Background: Modern power system operations often faced with very unsafe conditions
caused by voltage stability problems. If the problem cannot be controlled with the right method, then
a cascade system can occur. This condition can cause a voltage reduction drastically and leads to a
Objective: The Fast Voltage Stability Index (FVSI) and Line Stability Factor (LQP) implemented in
this study. Both indices can determine the optimal location and capacity of wind energy (WE) into
the grid to anticipate a sustained increase in load.
Method: One type of optimization method, a new variant of Genetic Algorithms, is used to solve the
multi-objective optimization problem known as Genetic Algorithm Sorting Non-Domination Sorting
II (NSGA-II). This algorithm can determine the optimal location and WE's capacity into the grid by
minimizing line power loss (Ploss) of power system with a system load increase scenario. Bus voltage
security, thermal line limits, and stability system are used as obstacles to maintain the system in a
safe condition due to the increasing the maximum load.
Results: The method suggested in this paper has been adequately tested on modification of the IEEE
14-bus standard test system connected to the WE. The WE integrated into the grid modeled using the
Power System Analysis Toolbox (PSAT). Based on the multi-objective manner, the method developed
can determine the best location and capacity of the WE simultaneously by minimizing Ploss with
SLI and satisfied all the system's security and stability constraints.
Conclusion: The technique provides well-distributed non-dominated solutions and well exploration
of the research space.