A. H. Foomani - Department of Electrical Engineering, Zanjan Branch, Islamic Azad University, Zanjan, Iran
M. Moradlou - Department of Electrical Engineering, Zanjan Branch, Islamic Azad University, Zanjan, Iran
P. Nazarian - Department of Electrical Engineering, Zanjan Branch, Islamic Azad University, Zanjan, Iran

Equipping renewable energy resources generation units in the distribution network to reduce economical and emission concerns are the examples of active distribution network(ADN). The other advantages of utilizing distributed generators (DGs) are improving technical constraints of ADN. In this paper multi-benefit functions are defined as main functions. Each of functions illustrates the positive impacts of utilizing wind turbines in the improving technical constraints of the ADN. Voltage stability (VS) is one of the main technical indices of the ADN. Several VSIs are defined to evaluate voltage stability of the ADN. The previous indices could not give the proper results about allocating DGs and accurate evaluating of voltage stability of ADN. This work proposes the new VSI. To this aim active power loss (APL), reactive power loss (RPL) and voltage stability index (VSI) are considered as technical constraints. In order to evaluate the presence of WT on improving APL and RPL, WTs are considered in two operational modes; unified power factor (UPF) and (APF). The main benefit function is solved by implementing genetic algorithm (GA). Multiplying weights to the APL, RPL and VSI (which are improved by attendance WTs) in benefit function formulation, make the multi-criteria decision formation to the proposed optimization problem. By employing analytical hierarchy process (AHP) technique and considering each technical constraints as main criteria, the obtained solutions are arranged. To verify the positive effectiveness of the proposed VSI, its results are compared with the results of other VSIs in the ۳۳, ۶۷ and ۱۱۸ bus IEEE radial DN.

Voltage Stability Index, Analytical Hierarchy Process, Active distribution network, multi-ceria decision formation, Wind Turbine