Wind Farm Placement in Order to Congestion Management using Generation Shift Distribution Factors

Seyyed Zeinolabedin Moussavi, Ali Badri, and Fazlolah Rastegar Kashkooli


Wind Farm, Probabilistic Optimal Power Flow, Point Estimate Methods, Congestion Management, Weibull Distribution


Wind farms (WF) with high level of penetration have established in power systems worldwide more rapidly than other renewable resources. Due to increment in energy demands, congestion in transmission lines becomes frequent. In this paper, efficient method is proposed for locating WFs in order to reduce the loads on congested lines. Normal distribution is assumed for loads to determine the vulnerable lines to congestion. For this purpose, AC probabilistic optimal power flow (P-OPF) is formulated and solved using Monte Carlo simulations (MCS). In addition, point estimate methods (PEMs) are used as efficient alternatives for time-demanding MCS. After recognizing the line(s) with high probability of congestion, generation shift distribution factors (GSDF) associated with those lines are calculated. These GSDFs show that injection at which bus would reduce the flow at concerned lines. Stochastic nature of wind speed has been modeled by normal and Weibull distributions in order to include the uncertainties associated with WFs output power in power system studies. It is shown that 3PEM is the best alternative for MCS with highest accuracy and lowest time consumption, compared to other PEMs. The proposed methodologies have been tested in 6-Bus and as well as 30-Bus test systems and the simulation results are provided.

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