Title :
Identification of power injection capabilities for transmission system investment optimization
Author :
Ergun, Hakan ; Van Hertem, Dirk ; Belmans, Ronnie
Author_Institution :
Dept. of Electr. Eng. (ESAT), Univ. of Leuven, Heverlee - Leuven, Belgium
Abstract :
In this paper, method to identify strong nodes in a transmission grid is shown. The method can be used to identify transmission system investment needs and can serve as filter for transmission system investment optimization. Based on an optimal power flow calculation, the maximum power injection capability of buses is calculated. In this context AC OPF and DC OPF methods are compared in terms of accuracy, convergence and computational effort. To take uncertainties in generation and load into account, the Gaussian Component Combination Method (GCCM) is used, which is compared to Monte Carlo Simulation (MCS). The importance of considering security aspects while determining strong nodes is depicted using N-1 analysis. Additionally, the effect of power flow controlling devices on the maximum power injection capability of investigated grid nodes is shown, in particular with phase shifting transformers and HVDC links.
Keywords :
Gaussian processes; Monte Carlo methods; investment; load flow; optimisation; power transmission economics; AC OPF method; DC OPF method; Gaussian component combination method; HVDC links; Monte Carlo simulation; N-1 analysis; grid nodes; maximum power injection capability; optimal power flow calculation; phase shifting transformers; power flow controlling devices; power injection capabilities; transmission grid; transmission system investment optimization; Europe; Generators; HVDC transmission; Investment; Optimization; Probabilistic logic; Security; Gaussian Component Combination Method; HVDC; Maximum power injection capability; Probabilistic Power Flow; Transmission System Investments;
Conference_Titel :
PowerTech (POWERTECH), 2013 IEEE Grenoble
Conference_Location :
Grenoble
DOI :
10.1109/PTC.2013.6652223