Probabilistic Placement of Wind Turbines in Distribution Networks

Abstract

This study presents an efficient approach for determining the optimal locations of wind turbines (WTs) in distribution systems, which considers the existing uncertainties in the power generation of WTs and the load demand of consumers. The daily load profiles of the seasonal and geographical-dependent behaviors of WTs are also considered. The proposed probabilistic approach is based on scenario tree modeling, and each scenario is assessed in regard to power loss minimization. Then, the TOPSIS (technique for order preference by similarity to an ideal solution) method is adopted to regulate the optimal placement of WTs considering the average value and the standard deviation of active power losses as possible attributes. This approach enables a multi-attribute analysis of the search space to yield a more efficient solution. Detailed simulation studies, conducted on IEEE 33-bus test system, are utilized to examine the effectiveness of the proposed method. The results of this study are discussed in depth.

Probabilistic Energy Management of DGs and Electric Vehicle Parking Lots in a Smart Grid considering Demand Response

“…Figure 7 illustrates the test system employed as a microgrid (MG) in this study [41][42][43]. The understudy microgrid incorporates two 500 kW WTs located at bus 15 and bus 21, as well as two 500 kW PV arrays situated at buses 9 and 30.…”

Optimal probabilistic operation management of smart parking lot and renewable sources in microgrid to reduce cost and improve system reliability considering demand response program

“…Finally, the local search is performed by the leader projectile, which indicates the best projectile position of N step leader. The PDF of the standard uniform distribution can be represented as Equation (42).…”

“…In the proposed MG, two 500 kW wind turbines on buses 15 and 21 and the two 500 kW photovoltaic units on buses 9 and 30 are used. Also, six 500 kW parking lots on buses 5, 12, 17, 19, 24, and 28 are accumulated in MG. [41][42][43] The wind speed and solar radiation data are taken of the McHenry precinct of the North Dakota region. 44 Also, forward-backward sweep (FBS) is used for the load flow.…”