Probabilistic Risk-Based Planning of Distributed Generation Units Using Multi Objective Hybrid Augmented Weighted ε-Constraint Approach

Utilization of Distributed Generation (DG) resources has increased dramatically in power systems due to economic and environmental benefits. Risk-based planning methods could manage the operational and economic risks at acceptable levels. In this paper a new probabilistic multi-objective risk-based DG planning method is proposed. In the proposed method, operation and investment costs minimization, reliability improvement, losses minimization, and operational risks minimization are considered. Uncertainties of wind generation and demand are modeled by using scenario tree and two stage method. The multi-objective problem is solved by using a combination of lexicographic optimization technique and hybrid augmented weighted ε-constraint approach. In addition, fuzzy satisfying criterion is used for decision making among Pareto solutions. Analyzing the numerical results validated that the proposed method has an appropriate and accurate performance in achieving the set of Pareto solutions. By analyzing the Pareto solutions, it is proved that by more investment on DG allocation, reduction of loss and operation risk could be appropriately achieved. Comprehensive risk analysis of wind energy generation and the curtailment of wind power are conducted under different cases. It is concluded that when the wind power injection increases the negative effects on the power system increase. Moreover, in case of considering wind power curtailment, the risk factor significantly reduced.