Multi-objective optimization of solar photovoltaic shadings

What is it about?

Shading is one of the cases that has effectivity on the household energy consumption. Shadings can be used either in horizontal or vertical form adjacent to the building’s window in order to control the sunlight. In this paper, a multi-objective optimization is conducted to simultaneously reduce the annual electricity consumption and augment the electricity production with the application of photovoltaic shadings installed over the building window.To initiate the multi-objective optimization, four design variables based on the positioning and geometry of photovoltaic shading are selected and test samples are simulated through EnergyPlus software. The model is three-floor building located in Tehran, Iran. Next, the Morris sensitivity analysis (MSA) is implemented to calculate the extent to which each design variable affects the objective functions. Afterwards, the relation between the design variables and objective functions is extracted through the regression modeling using GMDH type-ANN and the equations extracted are then utilized as inputs for genetic algorithm to conduct a Pareto-based optimization. The results demonstrate that the maximum sunlight reception is attributed to the PV shading in southern direction of the building and its optimal tilt angle is 19.6 considering an annual period. There are slight changes to the tilt angle while seasonal period is considered for the calculations. The results also show that the use of solar shadings can reduce electricity consumption by approximately 4 to 11, 1 to 4, and 10 to 22% for an annual period, winter and summer season, respectively. At the end, the numerical data for the city of Tehran is compared to the cities of Canberra and Macapa.

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Photo by Asia Chang on Unsplash

Photo by Asia Chang on Unsplash

Why is it important?

Shading is one of the cases that has effectivity on the household energy consumption. Shadings can be used either in horizontal or vertical form adjacent to the building’s window in order to control the sunlight. In this paper, a multi-objective optimization is conducted to simultaneously reduce the annual electricity consumption and augment the electricity production with the application of photovoltaic shadings installed over the building window.To initiate the multi-objective optimization, four design variables based on the positioning and geometry of photovoltaic shading are selected and test samples are simulated through EnergyPlus software. The model is three-floor building located in Tehran, Iran. Next, the Morris sensitivity analysis (MSA) is implemented to calculate the extent to which each design variable affects the objective functions. Afterwards, the relation between the design variables and objective functions is extracted through the regression modeling using GMDH type-ANN and the equations extracted are then utilized as inputs for genetic algorithm to conduct a Pareto-based optimization. The results demonstrate that the maximum sunlight reception is attributed to the PV shading in southern direction of the building and its optimal tilt angle is 19.6 considering an annual period. There are slight changes to the tilt angle while seasonal period is considered for the calculations. The results also show that the use of solar shadings can reduce electricity consumption by approximately 4 to 11, 1 to 4, and 10 to 22% for an annual period, winter and summer season, respectively. At the end, the numerical data for the city of Tehran is compared to the cities of Canberra and Macapa. K E Y W O R D S annual electricity consumption, annual electricity production, genetic algorithm, GMDH type-ANN, multi-objective optimization, photovoltaic shading, tilt angle