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Integrated building photovoltaic panels (BIPV) can be used to receive solar energy. BIPVs are divided into different groups, PV-sunshade (PVSDS) type of which is targeted in present study. PVSDS can be used in residential buildings to contribute significantly to the economic costs of the building by saving the building's electricity consumption. The use of solar panels in buildings is useful when it is economically viable. For this purpose, in this study, a multi-objective optimization is performed to simultaneously reduce the annual cost of electricity consumption and the cost of installing window glass and PV system by applying photovoltaic shadows installed on the building window. To initiate multi-objective optimization, six design variables based on the position and geometry of the photovoltaic shade are selected and energy simulations are performed through EnergyPlus software for 5 cities with different climates in Europe. Design variables and objective functions are identified in JEPLUS (Java+ EnergyPlus) software, then the NSGA-II algorithm is employed for optimization which results in the several optimal points on a Pareto Front. Based on the climatic condition of the city, a specific optimal point on the Pareto Front is attributed to that city. The results show that 17 to 34 % in the cost of electricity consumption of the building is saved by choosing a suitable solar shading between. Also, the static payback period is obtained in a period of 1.5 to 6 years for different cities. It is also construed that the tilt angle of PV shading in cities that are further from the equator is higher. • Six design variables based on geometry and position of photovoltaic shading were considered as the inputs. • The objective functions for the building model in different European cities were optimized in a range of 17-34%. • It was shown that the ideal tilt angle of the photovoltaic shading has risen while increasing the distance from the equator. • The static payback period of the costs of installing the photovoltaic shading in each city was calculated. [ABSTRACT FROM AUTHOR]