M. R. Baghayipour, A. Akbari Foroud,
Volume 8, Issue 1 (3-2012)
Abstract
This paper presents a method to improve the accuracy of DC Optimal Power Flow problem, based on evaluating some nodal shares of transmission losses, and illustrates its efficiency through comparing with the conventional DCOPF solution, as well as the full AC one. This method provides three main advantages, confirming its efficiency:
1- It results in such generation levels, line flows, and nodal voltage angles that are more accurate than the conventional DCOPF solution.
2- Like the previous DCOPF problem, the new method is derived from a non-iterative DC power flow algorithm, and thus its solution requires no long run time.
3- Its formulation is simple and easy to understand. Moreover, it can simply be realized in the form of Lagrange representation, makes it possible to be considered as some constraints in the body of any bi-level optimization problem, with its internal level including the OPF problem satisfaction.
M.a Armin, H Rajabi Mashhadi,
Volume 11, Issue 4 (12-2015)
Abstract
Wind energy penetration in power system has been increased very fast and large amount of capitals invested for wind farms all around the world. Meanwhile, in power systems with wind turbine generators (WTGs), the value of Available transfer capability (ATC) is influenced by the probabilistic nature of the wind power. The Mont Carlo Simulation (MCS) is the most common method to model the uncertainty of WTG. However, the MCS method suffers from low convergence rate. To overcome this shortcoming, the proposed technique in this paper uses a new formulation for solving ATC problem analytically. This lowers the computational burden of the ATC computation and hence results in increased convergence rate of the MCS. Using this fast technique to evaluate the ATC, wind generation and load correlation is required to get into modeling. A numerical method is presented to consider load and wind correlation. The proposed method is tested on the modified IEEE 118 bus to analyze the impacts of the WTGs on the ATC. The obtained results show that wind generation capacity and its correlation with system load has significant impacts on the network transfer capability. In other words, ATC probability distribution is sensitive to the wind generation capacity.
