Probabilistic assessment of wind turbine impact on distribution networks using linearized power flow formulation

摘要

The attractiveness of renewable energy resources has convinced the power system operators to utilize their cheap brought up energy as much as possible. Continuously, the integration of renewables, especially wind based ones, has been followed up in distribution networks as well as transmission scale. The main challenge that comes up with increasing of this integration is uncertain generation of these resources, which affects the networks parameters and optimization strategies. Consequently, studying the approaches, which focus on handling these uncertainties deserve special consideration. Two main features of time and accuracy are the most important evaluation criteria of these methods. The most accurate approach of Monte Carlo simulation suffers from high computational time, which makes it inapplicable to problems, which needs more swiftness. In the other hand, decreasing the time increase the results error that may cause to incorrect decisions. In this atmosphere, proposing a method, which provides suitable trade-off between these two criteria, can be so valuable. This paper, proposes the utilization of a set of accurate linear power flow equations in simulation of probabilistic methods, which brings out so considerable swiftness. In this paper, the linear power flow equations have been proposed for modeling the distribution network instead of typical Newton-Raphson approach, which decrease the computation time per each simulation. Implementation of these equations in MCS method results in lower error in compare with the well-known approaches of two points estimate and Latin hypercube sampling methods where its swiftness is compatible with them. Using proposed equations in two points estimate method and Latin hypercube sampling methods makes them so faster which prepare them for online probabilistic analysis of distribution network. Finally, two standard test systems of IEEE 33-bus and 69-bus have been employed for validation of proposed method.