Offshore floating photovoltaics system assessment in worldwide perspective

Floating solar photovoltaics (FPV), whether placed on freshwater bodies such as lakes or on the open seas, are an attractive solution for the deployment of photovoltaic (PV) panels that avoid competition for land with other uses, including other forms of renewable energy generation. While the vast majority of FPV deployments have been on freshwater bodies, in this paper, we chose to focus on offshore FPV, a mode of deployment that may be particularly attractive to nations where the landmass is constricted, such as is the case in small islands. There is a wide perception that seawater cooling is the main reason for the enhanced performance of offshore FPV panels. In this paper, a worldwide assessment is made to validate this perception. To this end, a technology-specific heat transfer model is used to calculate PV system performance for a data set of 20 locations consisting of one system located on land and another one offshore. The analysis assumes that the floating offshore panels are placed on metal pontoons and that all panels are based on monocrystalline silicon technology. Our analysis shows that the energy yield difference, between land-based and offshore systems, for the time period of 2008 and 2018, varies between 20% and −4% showing that offshore FPV yield advantages are site-specific. In addition, the effect of other environmental factors, namely, irradiation level difference, ambient temperature, wind speed, precipitation, and sea surface temperature, is studied in this paper, which leads to the formulation of two different regression models. These can be used as a first step in predicting yield advantages for other locations

Simulation of performance differences between offshore and land-based photovoltaic systems

Abstract The purpose of this study is to model, simulate, and compare the performance of a photovoltaics system on land and at sea. To be able to have a fair comparison the effect of sea waves, wind speed and relative humidity are considered in this model. The sea waves are modeled in the frequency domain, using a wave spectrum. The irradiation on a tilted surface for a floating system is calculated considering the tilt angle that is affected by the sea waves. Moreover, the temperature is estimated based on heat transfer theory and the natural cooling system for both floating and land-based photovoltaic systems. Actual measured weather data from two different locations, one located at Utrecht University campus and the other one on the North Sea, are used to simulate the systems, thus making the comparison possible. Energy yield is calculated for these weather conditions. The results show that the relative annual average output energy is about 12.96% higher at sea compared with land. However, in some months, this relative output energy increases up to 18% higher energy yield at sea

Proof of Concept for a Novel and Smart Shade Resilient Photovoltaic Module

In this study, the performance of a shade resilient smart module is studied under a dynamic shading pattern. A smart module architecture is developed to mitigate the non-linear shading effect on the module performance. Partial shading decreases the output current of the shaded cells and affects the unshaded cells’ output power. After distributing the module cells into small groups, based on a least square support vector machine optimisation method, DC–DC buck converters compensate the decreased current levels, by adjusting the output current and voltage level from any individual group of cells. The system is simulated in the MATLAB Simulink environment, and the output results are presented. Results show that the module performs efficiently and output power of the unshaded groups of cells never decreased because of the effect of shading on the other groups. Additionally, the maximum output power is harvested from all groups simultaneously. Prototype hardware is designed and built to implement the proof of concept. The real-time results of hardware testing show that the smart module performs as expected and mitigates partially shaded conditions by extracting maximum power from each group, regardless of other groups shading condition

Proof of Concept for a Novel and Smart Shade Resilient Photovoltaic Module

In this study, the performance of a shade resilient smart module is studied under a dynamic shading pattern. A smart module architecture is developed to mitigate the non-linear shading effect on the module performance. Partial shading decreases the output current of the shaded cells and affects the unshaded cells’ output power. After distributing the module cells into small groups, based on a least square support vector machine optimisation method, DC–DC buck converters compensate the decreased current levels, by adjusting the output current and voltage level from any individual group of cells. The system is simulated in the MATLAB Simulink environment, and the output results are presented. Results show that the module performs efficiently and output power of the unshaded groups of cells never decreased because of the effect of shading on the other groups. Additionally, the maximum output power is harvested from all groups simultaneously. Prototype hardware is designed and built to implement the proof of concept. The real-time results of hardware testing show that the smart module performs as expected and mitigates partially shaded conditions by extracting maximum power from each group, regardless of other groups shading condition

Simulation of performance differences between offshore and land-based photovoltaic systems

Abstract The purpose of this study is to model, simulate, and compare the performance of a photovoltaics system on land and at sea. To be able to have a fair comparison the effect of sea waves, wind speed and relative humidity are considered in this model. The sea waves are modeled in the frequency domain, using a wave spectrum. The irradiation on a tilted surface for a floating system is calculated considering the tilt angle that is affected by the sea waves. Moreover, the temperature is estimated based on heat transfer theory and the natural cooling system for both floating and land-based photovoltaic systems. Actual measured weather data from two different locations, one located at Utrecht University campus and the other one on the North Sea, are used to simulate the systems, thus making the comparison possible. Energy yield is calculated for these weather conditions. The results show that the relative annual average output energy is about 12.96% higher at sea compared with land. However, in some months, this relative output energy increases up to 18% higher energy yield at sea

Improvement of Shade Resilience in Photovoltaic Modules Using Buck Converters in a Smart Module Architecture

Partial shading has a nonlinear effect on the performance of photovoltaic (PV) modules. Different methods of optimizing energy harvesting under partial shading conditions have been suggested to mitigate this issue. In this paper, a smart PV module architecture is proposed for improvement of shade resilience in a PV module consisting of 60 silicon solar cells, which compensates the current drops caused by partial shading. The architecture consists of groups of series-connected solar cells in parallel to a DC-DC buck converter. The number of cell groups is optimized with respect to cell and converter specifications using a least-squares support vector machine method. A generic model is developed to simulate the behavior of the smart architecture under different shading patterns, using high time resolution irradiance data. In this research the shading patterns are a combination of random and pole shadows. To investigate the shade resilience, results for the smart architecture are compared with an ideal module, and also ordinary series and parallel connected architectures. Although the annual yield for the smart architecture is 79.5% of the yield of an ideal module, we show that the smart architecture outperforms a standard series connected module by 47%, and a parallel architecture by 13.4%