Abstract
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 power outage. 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.
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