This study evaluates the most effective method to maximize the voltage stability margin in two simulated microgrids under seven different scenarios, 33 and 69 IEEE RTS models. Three different evolution algorithms are used to improve the voltage stability margin. Moreover, other power system indices such as voltage profile improvement and reducing the power losses are considered in the presented simulations. Power system limitations such as power flow restriction, line heat capacity, power transmission capacity through the line as well as voltage variation constraint are viewed to make the simulation more realistic. This paper presents solar-wind DGs, Dstatcom and capacitor placement and sizing separately as well as simultaneously. The main objective of this study is to achieve the maximum voltage stability margin in microgrids and its comparison by three different evolutionary algorithms, particle swarm optimization (PSO), genetic algorithm (GA) and honey bees mating optimization (HBMO). In the first stage, GA is applied on all seven scenarios. After selecting the best combination of the devices which creates the maximum voltage stability margin, the combination is also studied using two other evolutionary algorithms, PSO and HBMO.
