Showing 4 results for Contingency
M. Esmaili, H. A Shayanfar, N. Amjady,
Volume 6, Issue 1 (3-2010)
Abstract
Congestion management in electricity markets is traditionally done using deterministic values of power system parameters considering a fixed network configuration. In this paper, a stochastic programming framework is proposed for congestion management considering the power system uncertainties. The uncertainty sources that are modeled in the proposed stochastic framework consist of contingencies of generating units and branches as well as load forecast errors. The Forced Outage Rate of equipment and the normal distribution function to model load forecast errors are employed in the stochastic programming. Using the roulette wheel mechanism and Monte-Carlo analysis, possible scenarios of power system operating states are generated and a probability is assigned to each scenario. Scenario reduction is adopted as a tradeoff between computation time and solution accuracy. After scenario reduction, stochastic congestion management solution is extracted by aggregation of solutions obtained from feasible scenarios. Congestion management using the proposed stochastic framework provides a more realistic solution compared with the deterministic solution by a reasonable uncertainty cost. Results of testing the proposed stochastic congestion management on the 24-bus reliability test system indicate the efficiency of the proposed framework.
D. S. Javan, H. Rajabi Mashhadi,
Volume 7, Issue 4 (12-2011)
Abstract
Deregulation of power system in recent years has changed static security assessment to the major concerns for which fast and accurate evaluation methodology is needed. Contingencies related to voltage violations and power line overloading have been responsible for power system collapse. This paper presents an enhanced radial basis function neural network (RBFNN) approach for on-line ranking of the contingencies expected to cause steady state bus voltage and power flow violations. Hidden layer units (neurons) have been selected with the growing and pruning algorithm which has the superiority of being able to choose optimal unit’s center and width (radius). A feature preference technique-based class separability index and correlation coefficient has been employed to identify the relevant inputs for the neural network. The advantages of this method are simplicity of algorithm and high accuracy in classification. The effectiveness of the proposed approach has been demonstrated on IEEE 14-bus power system.
M. Ghayeni,
Volume 15, Issue 4 (12-2019)
Abstract
In this paper, the new approach for the transmission reliability cost allocation (TRCA) problem is proposed. In the conventional TRCA problem, for calculating the contribution of each user (generators & loads or contracts) in the reliability margin of each transmission line, the outage analysis is performed for all system contingencies. It is obvious that this analysis is very time-consuming for large power systems. This paper suggests that this calculation should be done only for major contingencies. To do this, at first, the contingency filtering technique (CFT) is introduced based on the new economic indices that quantify the severity of each contingency to determine the critical contingencies. Then the results of contingency filtering are used in the TRCA problem. The simulation results are reported for the IEEE 118-bus test system. The obtained results show that by application of CFT in TRCA problem, the simulation time is greatly reduced, but the percentage of error remains within an acceptable limit.
S. M. Alavi, R. Ghazi,
Volume 18, Issue 1 (3-2022)
Abstract
One of the significant concerns in the MTDC systems is that voltage source converters (VSCs) do not hit their limits in the post-contingency conditions. Converters outage, DC line disconnection, and changeable output power of wind farms are the most common threats in these systems. Therefore, their destructive impact on neighboring AC systems should be minimized as much as possible. The fixed droop control is a better choice than others to deal with this, although it also has some limitations. Accordingly, a novel centralized droop-based control strategy considering N-1 contingency is proposed in this paper. It prevents converters from exceeding their limits while causes optimal power sharing and minimum DC link voltage deviation immediately, without secondary control layer. It also utilizes maximum wind power without curtailment. These properties improve the performance of the MTDC system in post-contingency conditions. The effectiveness of the proposed control method is validated by simulation of a 4-terminal VSC-MTDC system in MATLAB/Simulink R2016a.
