342 research outputs found
Day-ahead allocation of operation reserve in composite power systems with large-scale centralized wind farms
This paper focuses on the day-ahead allocation of operation reserve considering wind power prediction error and network transmission constraints in a composite power system. A two-level model that solves the allocation problem is presented. The upper model allocates operation reserve among subsystems from the economic point of view. In the upper model, transmission constraints of tielines are formulated to represent limited reserve support from the neighboring system due to wind power fluctuation. The lower model evaluates the system on the reserve schedule from the reliability point of view. In the lower model, the reliability evaluation of composite power system is performed by using Monte Carlo simulation in a multi-area system. Wind power prediction errors and tieline constraints are incorporated. The reserve requirements in the upper model are iteratively adjusted by the resulting reliability indices from the lower model. Thus, the reserve allocation is gradually optimized until the system achieves the balance between reliability and economy. A modified two-area reliability test system (RTS) is analyzed to demonstrate the validity of the method.This work was supported by National Natural Science Foundation of China (No. 51277141) and National High Technology Research and Development Program of China (863 Program) (No. 2011AA05A103)
Dynamic Effects Increasing Network Vulnerability to Cascading Failures
We study cascading failures in networks using a dynamical flow model based on
simple conservation and distribution laws to investigate the impact of
transient dynamics caused by the rebalancing of loads after an initial network
failure (triggering event). It is found that considering the flow dynamics may
imply reduced network robustness compared to previous static overload failure
models. This is due to the transient oscillations or overshooting in the loads,
when the flow dynamics adjusts to the new (remaining) network structure. We
obtain {\em upper} and {\em lower} limits to network robustness, and it is
shown that {\it two} time scales and , defined by the network
dynamics, are important to consider prior to accurately addressing network
robustness or vulnerability. The robustness of networks showing cascading
failures is generally determined by a complex interplay between the network
topology and flow dynamics, where the ratio determines the
relative role of the two of them.Comment: 4 pages Latex, 4 figure
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