shown in the Table 5. One column shows the added elements for a generic template with X cell-strings, while the other shows the discrete elements which have been added for the configurations examined in detail in this work. Three different types of switches are present in the table. The distinction is made based on their use and the conditions that they should withstand when they are active
Energy vs cost
In order to estimate the energy recovered throughout the year, the energy produced by a conventional module working for a full year under uniform conditions has been evaluated by simulation. For the conventional module used in this work, this value is equal to 162.70 kWh. Based on both this value and the average losses due to partial shading in each shading scenario, the annual energy produced by the conventional module for each shading scenario has been evaluated. Finally, by applying the
Conclusion
The potential benefit of reconfigurable PV modules in installations where non-uniform conditions are prevalent has been explored. Operation under three different shading scenarios has been considered and the performance of reconfigurable topology has been benchmarked to the one of conventional modules. A cost function has been defined and used for estimation of financial gain, so that it has been possible to analyse the potential benefit of reconfigurable solution in both energy and financial
Acknowledgment
This project has received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement No. 751159. Imec is a partner in EnergyVille (www.energyville.be), a collaboration between the Flemish research partners KU Leuven, VITO, imec, and UHasselt in the field of sustainable energy and intelligent energy systems.
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